From 349aa30363742c9ebf5f330caee357b697082dd3 Mon Sep 17 00:00:00 2001 From: nf-core-bot Date: Fri, 30 Jun 2023 16:13:48 +0000 Subject: [PATCH 001/149] Template update for nf-core/tools version 2.9 --- .github/CONTRIBUTING.md | 1 - .github/ISSUE_TEMPLATE/bug_report.yml | 2 +- .github/workflows/awsfulltest.yml | 11 +- .github/workflows/awstest.yml | 10 +- .github/workflows/ci.yml | 2 +- .gitpod.yml | 5 + CITATIONS.md | 6 + README.md | 6 +- assets/methods_description_template.yml | 12 +- assets/multiqc_config.yml | 4 +- assets/nf-core-molkart_logo_light.png | Bin 10336 -> 70183 bytes assets/slackreport.json | 2 +- conf/test_full.config | 2 - docs/usage.md | 6 +- lib/NfcoreSchema.groovy | 530 ------------------------ lib/NfcoreTemplate.groovy | 2 +- lib/WorkflowMain.groovy | 37 -- lib/WorkflowMolkart.groovy | 45 +- main.nf | 16 + nextflow.config | 52 ++- nextflow_schema.json | 36 +- workflows/molkart.nf | 25 +- 22 files changed, 175 insertions(+), 637 deletions(-) delete mode 100755 lib/NfcoreSchema.groovy diff --git a/.github/CONTRIBUTING.md b/.github/CONTRIBUTING.md index b07b118..393a6c0 100644 --- a/.github/CONTRIBUTING.md +++ b/.github/CONTRIBUTING.md @@ -116,4 +116,3 @@ To get started: Devcontainer specs: - [DevContainer config](.devcontainer/devcontainer.json) -- [Dockerfile](.devcontainer/Dockerfile) diff --git a/.github/ISSUE_TEMPLATE/bug_report.yml b/.github/ISSUE_TEMPLATE/bug_report.yml index d9bf0f3..959f14a 100644 --- a/.github/ISSUE_TEMPLATE/bug_report.yml +++ b/.github/ISSUE_TEMPLATE/bug_report.yml @@ -42,7 +42,7 @@ body: attributes: label: System information description: | - * Nextflow version _(eg. 22.10.1)_ + * Nextflow version _(eg. 23.04.0)_ * Hardware _(eg. HPC, Desktop, Cloud)_ * Executor _(eg. slurm, local, awsbatch)_ * Container engine: _(e.g. Docker, Singularity, Conda, Podman, Shifter, Charliecloud, or Apptainer)_ diff --git a/.github/workflows/awsfulltest.yml b/.github/workflows/awsfulltest.yml index 1b3e7bc..1ba5bcf 100644 --- a/.github/workflows/awsfulltest.yml +++ b/.github/workflows/awsfulltest.yml @@ -14,7 +14,7 @@ jobs: runs-on: ubuntu-latest steps: - name: Launch workflow via tower - uses: seqeralabs/action-tower-launch@v1 + uses: seqeralabs/action-tower-launch@v2 # TODO nf-core: You can customise AWS full pipeline tests as required # Add full size test data (but still relatively small datasets for few samples) # on the `test_full.config` test runs with only one set of parameters @@ -22,13 +22,18 @@ jobs: workspace_id: ${{ secrets.TOWER_WORKSPACE_ID }} access_token: ${{ secrets.TOWER_ACCESS_TOKEN }} compute_env: ${{ secrets.TOWER_COMPUTE_ENV }} + revision: ${{ github.sha }} workdir: s3://${{ secrets.AWS_S3_BUCKET }}/work/molkart/work-${{ github.sha }} parameters: | { + "hook_url": "${{ secrets.MEGATESTS_ALERTS_SLACK_HOOK_URL }}", "outdir": "s3://${{ secrets.AWS_S3_BUCKET }}/molkart/results-${{ github.sha }}" } - profiles: test_full,aws_tower + profiles: test_full + - uses: actions/upload-artifact@v3 with: name: Tower debug log file - path: tower_action_*.log + path: | + tower_action_*.log + tower_action_*.json diff --git a/.github/workflows/awstest.yml b/.github/workflows/awstest.yml index b7d0785..e721f23 100644 --- a/.github/workflows/awstest.yml +++ b/.github/workflows/awstest.yml @@ -12,18 +12,22 @@ jobs: steps: # Launch workflow using Tower CLI tool action - name: Launch workflow via tower - uses: seqeralabs/action-tower-launch@v1 + uses: seqeralabs/action-tower-launch@v2 with: workspace_id: ${{ secrets.TOWER_WORKSPACE_ID }} access_token: ${{ secrets.TOWER_ACCESS_TOKEN }} compute_env: ${{ secrets.TOWER_COMPUTE_ENV }} + revision: ${{ github.sha }} workdir: s3://${{ secrets.AWS_S3_BUCKET }}/work/molkart/work-${{ github.sha }} parameters: | { "outdir": "s3://${{ secrets.AWS_S3_BUCKET }}/molkart/results-test-${{ github.sha }}" } - profiles: test,aws_tower + profiles: test + - uses: actions/upload-artifact@v3 with: name: Tower debug log file - path: tower_action_*.log + path: | + tower_action_*.log + tower_action_*.json diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index ba0cf4e..71375af 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -24,7 +24,7 @@ jobs: strategy: matrix: NXF_VER: - - "22.10.1" + - "23.04.0" - "latest-everything" steps: - name: Check out pipeline code diff --git a/.gitpod.yml b/.gitpod.yml index 85d95ec..25488dc 100644 --- a/.gitpod.yml +++ b/.gitpod.yml @@ -1,4 +1,9 @@ image: nfcore/gitpod:latest +tasks: + - name: Update Nextflow and setup pre-commit + command: | + pre-commit install --install-hooks + nextflow self-update vscode: extensions: # based on nf-core.nf-core-extensionpack diff --git a/CITATIONS.md b/CITATIONS.md index 30d55b0..0be89c4 100644 --- a/CITATIONS.md +++ b/CITATIONS.md @@ -12,7 +12,10 @@ - [FastQC](https://www.bioinformatics.babraham.ac.uk/projects/fastqc/) + > Andrews, S. (2010). FastQC: A Quality Control Tool for High Throughput Sequence Data [Online]. Available online https://www.bioinformatics.babraham.ac.uk/projects/fastqc/. + - [MultiQC](https://pubmed.ncbi.nlm.nih.gov/27312411/) + > Ewels P, Magnusson M, Lundin S, Käller M. MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics. 2016 Oct 1;32(19):3047-8. doi: 10.1093/bioinformatics/btw354. Epub 2016 Jun 16. PubMed PMID: 27312411; PubMed Central PMCID: PMC5039924. ## Software packaging/containerisation tools @@ -31,5 +34,8 @@ - [Docker](https://dl.acm.org/doi/10.5555/2600239.2600241) + > Merkel, D. (2014). Docker: lightweight linux containers for consistent development and deployment. Linux Journal, 2014(239), 2. doi: 10.5555/2600239.2600241. + - [Singularity](https://pubmed.ncbi.nlm.nih.gov/28494014/) + > Kurtzer GM, Sochat V, Bauer MW. Singularity: Scientific containers for mobility of compute. PLoS One. 2017 May 11;12(5):e0177459. doi: 10.1371/journal.pone.0177459. eCollection 2017. PubMed PMID: 28494014; PubMed Central PMCID: PMC5426675. diff --git a/README.md b/README.md index 755b849..10079c1 100644 --- a/README.md +++ b/README.md @@ -2,7 +2,7 @@ [![AWS CI](https://img.shields.io/badge/CI%20tests-full%20size-FF9900?labelColor=000000&logo=Amazon%20AWS)](https://nf-co.re/molkart/results)[![Cite with Zenodo](http://img.shields.io/badge/DOI-10.5281/zenodo.XXXXXXX-1073c8?labelColor=000000)](https://doi.org/10.5281/zenodo.XXXXXXX) -[![Nextflow](https://img.shields.io/badge/nextflow%20DSL2-%E2%89%A522.10.1-23aa62.svg)](https://www.nextflow.io/) +[![Nextflow](https://img.shields.io/badge/nextflow%20DSL2-%E2%89%A523.04.0-23aa62.svg)](https://www.nextflow.io/) [![run with conda](http://img.shields.io/badge/run%20with-conda-3EB049?labelColor=000000&logo=anaconda)](https://docs.conda.io/en/latest/) [![run with docker](https://img.shields.io/badge/run%20with-docker-0db7ed?labelColor=000000&logo=docker)](https://www.docker.com/) [![run with singularity](https://img.shields.io/badge/run%20with-singularity-1d355c.svg?labelColor=000000)](https://sylabs.io/docs/) @@ -66,11 +66,11 @@ nextflow run nf-core/molkart \ > provided by the `-c` Nextflow option can be used to provide any configuration _**except for parameters**_; > see [docs](https://nf-co.re/usage/configuration#custom-configuration-files). -For more details, please refer to the [usage documentation](https://nf-co.re/molkart/usage) and the [parameter documentation](https://nf-co.re/molkart/parameters). +For more details and further functionality, please refer to the [usage documentation](https://nf-co.re/molkart/usage) and the [parameter documentation](https://nf-co.re/molkart/parameters). ## Pipeline output -To see the the results of a test run with a full size dataset refer to the [results](https://nf-co.re/molkart/results) tab on the nf-core website pipeline page. +To see the results of an example test run with a full size dataset refer to the [results](https://nf-co.re/molkart/results) tab on the nf-core website pipeline page. For more details about the output files and reports, please refer to the [output documentation](https://nf-co.re/molkart/output). diff --git a/assets/methods_description_template.yml b/assets/methods_description_template.yml index fcc76d5..74dd468 100644 --- a/assets/methods_description_template.yml +++ b/assets/methods_description_template.yml @@ -3,17 +3,21 @@ description: "Suggested text and references to use when describing pipeline usag section_name: "nf-core/molkart Methods Description" section_href: "https://github.com/nf-core/molkart" plot_type: "html" -## TODO nf-core: Update the HTML below to your prefered methods description, e.g. add publication citation for this pipeline +## TODO nf-core: Update the HTML below to your preferred methods description, e.g. add publication citation for this pipeline ## You inject any metadata in the Nextflow '${workflow}' object data: |

Methods

-

Data was processed using nf-core/molkart v${workflow.manifest.version} ${doi_text} of the nf-core collection of workflows (Ewels et al., 2020).

+

Data was processed using nf-core/molkart v${workflow.manifest.version} ${doi_text} of the nf-core collection of workflows (Ewels et al., 2020), utilising reproducible software environments from the Bioconda (Grüning et al., 2018) and Biocontainers (da Veiga Leprevost et al., 2017) projects.

The pipeline was executed with Nextflow v${workflow.nextflow.version} (Di Tommaso et al., 2017) with the following command:

${workflow.commandLine}
+

${tool_citations}

References

Notes:
diff --git a/assets/multiqc_config.yml b/assets/multiqc_config.yml index 002ca4c..2ba4d57 100644 --- a/assets/multiqc_config.yml +++ b/assets/multiqc_config.yml @@ -1,7 +1,7 @@ report_comment: > - This report has been generated by the nf-core/molkart + This report has been generated by the nf-core/molkart analysis pipeline. 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@@ { "fallback": "Plain-text summary of the attachment.", "color": "<% if (success) { %>good<% } else { %>danger<%} %>", - "author_name": "sanger-tol/readmapping v${version} - ${runName}", + "author_name": "nf-core/molkart v${version} - ${runName}", "author_icon": "https://www.nextflow.io/docs/latest/_static/favicon.ico", "text": "<% if (success) { %>Pipeline completed successfully!<% } else { %>Pipeline completed with errors<% } %>", "fields": [ diff --git a/conf/test_full.config b/conf/test_full.config index ce72ba6..e0e4cef 100644 --- a/conf/test_full.config +++ b/conf/test_full.config @@ -10,8 +10,6 @@ ---------------------------------------------------------------------------------------- */ -cleanup = true - params { config_profile_name = 'Full test profile' config_profile_description = 'Full test dataset to check pipeline function' diff --git a/docs/usage.md b/docs/usage.md index 3353f83..9fbd003 100644 --- a/docs/usage.md +++ b/docs/usage.md @@ -57,7 +57,7 @@ An [example samplesheet](../assets/samplesheet.csv) has been provided with the p The typical command for running the pipeline is as follows: ```bash -nextflow run nf-core/molkart --input samplesheet.csv --outdir --genome GRCh37 -profile docker +nextflow run nf-core/molkart --input ./samplesheet.csv --outdir ./results --genome GRCh37 -profile docker ``` This will launch the pipeline with the `docker` configuration profile. See below for more information about profiles. @@ -76,7 +76,8 @@ If you wish to repeatedly use the same parameters for multiple runs, rather than Pipeline settings can be provided in a `yaml` or `json` file via `-params-file `. > ⚠️ Do not use `-c ` to specify parameters as this will result in errors. Custom config files specified with `-c` must only be used for [tuning process resource specifications](https://nf-co.re/docs/usage/configuration#tuning-workflow-resources), other infrastructural tweaks (such as output directories), or module arguments (args). -> The above pipeline run specified with a params file in yaml format: + +The above pipeline run specified with a params file in yaml format: ```bash nextflow run nf-core/molkart -profile docker -params-file params.yaml @@ -88,7 +89,6 @@ with `params.yaml` containing: input: './samplesheet.csv' outdir: './results/' genome: 'GRCh37' -input: 'data' <...> ``` diff --git a/lib/NfcoreSchema.groovy b/lib/NfcoreSchema.groovy deleted file mode 100755 index 9b34804..0000000 --- a/lib/NfcoreSchema.groovy +++ /dev/null @@ -1,530 +0,0 @@ -// -// This file holds several functions used to perform JSON parameter validation, help and summary rendering for the nf-core pipeline template. -// - -import nextflow.Nextflow -import org.everit.json.schema.Schema -import org.everit.json.schema.loader.SchemaLoader -import org.everit.json.schema.ValidationException -import org.json.JSONObject -import org.json.JSONTokener -import org.json.JSONArray -import groovy.json.JsonSlurper -import groovy.json.JsonBuilder - -class NfcoreSchema { - - // - // Resolve Schema path relative to main workflow directory - // - public static String getSchemaPath(workflow, schema_filename='nextflow_schema.json') { - return "${workflow.projectDir}/${schema_filename}" - } - - // - // Function to loop over all parameters defined in schema and check - // whether the given parameters adhere to the specifications - // - /* groovylint-disable-next-line UnusedPrivateMethodParameter */ - public static void validateParameters(workflow, params, log, schema_filename='nextflow_schema.json') { - def has_error = false - //~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~// - // Check for nextflow core params and unexpected params - def json = new File(getSchemaPath(workflow, schema_filename=schema_filename)).text - def Map schemaParams = (Map) new JsonSlurper().parseText(json).get('definitions') - def nf_params = [ - // Options for base `nextflow` command - 'bg', - 'c', - 'C', - 'config', - 'd', - 'D', - 'dockerize', - 'h', - 'log', - 'q', - 'quiet', - 'syslog', - 'v', - - // Options for `nextflow run` command - 'ansi', - 'ansi-log', - 'bg', - 'bucket-dir', - 'c', - 'cache', - 'config', - 'dsl2', - 'dump-channels', - 'dump-hashes', - 'E', - 'entry', - 'latest', - 'lib', - 'main-script', - 'N', - 'name', - 'offline', - 'params-file', - 'pi', - 'plugins', - 'poll-interval', - 'pool-size', - 'profile', - 'ps', - 'qs', - 'queue-size', - 'r', - 'resume', - 'revision', - 'stdin', - 'stub', - 'stub-run', - 'test', - 'w', - 'with-apptainer', - 'with-charliecloud', - 'with-conda', - 'with-dag', - 'with-docker', - 'with-mpi', - 'with-notification', - 'with-podman', - 'with-report', - 'with-singularity', - 'with-timeline', - 'with-tower', - 'with-trace', - 'with-weblog', - 'without-docker', - 'without-podman', - 'work-dir' - ] - def unexpectedParams = [] - - // Collect expected parameters from the schema - def expectedParams = [] - def enums = [:] - for (group in schemaParams) { - for (p in group.value['properties']) { - expectedParams.push(p.key) - if (group.value['properties'][p.key].containsKey('enum')) { - enums[p.key] = group.value['properties'][p.key]['enum'] - } - } - } - - for (specifiedParam in params.keySet()) { - // nextflow params - if (nf_params.contains(specifiedParam)) { - log.error "ERROR: You used a core Nextflow option with two hyphens: '--${specifiedParam}'. Please resubmit with '-${specifiedParam}'" - has_error = true - } - // unexpected params - def params_ignore = params.schema_ignore_params.split(',') + 'schema_ignore_params' - def expectedParamsLowerCase = expectedParams.collect{ it.replace("-", "").toLowerCase() } - def specifiedParamLowerCase = specifiedParam.replace("-", "").toLowerCase() - def isCamelCaseBug = (specifiedParam.contains("-") && !expectedParams.contains(specifiedParam) && expectedParamsLowerCase.contains(specifiedParamLowerCase)) - if (!expectedParams.contains(specifiedParam) && !params_ignore.contains(specifiedParam) && !isCamelCaseBug) { - // Temporarily remove camelCase/camel-case params #1035 - def unexpectedParamsLowerCase = unexpectedParams.collect{ it.replace("-", "").toLowerCase()} - if (!unexpectedParamsLowerCase.contains(specifiedParamLowerCase)){ - unexpectedParams.push(specifiedParam) - } - } - } - - //~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~// - // Validate parameters against the schema - InputStream input_stream = new File(getSchemaPath(workflow, schema_filename=schema_filename)).newInputStream() - JSONObject raw_schema = new JSONObject(new JSONTokener(input_stream)) - - // Remove anything that's in params.schema_ignore_params - raw_schema = removeIgnoredParams(raw_schema, params) - - Schema schema = SchemaLoader.load(raw_schema) - - // Clean the parameters - def cleanedParams = cleanParameters(params) - - // Convert to JSONObject - def jsonParams = new JsonBuilder(cleanedParams) - JSONObject params_json = new JSONObject(jsonParams.toString()) - - // Validate - try { - schema.validate(params_json) - } catch (ValidationException e) { - println '' - log.error 'ERROR: Validation of pipeline parameters failed!' - JSONObject exceptionJSON = e.toJSON() - printExceptions(exceptionJSON, params_json, log, enums) - println '' - has_error = true - } - - // Check for unexpected parameters - if (unexpectedParams.size() > 0) { - Map colors = NfcoreTemplate.logColours(params.monochrome_logs) - println '' - def warn_msg = 'Found unexpected parameters:' - for (unexpectedParam in unexpectedParams) { - warn_msg = warn_msg + "\n* --${unexpectedParam}: ${params[unexpectedParam].toString()}" - } - log.warn warn_msg - log.info "- ${colors.dim}Ignore this warning: params.schema_ignore_params = \"${unexpectedParams.join(',')}\" ${colors.reset}" - println '' - } - - if (has_error) { - Nextflow.error('Exiting!') - } - } - - // - // Beautify parameters for --help - // - public static String paramsHelp(workflow, params, command, schema_filename='nextflow_schema.json') { - Map colors = NfcoreTemplate.logColours(params.monochrome_logs) - Integer num_hidden = 0 - String output = '' - output += 'Typical pipeline command:\n\n' - output += " ${colors.cyan}${command}${colors.reset}\n\n" - Map params_map = paramsLoad(getSchemaPath(workflow, schema_filename=schema_filename)) - Integer max_chars = paramsMaxChars(params_map) + 1 - Integer desc_indent = max_chars + 14 - Integer dec_linewidth = 160 - desc_indent - for (group in params_map.keySet()) { - Integer num_params = 0 - String group_output = colors.underlined + colors.bold + group + colors.reset + '\n' - def group_params = params_map.get(group) // This gets the parameters of that particular group - for (param in group_params.keySet()) { - if (group_params.get(param).hidden && !params.show_hidden_params) { - num_hidden += 1 - continue; - } - def type = '[' + group_params.get(param).type + ']' - def description = group_params.get(param).description - def defaultValue = group_params.get(param).default != null ? " [default: " + group_params.get(param).default.toString() + "]" : '' - def description_default = description + colors.dim + defaultValue + colors.reset - // Wrap long description texts - // Loosely based on https://dzone.com/articles/groovy-plain-text-word-wrap - if (description_default.length() > dec_linewidth){ - List olines = [] - String oline = "" // " " * indent - description_default.split(" ").each() { wrd -> - if ((oline.size() + wrd.size()) <= dec_linewidth) { - oline += wrd + " " - } else { - olines += oline - oline = wrd + " " - } - } - olines += oline - description_default = olines.join("\n" + " " * desc_indent) - } - group_output += " --" + param.padRight(max_chars) + colors.dim + type.padRight(10) + colors.reset + description_default + '\n' - num_params += 1 - } - group_output += '\n' - if (num_params > 0){ - output += group_output - } - } - if (num_hidden > 0){ - output += colors.dim + "!! Hiding $num_hidden params, use --show_hidden_params to show them !!\n" + colors.reset - } - output += NfcoreTemplate.dashedLine(params.monochrome_logs) - return output - } - - // - // Groovy Map summarising parameters/workflow options used by the pipeline - // - public static LinkedHashMap paramsSummaryMap(workflow, params, schema_filename='nextflow_schema.json') { - // Get a selection of core Nextflow workflow options - def Map workflow_summary = [:] - if (workflow.revision) { - workflow_summary['revision'] = workflow.revision - } - workflow_summary['runName'] = workflow.runName - if (workflow.containerEngine) { - workflow_summary['containerEngine'] = workflow.containerEngine - } - if (workflow.container) { - workflow_summary['container'] = workflow.container - } - workflow_summary['launchDir'] = workflow.launchDir - workflow_summary['workDir'] = workflow.workDir - workflow_summary['projectDir'] = workflow.projectDir - workflow_summary['userName'] = workflow.userName - workflow_summary['profile'] = workflow.profile - workflow_summary['configFiles'] = workflow.configFiles.join(', ') - - // Get pipeline parameters defined in JSON Schema - def Map params_summary = [:] - def params_map = paramsLoad(getSchemaPath(workflow, schema_filename=schema_filename)) - for (group in params_map.keySet()) { - def sub_params = new LinkedHashMap() - def group_params = params_map.get(group) // This gets the parameters of that particular group - for (param in group_params.keySet()) { - if (params.containsKey(param)) { - def params_value = params.get(param) - def schema_value = group_params.get(param).default - def param_type = group_params.get(param).type - if (schema_value != null) { - if (param_type == 'string') { - if (schema_value.contains('$projectDir') || schema_value.contains('${projectDir}')) { - def sub_string = schema_value.replace('\$projectDir', '') - sub_string = sub_string.replace('\${projectDir}', '') - if (params_value.contains(sub_string)) { - schema_value = params_value - } - } - if (schema_value.contains('$params.outdir') || schema_value.contains('${params.outdir}')) { - def sub_string = schema_value.replace('\$params.outdir', '') - sub_string = sub_string.replace('\${params.outdir}', '') - if ("${params.outdir}${sub_string}" == params_value) { - schema_value = params_value - } - } - } - } - - // We have a default in the schema, and this isn't it - if (schema_value != null && params_value != schema_value) { - sub_params.put(param, params_value) - } - // No default in the schema, and this isn't empty - else if (schema_value == null && params_value != "" && params_value != null && params_value != false) { - sub_params.put(param, params_value) - } - } - } - params_summary.put(group, sub_params) - } - return [ 'Core Nextflow options' : workflow_summary ] << params_summary - } - - // - // Beautify parameters for summary and return as string - // - public static String paramsSummaryLog(workflow, params) { - Map colors = NfcoreTemplate.logColours(params.monochrome_logs) - String output = '' - def params_map = paramsSummaryMap(workflow, params) - def max_chars = paramsMaxChars(params_map) - for (group in params_map.keySet()) { - def group_params = params_map.get(group) // This gets the parameters of that particular group - if (group_params) { - output += colors.bold + group + colors.reset + '\n' - for (param in group_params.keySet()) { - output += " " + colors.blue + param.padRight(max_chars) + ": " + colors.green + group_params.get(param) + colors.reset + '\n' - } - output += '\n' - } - } - output += "!! Only displaying parameters that differ from the pipeline defaults !!\n" - output += NfcoreTemplate.dashedLine(params.monochrome_logs) - return output - } - - // - // Loop over nested exceptions and print the causingException - // - private static void printExceptions(ex_json, params_json, log, enums, limit=5) { - def causingExceptions = ex_json['causingExceptions'] - if (causingExceptions.length() == 0) { - def m = ex_json['message'] =~ /required key \[([^\]]+)\] not found/ - // Missing required param - if (m.matches()) { - log.error "* Missing required parameter: --${m[0][1]}" - } - // Other base-level error - else if (ex_json['pointerToViolation'] == '#') { - log.error "* ${ex_json['message']}" - } - // Error with specific param - else { - def param = ex_json['pointerToViolation'] - ~/^#\// - def param_val = params_json[param].toString() - if (enums.containsKey(param)) { - def error_msg = "* --${param}: '${param_val}' is not a valid choice (Available choices" - if (enums[param].size() > limit) { - log.error "${error_msg} (${limit} of ${enums[param].size()}): ${enums[param][0..limit-1].join(', ')}, ... )" - } else { - log.error "${error_msg}: ${enums[param].join(', ')})" - } - } else { - log.error "* --${param}: ${ex_json['message']} (${param_val})" - } - } - } - for (ex in causingExceptions) { - printExceptions(ex, params_json, log, enums) - } - } - - // - // Remove an element from a JSONArray - // - private static JSONArray removeElement(json_array, element) { - def list = [] - int len = json_array.length() - for (int i=0;i - if(raw_schema.keySet().contains('definitions')){ - raw_schema.definitions.each { definition -> - for (key in definition.keySet()){ - if (definition[key].get("properties").keySet().contains(ignore_param)){ - // Remove the param to ignore - definition[key].get("properties").remove(ignore_param) - // If the param was required, change this - if (definition[key].has("required")) { - def cleaned_required = removeElement(definition[key].required, ignore_param) - definition[key].put("required", cleaned_required) - } - } - } - } - } - if(raw_schema.keySet().contains('properties') && raw_schema.get('properties').keySet().contains(ignore_param)) { - raw_schema.get("properties").remove(ignore_param) - } - if(raw_schema.keySet().contains('required') && raw_schema.required.contains(ignore_param)) { - def cleaned_required = removeElement(raw_schema.required, ignore_param) - raw_schema.put("required", cleaned_required) - } - } - return raw_schema - } - - // - // Clean and check parameters relative to Nextflow native classes - // - private static Map cleanParameters(params) { - def new_params = params.getClass().newInstance(params) - for (p in params) { - // remove anything evaluating to false - if (!p['value']) { - new_params.remove(p.key) - } - // Cast MemoryUnit to String - if (p['value'].getClass() == nextflow.util.MemoryUnit) { - new_params.replace(p.key, p['value'].toString()) - } - // Cast Duration to String - if (p['value'].getClass() == nextflow.util.Duration) { - new_params.replace(p.key, p['value'].toString().replaceFirst(/d(?!\S)/, "day")) - } - // Cast LinkedHashMap to String - if (p['value'].getClass() == LinkedHashMap) { - new_params.replace(p.key, p['value'].toString()) - } - } - return new_params - } - - // - // This function tries to read a JSON params file - // - private static LinkedHashMap paramsLoad(String json_schema) { - def params_map = new LinkedHashMap() - try { - params_map = paramsRead(json_schema) - } catch (Exception e) { - println "Could not read parameters settings from JSON. $e" - params_map = new LinkedHashMap() - } - return params_map - } - - // - // Method to actually read in JSON file using Groovy. - // Group (as Key), values are all parameters - // - Parameter1 as Key, Description as Value - // - Parameter2 as Key, Description as Value - // .... - // Group - // - - private static LinkedHashMap paramsRead(String json_schema) throws Exception { - def json = new File(json_schema).text - def Map schema_definitions = (Map) new JsonSlurper().parseText(json).get('definitions') - def Map schema_properties = (Map) new JsonSlurper().parseText(json).get('properties') - /* Tree looks like this in nf-core schema - * definitions <- this is what the first get('definitions') gets us - group 1 - title - description - properties - parameter 1 - type - description - parameter 2 - type - description - group 2 - title - description - properties - parameter 1 - type - description - * properties <- parameters can also be ungrouped, outside of definitions - parameter 1 - type - description - */ - - // Grouped params - def params_map = new LinkedHashMap() - schema_definitions.each { key, val -> - def Map group = schema_definitions."$key".properties // Gets the property object of the group - def title = schema_definitions."$key".title - def sub_params = new LinkedHashMap() - group.each { innerkey, value -> - sub_params.put(innerkey, value) - } - params_map.put(title, sub_params) - } - - // Ungrouped params - def ungrouped_params = new LinkedHashMap() - schema_properties.each { innerkey, value -> - ungrouped_params.put(innerkey, value) - } - params_map.put("Other parameters", ungrouped_params) - - return params_map - } - - // - // Get maximum number of characters across all parameter names - // - private static Integer paramsMaxChars(params_map) { - Integer max_chars = 0 - for (group in params_map.keySet()) { - def group_params = params_map.get(group) // This gets the parameters of that particular group - for (param in group_params.keySet()) { - if (param.size() > max_chars) { - max_chars = param.size() - } - } - } - return max_chars - } -} diff --git a/lib/NfcoreTemplate.groovy b/lib/NfcoreTemplate.groovy index 25a0a74..408951a 100755 --- a/lib/NfcoreTemplate.groovy +++ b/lib/NfcoreTemplate.groovy @@ -128,7 +128,7 @@ class NfcoreTemplate { def email_html = html_template.toString() // Render the sendmail template - def max_multiqc_email_size = params.max_multiqc_email_size as nextflow.util.MemoryUnit + def max_multiqc_email_size = (params.containsKey('max_multiqc_email_size') ? params.max_multiqc_email_size : 0) as nextflow.util.MemoryUnit def smail_fields = [ email: email_address, subject: subject, email_txt: email_txt, email_html: email_html, projectDir: "$projectDir", mqcFile: mqc_report, mqcMaxSize: max_multiqc_email_size.toBytes() ] def sf = new File("$projectDir/assets/sendmail_template.txt") def sendmail_template = engine.createTemplate(sf).make(smail_fields) diff --git a/lib/WorkflowMain.groovy b/lib/WorkflowMain.groovy index 6e080d9..aebe9cc 100755 --- a/lib/WorkflowMain.groovy +++ b/lib/WorkflowMain.groovy @@ -20,40 +20,11 @@ class WorkflowMain { " https://github.com/${workflow.manifest.name}/blob/master/CITATIONS.md" } - // - // Generate help string - // - public static String help(workflow, params) { - def command = "nextflow run ${workflow.manifest.name} --input samplesheet.csv --genome GRCh37 -profile docker" - def help_string = '' - help_string += NfcoreTemplate.logo(workflow, params.monochrome_logs) - help_string += NfcoreSchema.paramsHelp(workflow, params, command) - help_string += '\n' + citation(workflow) + '\n' - help_string += NfcoreTemplate.dashedLine(params.monochrome_logs) - return help_string - } - - // - // Generate parameter summary log string - // - public static String paramsSummaryLog(workflow, params) { - def summary_log = '' - summary_log += NfcoreTemplate.logo(workflow, params.monochrome_logs) - summary_log += NfcoreSchema.paramsSummaryLog(workflow, params) - summary_log += '\n' + citation(workflow) + '\n' - summary_log += NfcoreTemplate.dashedLine(params.monochrome_logs) - return summary_log - } // // Validate parameters and print summary to screen // public static void initialise(workflow, params, log) { - // Print help to screen if required - if (params.help) { - log.info help(workflow, params) - System.exit(0) - } // Print workflow version and exit on --version if (params.version) { @@ -62,14 +33,6 @@ class WorkflowMain { System.exit(0) } - // Print parameter summary log to screen - log.info paramsSummaryLog(workflow, params) - - // Validate workflow parameters via the JSON schema - if (params.validate_params) { - NfcoreSchema.validateParameters(workflow, params, log) - } - // Check that a -profile or Nextflow config has been provided to run the pipeline NfcoreTemplate.checkConfigProvided(workflow, log) diff --git a/lib/WorkflowMolkart.groovy b/lib/WorkflowMolkart.groovy index f23ab88..f64d19e 100755 --- a/lib/WorkflowMolkart.groovy +++ b/lib/WorkflowMolkart.groovy @@ -11,6 +11,7 @@ class WorkflowMolkart { // Check and validate parameters // public static void initialise(params, log) { + genomeExistsError(params, log) @@ -46,15 +47,57 @@ class WorkflowMolkart { return yaml_file_text } - public static String methodsDescriptionText(run_workflow, mqc_methods_yaml) { + // + // Generate methods description for MultiQC + // + + public static String toolCitationText(params) { + + // TODO Optionally add in-text citation tools to this list. + // Can use ternary operators to dynamically construct based conditions, e.g. params["run_xyz"] ? "Tool (Foo et al. 2023)" : "", + // Uncomment function in methodsDescriptionText to render in MultiQC report + def citation_text = [ + "Tools used in the workflow included:", + "FastQC (Andrews 2010),", + "MultiQC (Ewels et al. 2016)", + "." + ].join(' ').trim() + + return citation_text + } + + public static String toolBibliographyText(params) { + + // TODO Optionally add bibliographic entries to this list. + // Can use ternary operators to dynamically construct based conditions, e.g. params["run_xyz"] ? "

  • Author (2023) Pub name, Journal, DOI
  • " : "", + // Uncomment function in methodsDescriptionText to render in MultiQC report + def reference_text = [ + "
  • Andrews S, (2010) FastQC, URL: https://www.bioinformatics.babraham.ac.uk/projects/fastqc/).
  • ", + "
  • Ewels, P., Magnusson, M., Lundin, S., & Käller, M. (2016). MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics , 32(19), 3047–3048. doi: /10.1093/bioinformatics/btw354
  • " + ].join(' ').trim() + + return reference_text + } + + public static String methodsDescriptionText(run_workflow, mqc_methods_yaml, params) { // Convert to a named map so can be used as with familar NXF ${workflow} variable syntax in the MultiQC YML file def meta = [:] meta.workflow = run_workflow.toMap() meta["manifest_map"] = run_workflow.manifest.toMap() + // Pipeline DOI meta["doi_text"] = meta.manifest_map.doi ? "(doi: ${meta.manifest_map.doi})" : "" meta["nodoi_text"] = meta.manifest_map.doi ? "": "
  • If available, make sure to update the text to include the Zenodo DOI of version of the pipeline used.
  • " + // Tool references + meta["tool_citations"] = "" + meta["tool_bibliography"] = "" + + // TODO Only uncomment below if logic in toolCitationText/toolBibliographyText has been filled! + //meta["tool_citations"] = toolCitationText(params).replaceAll(", \\.", ".").replaceAll("\\. \\.", ".").replaceAll(", \\.", ".") + //meta["tool_bibliography"] = toolBibliographyText(params) + + def methods_text = mqc_methods_yaml.text def engine = new SimpleTemplateEngine() diff --git a/main.nf b/main.nf index afd47ed..b967761 100644 --- a/main.nf +++ b/main.nf @@ -25,6 +25,22 @@ params.fasta = WorkflowMain.getGenomeAttribute(params, 'fasta') ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ */ +include { validateParameters; paramsHelp } from 'plugin/nf-validation' + +// Print help message if needed +if (params.help) { + def logo = NfcoreTemplate.logo(workflow, params.monochrome_logs) + def citation = '\n' + WorkflowMain.citation(workflow) + '\n' + def String command = "nextflow run ${workflow.manifest.name} --input samplesheet.csv --genome GRCh37 -profile docker" + log.info logo + paramsHelp(command) + citation + NfcoreTemplate.dashedLine(params.monochrome_logs) + System.exit(0) +} + +// Validate input parameters +if (params.validate_params) { + validateParameters() +} + WorkflowMain.initialise(workflow, params, log) /* diff --git a/nextflow.config b/nextflow.config index 9986acb..533249d 100644 --- a/nextflow.config +++ b/nextflow.config @@ -12,12 +12,12 @@ params { // TODO nf-core: Specify your pipeline's command line flags // Input options input = null - - // References genome = null igenomes_base = 's3://ngi-igenomes/igenomes' igenomes_ignore = false + + // MultiQC options multiqc_config = null multiqc_title = null @@ -27,7 +27,6 @@ params { // Boilerplate options outdir = null - tracedir = "${params.outdir}/pipeline_info" publish_dir_mode = 'copy' email = null email_on_fail = null @@ -36,19 +35,15 @@ params { hook_url = null help = false version = false - validate_params = true - show_hidden_params = false - schema_ignore_params = 'genomes' - // Config options + config_profile_name = null + config_profile_description = null custom_config_version = 'master' custom_config_base = "https://raw.githubusercontent.com/nf-core/configs/${params.custom_config_version}" - config_profile_description = null config_profile_contact = null config_profile_url = null - config_profile_name = null - + // Max resource options // Defaults only, expecting to be overwritten @@ -56,6 +51,13 @@ params { max_cpus = 16 max_time = '240.h' + // Schema validation default options + validationFailUnrecognisedParams = false + validationLenientMode = false + validationSchemaIgnoreParams = 'genomes' + validationShowHiddenParams = false + validate_params = true + } // Load base.config by default for all pipelines @@ -75,13 +77,11 @@ try { // } catch (Exception e) { // System.err.println("WARNING: Could not load nf-core/config/molkart profiles: ${params.custom_config_base}/pipeline/molkart.config") // } - - profiles { debug { dumpHashes = true process.beforeScript = 'echo $HOSTNAME' - cleanup = false + cleanup = false } conda { conda.enabled = true @@ -104,7 +104,6 @@ profiles { } docker { docker.enabled = true - docker.registry = 'quay.io' docker.userEmulation = true conda.enabled = false singularity.enabled = false @@ -128,7 +127,6 @@ profiles { } podman { podman.enabled = true - podman.registry = 'quay.io' conda.enabled = false docker.enabled = false singularity.enabled = false @@ -172,6 +170,18 @@ profiles { test_full { includeConfig 'conf/test_full.config' } } +// Set default registry for Apptainer, Docker, Podman and Singularity independent of -profile +// Will not be used unless Apptainer / Docker / Podman / Singularity are enabled +// Set to your registry if you have a mirror of containers +apptainer.registry = 'quay.io' +docker.registry = 'quay.io' +podman.registry = 'quay.io' +singularity.registry = 'quay.io' + +// Nextflow plugins +plugins { + id 'nf-validation' // Validation of pipeline parameters and creation of an input channel from a sample sheet +} // Load igenomes.config if required if (!params.igenomes_ignore) { @@ -179,8 +189,6 @@ if (!params.igenomes_ignore) { } else { params.genomes = [:] } - - // Export these variables to prevent local Python/R libraries from conflicting with those in the container // The JULIA depot path has been adjusted to a fixed path `/usr/local/share/julia` that needs to be used for packages in the container. // See https://apeltzer.github.io/post/03-julia-lang-nextflow/ for details on that. Once we have a common agreement on where to keep Julia packages, this is adjustable. @@ -198,19 +206,19 @@ process.shell = ['/bin/bash', '-euo', 'pipefail'] def trace_timestamp = new java.util.Date().format( 'yyyy-MM-dd_HH-mm-ss') timeline { enabled = true - file = "${params.tracedir}/execution_timeline_${trace_timestamp}.html" + file = "${params.outdir}/pipeline_info/execution_timeline_${trace_timestamp}.html" } report { enabled = true - file = "${params.tracedir}/execution_report_${trace_timestamp}.html" + file = "${params.outdir}/pipeline_info/execution_report_${trace_timestamp}.html" } trace { enabled = true - file = "${params.tracedir}/execution_trace_${trace_timestamp}.txt" + file = "${params.outdir}/pipeline_info/execution_trace_${trace_timestamp}.txt" } dag { enabled = true - file = "${params.tracedir}/pipeline_dag_${trace_timestamp}.html" + file = "${params.outdir}/pipeline_info/pipeline_dag_${trace_timestamp}.html" } manifest { @@ -219,7 +227,7 @@ manifest { homePage = 'https://github.com/nf-core/molkart' description = """An analysis pipeline for Molecular Cartography data from Resolve Biosciences.""" mainScript = 'main.nf' - nextflowVersion = '!>=22.10.1' + nextflowVersion = '!>=23.04.0' version = '1.0dev' doi = '' } diff --git a/nextflow_schema.json b/nextflow_schema.json index e50b8fd..ba0e791 100644 --- a/nextflow_schema.json +++ b/nextflow_schema.json @@ -15,9 +15,9 @@ "input": { "type": "string", "format": "file-path", + "exists": true, "mimetype": "text/csv", "pattern": "^\\S+\\.csv$", - "schema": "assets/schema_input.json", "description": "Path to comma-separated file containing information about the samples in the experiment.", "help_text": "You will need to create a design file with information about the samples in your experiment before running the pipeline. Use this parameter to specify its location. It has to be a comma-separated file with 3 columns, and a header row. See [usage docs](https://nf-co.re/molkart/usage#samplesheet-input).", "fa_icon": "fas fa-file-csv" @@ -57,6 +57,7 @@ "fasta": { "type": "string", "format": "file-path", + "exists": true, "mimetype": "text/plain", "pattern": "^\\S+\\.fn?a(sta)?(\\.gz)?$", "description": "Path to FASTA genome file.", @@ -157,7 +158,7 @@ "description": "Maximum amount of time that can be requested for any single job.", "default": "240.h", "fa_icon": "far fa-clock", - "pattern": "^(\\d+\\.?\\s*(s|m|h|day)\\s*)+$", + "pattern": "^(\\d+\\.?\\s*(s|m|h|d|day)\\s*)+$", "hidden": true, "help_text": "Use to set an upper-limit for the time requirement for each process. Should be a string in the format integer-unit e.g. `--max_time '2.h'`" } @@ -174,12 +175,14 @@ "type": "boolean", "description": "Display help text.", "fa_icon": "fas fa-question-circle", + "default": false, "hidden": true }, "version": { "type": "boolean", "description": "Display version and exit.", "fa_icon": "fas fa-question-circle", + "default": false, "hidden": true }, "publish_dir_mode": { @@ -203,6 +206,7 @@ "type": "boolean", "description": "Send plain-text email instead of HTML.", "fa_icon": "fas fa-remove-format", + "default": false, "hidden": true }, "max_multiqc_email_size": { @@ -217,6 +221,7 @@ "type": "boolean", "description": "Do not use coloured log outputs.", "fa_icon": "fas fa-palette", + "default": false, "hidden": true }, "hook_url": { @@ -228,6 +233,7 @@ }, "multiqc_config": { "type": "string", + "format": "file-path", "description": "Custom config file to supply to MultiQC.", "fa_icon": "fas fa-cog", "hidden": true @@ -243,13 +249,6 @@ "description": "Custom MultiQC yaml file containing HTML including a methods description.", "fa_icon": "fas fa-cog" }, - "tracedir": { - "type": "string", - "description": "Directory to keep pipeline Nextflow logs and reports.", - "default": "${params.outdir}/pipeline_info", - "fa_icon": "fas fa-cogs", - "hidden": true - }, "validate_params": { "type": "boolean", "description": "Boolean whether to validate parameters against the schema at runtime", @@ -257,12 +256,29 @@ "fa_icon": "fas fa-check-square", "hidden": true }, - "show_hidden_params": { + "validationShowHiddenParams": { "type": "boolean", "fa_icon": "far fa-eye-slash", "description": "Show all params when using `--help`", + "default": false, "hidden": true, "help_text": "By default, parameters set as _hidden_ in the schema are not shown on the command line when a user runs with `--help`. Specifying this option will tell the pipeline to show all parameters." + }, + "validationFailUnrecognisedParams": { + "type": "boolean", + "fa_icon": "far fa-check-circle", + "description": "Validation of parameters fails when an unrecognised parameter is found.", + "default": false, + "hidden": true, + "help_text": "By default, when an unrecognised parameter is found, it returns a warinig." + }, + "validationLenientMode": { + "type": "boolean", + "fa_icon": "far fa-check-circle", + "description": "Validation of parameters in lenient more.", + "default": false, + "hidden": true, + "help_text": "Allows string values that are parseable as numbers or booleans. For further information see [JSONSchema docs](https://github.com/everit-org/json-schema#lenient-mode)." } } } diff --git a/workflows/molkart.nf b/workflows/molkart.nf index b991898..2e9aada 100644 --- a/workflows/molkart.nf +++ b/workflows/molkart.nf @@ -1,21 +1,19 @@ /* ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - VALIDATE INPUTS + PRINT PARAMS SUMMARY ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ */ -def summary_params = NfcoreSchema.paramsSummaryMap(workflow, params) +include { paramsSummaryLog; paramsSummaryMap } from 'plugin/nf-validation' -// Validate input parameters -WorkflowMolkart.initialise(params, log) +def logo = NfcoreTemplate.logo(workflow, params.monochrome_logs) +def citation = '\n' + WorkflowMain.citation(workflow) + '\n' +def summary_params = paramsSummaryMap(workflow) -// TODO nf-core: Add all file path parameters for the pipeline to the list below -// Check input path parameters to see if they exist -def checkPathParamList = [ params.input, params.multiqc_config, params.fasta ] -for (param in checkPathParamList) { if (param) { file(param, checkIfExists: true) } } +// Print parameter summary log to screen +log.info logo + paramsSummaryLog(workflow) + citation -// Check mandatory parameters -if (params.input) { ch_input = file(params.input) } else { exit 1, 'Input samplesheet not specified!' } +WorkflowMolkart.initialise(params, log) /* ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ @@ -69,9 +67,12 @@ workflow MOLKART { // SUBWORKFLOW: Read in samplesheet, validate and stage input files // INPUT_CHECK ( - ch_input + file(params.input) ) ch_versions = ch_versions.mix(INPUT_CHECK.out.versions) + // TODO: OPTIONAL, you can use nf-validation plugin to create an input channel from the samplesheet with Channel.fromSamplesheet("input") + // See the documentation https://nextflow-io.github.io/nf-validation/samplesheets/fromSamplesheet/ + // ! There is currently no tooling to help you write a sample sheet schema // // MODULE: Run FastQC @@ -91,7 +92,7 @@ workflow MOLKART { workflow_summary = WorkflowMolkart.paramsSummaryMultiqc(workflow, summary_params) ch_workflow_summary = Channel.value(workflow_summary) - methods_description = WorkflowMolkart.methodsDescriptionText(workflow, ch_multiqc_custom_methods_description) + methods_description = WorkflowMolkart.methodsDescriptionText(workflow, ch_multiqc_custom_methods_description, params) ch_methods_description = Channel.value(methods_description) ch_multiqc_files = Channel.empty() From 78c9c5159b6d59ff8cce260c578af4ae2636b429 Mon Sep 17 00:00:00 2001 From: Florian Wuennemann Date: Thu, 13 Jul 2023 08:51:46 +0000 Subject: [PATCH 002/149] Updated README to include note about development phase. --- README.md | 10 ++++------ 1 file changed, 4 insertions(+), 6 deletions(-) diff --git a/README.md b/README.md index 755b849..4a3c6df 100644 --- a/README.md +++ b/README.md @@ -10,15 +10,13 @@ [![Get help on Slack](http://img.shields.io/badge/slack-nf--core%20%23molkart-4A154B?labelColor=000000&logo=slack)](https://nfcore.slack.com/channels/molkart)[![Follow on Twitter](http://img.shields.io/badge/twitter-%40nf__core-1DA1F2?labelColor=000000&logo=twitter)](https://twitter.com/nf_core)[![Follow on Mastodon](https://img.shields.io/badge/mastodon-nf__core-6364ff?labelColor=FFFFFF&logo=mastodon)](https://mstdn.science/@nf_core)[![Watch on YouTube](http://img.shields.io/badge/youtube-nf--core-FF0000?labelColor=000000&logo=youtube)](https://www.youtube.com/c/nf-core) +## Important note +This pipeline is under active development and does not work at this point. If you want to process your Resolve Bioscience data in the meantime, please go to https://github.com/FloWuenne/nf-MolKart, where you can find a working nextflow pipeline, outside the nf-core ecosystem. In the coming weeks, nf-MolKart will be completely transitioned into nf-core/molkart for future use. + ## Introduction -**nf-core/molkart** is a bioinformatics pipeline that ... +**nf-core/molkart** is a pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH). It takes as input a table of FISH spot positions (x,y,z,gene), a corresponding DAPI image (tiff format) and optionally a membrane staining image in tiff format. nf-core/molkart performs end-to-end processing of the data including image processing, QC filtering of spots, cell segmentation, spot to cell assignment and reports quality metrics such as the spot assignment rate, average spots per cell and segmentation mask size ranges. - From f2be8fc9d3b681b679e83039814fbb0a02c6944c Mon Sep 17 00:00:00 2001 From: Florian Wuennemann Date: Thu, 10 Aug 2023 19:26:01 +0000 Subject: [PATCH 003/149] Installed first batch of nf-core modules. --- modules.json | 30 ++++++++ modules/nf-core/cellpose/main.nf | 56 +++++++++++++++ modules/nf-core/cellpose/meta.yml | 46 +++++++++++++ modules/nf-core/deepcell/mesmer/main.nf | 39 +++++++++++ modules/nf-core/deepcell/mesmer/meta.yml | 49 +++++++++++++ modules/nf-core/ilastik/multicut/main.nf | 58 ++++++++++++++++ modules/nf-core/ilastik/multicut/meta.yml | 64 +++++++++++++++++ .../ilastik/pixelclassification/main.nf | 58 ++++++++++++++++ .../ilastik/pixelclassification/meta.yml | 55 +++++++++++++++ modules/nf-core/mcquant/main.nf | 49 +++++++++++++ modules/nf-core/mcquant/meta.yml | 69 +++++++++++++++++++ modules/nf-core/mindagap/mindagap/main.nf | 49 +++++++++++++ modules/nf-core/mindagap/mindagap/meta.yml | 51 ++++++++++++++ workflows/molkart.nf | 5 ++ 14 files changed, 678 insertions(+) create mode 100644 modules/nf-core/cellpose/main.nf create mode 100644 modules/nf-core/cellpose/meta.yml create mode 100644 modules/nf-core/deepcell/mesmer/main.nf create mode 100644 modules/nf-core/deepcell/mesmer/meta.yml create mode 100644 modules/nf-core/ilastik/multicut/main.nf create mode 100644 modules/nf-core/ilastik/multicut/meta.yml create mode 100644 modules/nf-core/ilastik/pixelclassification/main.nf create mode 100644 modules/nf-core/ilastik/pixelclassification/meta.yml create mode 100644 modules/nf-core/mcquant/main.nf create mode 100644 modules/nf-core/mcquant/meta.yml create mode 100644 modules/nf-core/mindagap/mindagap/main.nf create mode 100644 modules/nf-core/mindagap/mindagap/meta.yml diff --git a/modules.json b/modules.json index 42d5674..ccab519 100644 --- a/modules.json +++ b/modules.json @@ -5,16 +5,46 @@ "https://github.com/nf-core/modules.git": { "modules": { "nf-core": { + "cellpose": { + "branch": "master", + "git_sha": "716ef3019b66772a817b417078edce2f7b337858", + "installed_by": ["modules"] + }, "custom/dumpsoftwareversions": { "branch": "master", "git_sha": "76cc4938c1f6ea5c7d83fed1eeffc146787f9543", "installed_by": ["modules"] }, + "deepcell/mesmer": { + "branch": "master", + "git_sha": "b9829e1064382745d8dff7f1d74d2138d2864f71", + "installed_by": ["modules"] + }, "fastqc": { "branch": "master", "git_sha": "c8e35eb2055c099720a75538d1b8adb3fb5a464c", "installed_by": ["modules"] }, + "ilastik/multicut": { + "branch": "master", + "git_sha": "6f150e1503c0826c21fedf1fa566cdbecbe98ec7", + "installed_by": ["modules"] + }, + "ilastik/pixelclassification": { + "branch": "master", + "git_sha": "6f150e1503c0826c21fedf1fa566cdbecbe98ec7", + "installed_by": ["modules"] + }, + "mcquant": { + "branch": "master", + "git_sha": "b9829e1064382745d8dff7f1d74d2138d2864f71", + "installed_by": ["modules"] + }, + "mindagap/mindagap": { + "branch": "master", + "git_sha": "240937a2a9c30298110753292be041188891f2cb", + "installed_by": ["modules"] + }, "multiqc": { "branch": "master", "git_sha": "f2d63bd5b68925f98f572eed70993d205cc694b7", diff --git a/modules/nf-core/cellpose/main.nf b/modules/nf-core/cellpose/main.nf new file mode 100644 index 0000000..a2b2206 --- /dev/null +++ b/modules/nf-core/cellpose/main.nf @@ -0,0 +1,56 @@ +process CELLPOSE { + tag "$meta.id" + label 'process_medium' + + container "docker.io/biocontainers/cellpose:2.1.1_cv2" + + input: + tuple val(meta), path(image) + path(model) + + output: + tuple val(meta), path("*masks.tif"), emit: mask + path "versions.yml" , emit: versions + + when: + task.ext.when == null || task.ext.when + + script: + // Exit if running this module with -profile conda / -profile mamba + if (workflow.profile.tokenize(',').intersect(['conda', 'mamba']).size() >= 1) { + error "I did not manage to create a cellpose module in Conda that works in all OSes. Please use Docker / Singularity / Podman instead." + } + def args = task.ext.args ?: '' + def prefix = task.ext.prefix ?: "${meta.id}" + def model_command = model ? "--pretrained_model $model" : "" + def VERSION = '2.1.1' + """ + cellpose \ + --image_path $image \ + --save_tif \ + --verbose \ + $model_command \ + $args + + cat <<-END_VERSIONS > versions.yml + "${task.process}": + cellpose: $VERSION + END_VERSIONS + """ + stub: + // Exit if running this module with -profile conda / -profile mamba + if (workflow.profile.tokenize(',').intersect(['conda', 'mamba']).size() >= 1) { + error "I did not manage to create a cellpose module in Conda that works in all OSes. Please use Docker / Singularity / Podman instead." + } + def prefix = task.ext.prefix ?: "${meta.id}" + def VERSION = "2.1.1" // WARN: Version information not provided by tool on CLI. Please update this string when bumping container versions. + """ + touch ${prefix}_cp_masks.tif + + cat <<-END_VERSIONS > versions.yml + "${task.process}": + cellpose: $VERSION + END_VERSIONS + """ + +} diff --git a/modules/nf-core/cellpose/meta.yml b/modules/nf-core/cellpose/meta.yml new file mode 100644 index 0000000..b452f57 --- /dev/null +++ b/modules/nf-core/cellpose/meta.yml @@ -0,0 +1,46 @@ +name: "cellpose" +description: cellpose segments cells in images +keywords: + - segmentation + - image + - cellpose +tools: + - "cellpose": + description: "cellpose is an anatomical segmentation algorithm written in Python 3 by Carsen Stringer and Marius Pachitariu" + homepage: "https://github.com/MouseLand/cellpose" + documentation: "https://cellpose.readthedocs.io/en/latest/command.html" + tool_dev_url: "https://github.com/MouseLand/cellpose" + doi: 10.1038/s41592-022-01663-4 + licence: "BSD 3-Clause" + +input: + - meta: + type: map + description: | + Groovy Map containing sample information + (sample id) + - image: + type: file + description: tif file for ready for segmentation + pattern: "*.{tif,tiff}" + - model: + type: file + description: Optional input file. Cellpose 2 model trained by user using human-in-the-loop approach. + +output: + - meta: + type: map + description: | + Groovy Map containing sample information + [sample id] + - versions: + type: file + description: File containing software versions + pattern: "versions.yml" + - mask: + type: file + description: labelled mask output from cellpose in tif format + pattern: "*.{tif, tiff}" + +authors: + - "@josenimo" diff --git a/modules/nf-core/deepcell/mesmer/main.nf b/modules/nf-core/deepcell/mesmer/main.nf new file mode 100644 index 0000000..56d96c5 --- /dev/null +++ b/modules/nf-core/deepcell/mesmer/main.nf @@ -0,0 +1,39 @@ +process DEEPCELL_MESMER { + tag "$meta.id" + label 'process_single' + + container "docker.io/vanvalenlab/deepcell-applications:0.4.1" + + input: + tuple val(meta) , path(img) + tuple val(meta2), path(membrane_img) + + // Output a .tif image, don't touch versions + output: + tuple val(meta), path("mask.tif"), emit: mask + path "versions.yml" , emit: versions + + when: + task.ext.when == null || task.ext.when + + script: + def args = task.ext.args ?: '' + def prefix = task.ext.prefix ?: "${meta.id}" + def membrane_command = membrane_img ? "--membrane-image $membrane_img" : "" + def VERSION = "0.4.0" + + """ + python /usr/src/app/run_app.py mesmer \ + --squeeze \ + --nuclear-image $img \ + --output-directory . \ + --output-name mask.tif \ + $membrane_command \ + $args + + cat <<-END_VERSIONS > versions.yml + "${task.process}": + deepcell_mesmer:: $VERSION + END_VERSIONS + """ +} diff --git a/modules/nf-core/deepcell/mesmer/meta.yml b/modules/nf-core/deepcell/mesmer/meta.yml new file mode 100644 index 0000000..49fd391 --- /dev/null +++ b/modules/nf-core/deepcell/mesmer/meta.yml @@ -0,0 +1,49 @@ +name: "deepcell_mesmer" +description: Deepcell/mesmer segmentation for whole-cell +keywords: + - imaging + - spatial_omics + - segmentation +tools: + - "mesmer": + description: "Deep cell is a collection of tools to segment imaging data" + homepage: "https://github.com/vanvalenlab/deepcell-tf" + documentation: "https://github.com/vanvalenlab/intro-to-deepcell/tree/master/pretrained_models" + tool_dev_url: "https://githu/b.com/vanvalenlab/deepcell-tf" + doi: 10.1038/s41587-021-01094-0 + licence: "APACHE2" + +input: + # Only when we have meta + - meta: + type: map + description: | + Groovy Map containing sample information + e.g. [ id:'test', single_end:false ] + # We always need to have an image of the tissue. (That's the whole point fo cell segmentation) + - img: + type: file + description: Multichannel image file + pattern: "*.{tiff,tif,h5,hdf5}" + +output: + #Only when we have meta + - meta: + type: map + description: | + Groovy Map containing sample information + e.g. [ id:'test', single_end:false ] + # + - versions: + type: file + description: File containing software versions + pattern: "versions.yml" + + - mask: + type: file + description: File containing the mask. + pattern: "*.{tif, tiff}" + +authors: + - "@migueLib" + - "@chiarasch" diff --git a/modules/nf-core/ilastik/multicut/main.nf b/modules/nf-core/ilastik/multicut/main.nf new file mode 100644 index 0000000..f792487 --- /dev/null +++ b/modules/nf-core/ilastik/multicut/main.nf @@ -0,0 +1,58 @@ +process ILASTIK_MULTICUT { + tag "$meta.id" + label 'process_low' + + container "docker.io/biocontainers/ilastik:1.4.0_cv1" + + input: + tuple val(meta), path(h5) + tuple val(meta2), path (ilp) + tuple val(meta3), path (probs) + + output: + tuple val(meta), path("*.tiff") , emit: out_tiff + path "versions.yml" , emit: versions + + when: + task.ext.when == null || task.ext.when + + script: + // Exit if running this module with -profile conda / -profile mamba + if (workflow.profile.tokenize(',').intersect(['conda', 'mamba']).size() >= 1) { + error "ILASTIK_MULTICUT module does not support Conda. Please use Docker / Singularity / Podman instead." + } + def args = task.ext.args ?: '' + def prefix = task.ext.prefix ?: "${meta.id}" + + """ + /opt/ilastik-1.4.0-Linux/run_ilastik.sh \\ + --headless \\ + --readonly 1 \\ + --project=$ilp \\ + --raw_data=$h5 \\ + --probabilities=$probs \\ + --export_source="Multicut Segmentation" \\ + --output_filename_format=${prefix}.tiff \\ + $args + + cat <<-END_VERSIONS > versions.yml + "${task.process}": + ilastik: \$(/opt/ilastik-1.4.0-Linux/run_ilastik.sh --headless --version) + END_VERSIONS + """ + + stub: + // Exit if running this module with -profile conda / -profile mamba + if (workflow.profile.tokenize(',').intersect(['conda', 'mamba']).size() >= 1) { + error "ILASTIK_MULTICUT module does not support Conda. Please use Docker / Singularity / Podman instead." + } + def prefix = task.ext.prefix ?: "${meta.id}" + def VERSION = "1.4.0" // WARN: Version information not provided by tool on CLI. Please update this string when bumping container versions. + """ + touch ${prefix}.tiff + cat <<-END_VERSIONS > versions.yml + "${task.process}": + ilastik:: $VERSION + END_VERSIONS + """ +} diff --git a/modules/nf-core/ilastik/multicut/meta.yml b/modules/nf-core/ilastik/multicut/meta.yml new file mode 100644 index 0000000..39493df --- /dev/null +++ b/modules/nf-core/ilastik/multicut/meta.yml @@ -0,0 +1,64 @@ +name: "ilastik_multicut" + +description: Ilastik is a tool that utilizes machine learning algorithms to classify pixels, segment, track and count cells in images. Ilastik contains a graphical user interface to interactively label pixels. However, this nextflow module will implement the --headless mode, to apply pixel classification using a pre-trained .ilp file on an input image. +keywords: + - multicut + - segmentation + - pixel classification +tools: + - "ilastik": + description: "Ilastik is a user friendly tool that enables pixel classification, segmentation and analysis." + homepage: "https://www.ilastik.org/" + documentation: "https://www.ilastik.org/documentation/" + tool_dev_url: "https://github.com/ilastik/ilastik" + licence: "GPL3" + +input: + - meta: + type: map + description: | + Groovy Map containing sample information + e.g. [ id:'test', single_end:false ] + - h5: + type: file + description: h5 file containing image stack to classify file + pattern: "*.{h5,hdf5}" + + - meta2: + type: map + description: | + Groovy Map containing sample information + e.g. [ id:'test', single_end:false ] + - ilp: + type: file + description: Trained ilastik .ilp project file + pattern: "*.{ilp}" + + - meta3: + type: map + description: | + Groovy Map containing sample information + e.g. [ id:'test', single_end:false ] + - probs: + type: file + description: Probability map for boundary based segmentation + pattern: "*.{h5,,hdf5}" + +output: + - meta: + type: map + description: | + Groovy Map containing sample information + e.g. [ id:'test', single_end:false ] + - versions: + type: file + description: File containing software versions + pattern: "versions.yml" + + - out_tiff: + type: file + description: Multicut segmentation mask output. + pattern: "*.{tiff}" + +authors: + - "@FloWuenne" diff --git a/modules/nf-core/ilastik/pixelclassification/main.nf b/modules/nf-core/ilastik/pixelclassification/main.nf new file mode 100644 index 0000000..2748283 --- /dev/null +++ b/modules/nf-core/ilastik/pixelclassification/main.nf @@ -0,0 +1,58 @@ +process ILASTIK_PIXELCLASSIFICATION { + tag "$meta.id" + label 'process_single' + + container "docker.io/biocontainers/ilastik:1.4.0_cv1" + + input: + tuple val(meta), path(input_img) + tuple val(meta2), path(ilp) + + output: + tuple val(meta), path("*.${suffix}") , emit: output + path "versions.yml" , emit: versions + + when: + task.ext.when == null || task.ext.when + + script: + // Exit if running this module with -profile conda / -profile mamba + if (workflow.profile.tokenize(',').intersect(['conda', 'mamba']).size() >= 1) { + error "ILASTIK_PIXELCLASSIFICATION module does not support Conda. Please use Docker / Singularity / Podman instead." + } + def args = task.ext.args ?: '' + def prefix = task.ext.prefix ?: "${meta.id}" + suffix = task.ext.suffix ?: "h5" + + """ + /opt/ilastik-1.4.0-Linux/run_ilastik.sh \\ + --headless \\ + --readonly 1 \\ + --project=$ilp \\ + --output_filename_format=${prefix}.${suffix} \\ + $args \\ + $input_img + + cat <<-END_VERSIONS > versions.yml + "${task.process}": + ilastik: \$(/opt/ilastik-1.4.0-Linux/run_ilastik.sh --headless --version) + END_VERSIONS + """ + + stub: + // Exit if running this module with -profile conda / -profile mamba + if (workflow.profile.tokenize(',').intersect(['conda', 'mamba']).size() >= 1) { + error "ILASTIK_PIXELCLASSIFICATION module does not support Conda. Please use Docker / Singularity / Podman instead." + } + def prefix = task.ext.prefix ?: "${meta.id}" + suffix = task.ext.suffix ?: "h5" + + """ + touch ${prefix}.${suffix} + + cat <<-END_VERSIONS > versions.yml + "${task.process}": + ilastik:: \$(/opt/ilastik-1.4.0-Linux/run_ilastik.sh --headless --version) + END_VERSIONS + """ +} diff --git a/modules/nf-core/ilastik/pixelclassification/meta.yml b/modules/nf-core/ilastik/pixelclassification/meta.yml new file mode 100644 index 0000000..017ea84 --- /dev/null +++ b/modules/nf-core/ilastik/pixelclassification/meta.yml @@ -0,0 +1,55 @@ +name: "ilastik_pixelclassification" + +description: Ilastik is a tool that utilizes machine learning algorithms to classify pixels, segment, track and count cells in images. Ilastik contains a graphical user interface to interactively label pixels. However, this nextflow module will implement the --headless mode, to apply pixel classification using a pre-trained .ilp file on an input image. +keywords: + - pixel_classification + - segmentation + - probability_maps +tools: + - "ilastik": + description: "Ilastik is a user friendly tool that enables pixel classification, segmentation and analysis." + homepage: "https://www.ilastik.org/" + documentation: "https://www.ilastik.org/documentation/" + tool_dev_url: "https://github.com/ilastik/ilastik" + licence: "GPL3" + +input: + - meta: + type: map + description: | + Groovy Map containing sample information for h5 file + e.g. [ id:'test', single_end:false ] + + - input_img: + type: file + description: Input img file containing image stack to classify + + - meta2: + type: map + description: | + Groovy Map containing sample information for ilp file + e.g. [ id:'test', single_end:false ] + + - ilp: + type: file + description: Trained ilastik pixel classification .ilp project file + pattern: "*.{ilp}" + +output: + - meta: + type: map + description: | + Groovy Map containing sample information + e.g. [ id:'test', single_end:false ] + + - versions: + type: file + description: File containing software versions + pattern: "versions.yml" + + - output: + type: file + description: Output file from ilastik pixel classification. + +authors: + - "@FloWuenne" diff --git a/modules/nf-core/mcquant/main.nf b/modules/nf-core/mcquant/main.nf new file mode 100644 index 0000000..bc0eedf --- /dev/null +++ b/modules/nf-core/mcquant/main.nf @@ -0,0 +1,49 @@ +process MCQUANT { + tag "$meta.id" + label 'process_single' + + // WARN: Version information not provided by tool on CLI. Please update version string below when bumping container versions. + container "docker.io/labsyspharm/quantification:1.5.4" + + input: + tuple val(meta), path(image) + tuple val(meta2), path(mask) + tuple val(meta3), path(markerfile) + + output: + tuple val(meta), path("*.csv"), emit: csv + path "versions.yml" , emit: versions + + when: + task.ext.when == null || task.ext.when + + script: + def args = task.ext.args ?: '' + def prefix = task.ext.prefix ?: "${meta.id}" + def VERSION = '1.5.4' // WARN: Version information not provided by tool on CLI. Please update this string when bumping container versions. + """ + python /app/CommandSingleCellExtraction.py \ + --masks $mask \ + --image $image \ + --channel_names $markerfile \ + --output . \ + $args + + cat <<-END_VERSIONS > versions.yml + "${task.process}": + mcquant: $VERSION + END_VERSIONS + """ + + stub: + def prefix = task.ext.prefix ?: "${meta.id}" + def VERSION = '1.5.4' + """ + touch ${prefix}.csv + + cat <<-END_VERSIONS > versions.yml + "${task.process}": + mcquant: $VERSION + END_VERSIONS + """ +} diff --git a/modules/nf-core/mcquant/meta.yml b/modules/nf-core/mcquant/meta.yml new file mode 100644 index 0000000..5400314 --- /dev/null +++ b/modules/nf-core/mcquant/meta.yml @@ -0,0 +1,69 @@ +name: "mcquant" +description: write your description here +keywords: + - quantification + - image_analysis + - mcmicro + - highly_multiplexed_imaging +tools: + - "mcquant": + description: "Module for single-cell data extraction given a segmentation mask and multi-channel image. The CSV structure is aligned with histoCAT output." + homepage: "https://github.com/labsyspharm/quantification" + documentation: "https://github.com/labsyspharm/quantification/blob/master/README.md" + tool_dev_url: "https://github.com/labsyspharm/quantification" + doi: 10.1038/s41592-021-01308-y + licence: "" + +input: + - meta: + type: map + description: | + Groovy Map containing sample information + e.g. [ id:'test', single_end:false ] + + - image: + type: file + description: Multi-channel image file + pattern: "*.{tiff,tif,h5,hdf5}" + + - meta2: + type: map + description: | + Groovy Map containing sample information + e.g. [ id:'test', single_end:false ] + + - mask: + type: file + description: Labeled segmentation mask for image + pattern: "*.{tiff,tif,h5,hdf5}" + + - meta3: + type: map + description: | + Groovy Map containing sample information + e.g. [ id:'test', single_end:false ] + + - markerfile: + type: file + description: Marker file with channel names for image to quantify + pattern: "*.{csv}" + +output: + - meta: + type: map + description: | + Groovy Map containing sample information + e.g. [ id:'test', single_end:false ] + + - versions: + type: file + description: File containing software versions + pattern: "versions.yml" + + - csv: + type: file + description: Quantified regionprops_table + pattern: "*.{csv}" + +authors: + - "@FloWuenne" diff --git a/modules/nf-core/mindagap/mindagap/main.nf b/modules/nf-core/mindagap/mindagap/main.nf new file mode 100644 index 0000000..8d339ba --- /dev/null +++ b/modules/nf-core/mindagap/mindagap/main.nf @@ -0,0 +1,49 @@ +process MINDAGAP_MINDAGAP { + tag "$meta.id" + label 'process_low' + + conda "bioconda::mindagap=0.0.2" + container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? + 'https://depot.galaxyproject.org/singularity/mindagap:0.0.2--pyhdfd78af_0' : + 'biocontainers/mindagap:0.0.2--pyhdfd78af_0' }" + + input: + tuple val(meta), path(tiff) + val(boxsize) + val(loopnum) + + output: + tuple val(meta), path("*gridfilled.tiff"), emit: tiff + path "versions.yml" , emit: versions + + when: + task.ext.when == null || task.ext.when + + script: + def args = task.ext.args ?: '' + def args2 = task.ext.args2 ?: '' + def prefix = task.ext.prefix ?: "${meta.id}" + """ + mindagap.py \\ + $args \\ + $tiff \\ + $boxsize \\ + $loopnum + + cat <<-END_VERSIONS > versions.yml + "${task.process}": + mindagap: \$(mindagap.py test -v) + END_VERSIONS + """ + + stub: + def prefix = task.ext.prefix ?: "${meta.id}" + """ + touch ${prefix}.gridfilled.tiff + + cat <<-END_VERSIONS > versions.yml + "${task.process}": + mindagap: \$(mindagap.py test -v) + END_VERSIONS + """ +} diff --git a/modules/nf-core/mindagap/mindagap/meta.yml b/modules/nf-core/mindagap/mindagap/meta.yml new file mode 100644 index 0000000..022886a --- /dev/null +++ b/modules/nf-core/mindagap/mindagap/meta.yml @@ -0,0 +1,51 @@ +name: "mindagap_mindagap" +description: Takes a single panorama image and fills the empty grid lines with neighbour-weighted values. +keywords: + - imaging + - resolve_bioscience + - spatial_transcriptomics +tools: + - "mindagap": + description: "Mindagap is a collection of tools to process multiplexed FISH data, such as produced by Resolve Biosciences Molecular Cartography." + homepage: "https://github.com/ViriatoII/MindaGap" + documentation: "https://github.com/ViriatoII/MindaGap/blob/main/README.md" + tool_dev_url: "https://github.com/ViriatoII/MindaGap" + licence: "BSD-3-Clause license" + +input: + - meta: + type: map + description: | + Groovy Map containing sample information + e.g. [ id:'test', single_end:false ] + - tiff: + type: file + description: A tiff file containing gridlines as produced by Molecular Cartography imaging. + pattern: "*.{tiff}" + - boxsize: + type: integer + description: A larger number allows to overcome large gaps, but makes looses fine details in new filled grid. + - loopnum: + type: integer + description: The number of times gaussian blur is run consecutively on the gridlines. A smaller number is faster, but the result is less good. + +output: + - meta: + type: map + description: | + Groovy Map containing sample information + e.g. [ id:'test', single_end:false ] + + - versions: + type: file + description: File containing software versions + pattern: "versions.yml" + + - tiff: + type: file + description: A tiff file with gridlines filled based on consecutive gaussian blurring. + pattern: "*.{tiff}" + +authors: + - "@ViriatoII" + - "@flowuenne" diff --git a/workflows/molkart.nf b/workflows/molkart.nf index 2e9aada..55858e5 100644 --- a/workflows/molkart.nf +++ b/workflows/molkart.nf @@ -49,6 +49,11 @@ include { INPUT_CHECK } from '../subworkflows/local/input_check' include { FASTQC } from '../modules/nf-core/fastqc/main' include { MULTIQC } from '../modules/nf-core/multiqc/main' include { CUSTOM_DUMPSOFTWAREVERSIONS } from '../modules/nf-core/custom/dumpsoftwareversions/main' +include { MINDAGAP_MINDAGAP } from '../modules/nf-core/mindagap/mindagap/main' +include { CELLPOSE } from '../modules/nf-core/cellpose/main' +include { DEEPCELL_MESMER } from '../modules/nf-core/deepcell/mesmer/main' +include { ILASTIK_PIXELCLASSIFICATION } from '../modules/nf-core/ilastik/pixelclassification/main' +include { MCQUANT } from '../modules/nf-core/mcquant/main' /* ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ From 2f1e80040d77294b0887660c075a7cba182549b4 Mon Sep 17 00:00:00 2001 From: Florian Wuennemann Date: Thu, 10 Aug 2023 20:13:41 +0000 Subject: [PATCH 004/149] Automatic nextflow.config update. --- nextflow.config | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/nextflow.config b/nextflow.config index 533249d..1d163e5 100644 --- a/nextflow.config +++ b/nextflow.config @@ -16,7 +16,7 @@ params { genome = null igenomes_base = 's3://ngi-igenomes/igenomes' igenomes_ignore = false - + // MultiQC options multiqc_config = null @@ -43,7 +43,7 @@ params { custom_config_base = "https://raw.githubusercontent.com/nf-core/configs/${params.custom_config_version}" config_profile_contact = null config_profile_url = null - + // Max resource options // Defaults only, expecting to be overwritten From 111658fc0c1fdfb5bfe8fd5bc89649fc8f346f71 Mon Sep 17 00:00:00 2001 From: Florian Wuennemann Date: Tue, 19 Sep 2023 13:03:58 +0000 Subject: [PATCH 005/149] Started removing genome specific parameters from template. --- conf/test.config | 3 --- main.nf | 7 ------- nextflow.config | 11 ---------- nextflow_schema.json | 49 -------------------------------------------- workflows/molkart.nf | 33 +++++++++++++++++++++++++++-- 5 files changed, 31 insertions(+), 72 deletions(-) diff --git a/conf/test.config b/conf/test.config index d94efa5..f593198 100644 --- a/conf/test.config +++ b/conf/test.config @@ -23,7 +23,4 @@ params { // TODO nf-core: Specify the paths to your test data on nf-core/test-datasets // TODO nf-core: Give any required params for the test so that command line flags are not needed input = 'https://raw.githubusercontent.com/nf-core/test-datasets/viralrecon/samplesheet/samplesheet_test_illumina_amplicon.csv' - - // Genome references - genome = 'R64-1-1' } diff --git a/main.nf b/main.nf index b967761..ad5548c 100644 --- a/main.nf +++ b/main.nf @@ -11,13 +11,6 @@ nextflow.enable.dsl = 2 -/* -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - GENOME PARAMETER VALUES -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -*/ - -params.fasta = WorkflowMain.getGenomeAttribute(params, 'fasta') /* ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ diff --git a/nextflow.config b/nextflow.config index 1d163e5..629d320 100644 --- a/nextflow.config +++ b/nextflow.config @@ -12,11 +12,6 @@ params { // TODO nf-core: Specify your pipeline's command line flags // Input options input = null - // References - genome = null - igenomes_base = 's3://ngi-igenomes/igenomes' - igenomes_ignore = false - // MultiQC options multiqc_config = null @@ -183,12 +178,6 @@ plugins { id 'nf-validation' // Validation of pipeline parameters and creation of an input channel from a sample sheet } -// Load igenomes.config if required -if (!params.igenomes_ignore) { - includeConfig 'conf/igenomes.config' -} else { - params.genomes = [:] -} // Export these variables to prevent local Python/R libraries from conflicting with those in the container // The JULIA depot path has been adjusted to a fixed path `/usr/local/share/julia` that needs to be used for packages in the container. // See https://apeltzer.github.io/post/03-julia-lang-nextflow/ for details on that. Once we have a common agreement on where to keep Julia packages, this is adjustable. diff --git a/nextflow_schema.json b/nextflow_schema.json index ba0e791..a387957 100644 --- a/nextflow_schema.json +++ b/nextflow_schema.json @@ -42,45 +42,6 @@ } } }, - "reference_genome_options": { - "title": "Reference genome options", - "type": "object", - "fa_icon": "fas fa-dna", - "description": "Reference genome related files and options required for the workflow.", - "properties": { - "genome": { - "type": "string", - "description": "Name of iGenomes reference.", - "fa_icon": "fas fa-book", - "help_text": "If using a reference genome configured in the pipeline using iGenomes, use this parameter to give the ID for the reference. This is then used to build the full paths for all required reference genome files e.g. `--genome GRCh38`. \n\nSee the [nf-core website docs](https://nf-co.re/usage/reference_genomes) for more details." - }, - "fasta": { - "type": "string", - "format": "file-path", - "exists": true, - "mimetype": "text/plain", - "pattern": "^\\S+\\.fn?a(sta)?(\\.gz)?$", - "description": "Path to FASTA genome file.", - "help_text": "This parameter is *mandatory* if `--genome` is not specified. If you don't have a BWA index available this will be generated for you automatically. Combine with `--save_reference` to save BWA index for future runs.", - "fa_icon": "far fa-file-code" - }, - "igenomes_base": { - "type": "string", - "format": "directory-path", - "description": "Directory / URL base for iGenomes references.", - "default": "s3://ngi-igenomes/igenomes", - "fa_icon": "fas fa-cloud-download-alt", - "hidden": true - }, - "igenomes_ignore": { - "type": "boolean", - "description": "Do not load the iGenomes reference config.", - "fa_icon": "fas fa-ban", - "hidden": true, - "help_text": "Do not load `igenomes.config` when running the pipeline. You may choose this option if you observe clashes between custom parameters and those supplied in `igenomes.config`." - } - } - }, "institutional_config_options": { "title": "Institutional config options", "type": "object", @@ -175,14 +136,12 @@ "type": "boolean", "description": "Display help text.", "fa_icon": "fas fa-question-circle", - "default": false, "hidden": true }, "version": { "type": "boolean", "description": "Display version and exit.", "fa_icon": "fas fa-question-circle", - "default": false, "hidden": true }, "publish_dir_mode": { @@ -206,7 +165,6 @@ "type": "boolean", "description": "Send plain-text email instead of HTML.", "fa_icon": "fas fa-remove-format", - "default": false, "hidden": true }, "max_multiqc_email_size": { @@ -221,7 +179,6 @@ "type": "boolean", "description": "Do not use coloured log outputs.", "fa_icon": "fas fa-palette", - "default": false, "hidden": true }, "hook_url": { @@ -260,7 +217,6 @@ "type": "boolean", "fa_icon": "far fa-eye-slash", "description": "Show all params when using `--help`", - "default": false, "hidden": true, "help_text": "By default, parameters set as _hidden_ in the schema are not shown on the command line when a user runs with `--help`. Specifying this option will tell the pipeline to show all parameters." }, @@ -268,7 +224,6 @@ "type": "boolean", "fa_icon": "far fa-check-circle", "description": "Validation of parameters fails when an unrecognised parameter is found.", - "default": false, "hidden": true, "help_text": "By default, when an unrecognised parameter is found, it returns a warinig." }, @@ -276,7 +231,6 @@ "type": "boolean", "fa_icon": "far fa-check-circle", "description": "Validation of parameters in lenient more.", - "default": false, "hidden": true, "help_text": "Allows string values that are parseable as numbers or booleans. For further information see [JSONSchema docs](https://github.com/everit-org/json-schema#lenient-mode)." } @@ -287,9 +241,6 @@ { "$ref": "#/definitions/input_output_options" }, - { - "$ref": "#/definitions/reference_genome_options" - }, { "$ref": "#/definitions/institutional_config_options" }, diff --git a/workflows/molkart.nf b/workflows/molkart.nf index 55858e5..1301296 100644 --- a/workflows/molkart.nf +++ b/workflows/molkart.nf @@ -46,7 +46,6 @@ include { INPUT_CHECK } from '../subworkflows/local/input_check' // // MODULE: Installed directly from nf-core/modules // -include { FASTQC } from '../modules/nf-core/fastqc/main' include { MULTIQC } from '../modules/nf-core/multiqc/main' include { CUSTOM_DUMPSOFTWAREVERSIONS } from '../modules/nf-core/custom/dumpsoftwareversions/main' include { MINDAGAP_MINDAGAP } from '../modules/nf-core/mindagap/mindagap/main' @@ -79,8 +78,9 @@ workflow MOLKART { // See the documentation https://nextflow-io.github.io/nf-validation/samplesheets/fromSamplesheet/ // ! There is currently no tooling to help you write a sample sheet schema + // - // MODULE: Run FastQC + // MODULE: Run Mindagap_mindagap // FASTQC ( INPUT_CHECK.out.reads @@ -91,6 +91,35 @@ workflow MOLKART { ch_versions.unique().collectFile(name: 'collated_versions.yml') ) + // Stack images + + // + // MODULE: Apply Contract-limited adaptive histogram equalization (CLAHE) + // + + // + // MODULE: Cellpose segmentation + // + + // + // MODULE: Run Module Mindagap duplicatefinder + // + // Filter out potential duplicate spots from the spots table + + // + // MODULE: PROJECT SPOTS + // + // Transform spot table to 2 dimensional numpy array to use with MCQUANT + + + // + // MODULE: MCQuant + // + + // + // MODULE: Run Module MOLCART_QC + // + // // MODULE: MultiQC // From a2b153c9dfd804d8b9085a5b33e3e5d6f8ddbfa7 Mon Sep 17 00:00:00 2001 From: Florian Wuennemann Date: Tue, 19 Sep 2023 19:45:17 +0000 Subject: [PATCH 006/149] Prettier modification. --- assets/schema_input.json | 12 ++++++------ lib/WorkflowMain.groovy | 2 ++ lib/WorkflowMolkart.groovy | 4 +++- main.nf | 5 +++-- nextflow.config | 2 +- nextflow_schema.json | 3 ++- workflows/molkart.nf | 30 +++++++++++++++--------------- 7 files changed, 32 insertions(+), 26 deletions(-) diff --git a/assets/schema_input.json b/assets/schema_input.json index 9252388..671ac7e 100644 --- a/assets/schema_input.json +++ b/assets/schema_input.json @@ -9,20 +9,20 @@ "properties": { "sample": { "type": "string", - "pattern": "^\\S+$", + "pattern": ".*$", "errorMessage": "Sample name must be provided and cannot contain spaces" }, - "fastq_1": { + "nuclear_image": { "type": "string", - "pattern": "^\\S+\\.f(ast)?q\\.gz$", + "pattern": ".*.tiff$", "errorMessage": "FastQ file for reads 1 must be provided, cannot contain spaces and must have extension '.fq.gz' or '.fastq.gz'" }, - "fastq_2": { + "spot_table": { "errorMessage": "FastQ file for reads 2 cannot contain spaces and must have extension '.fq.gz' or '.fastq.gz'", "anyOf": [ { "type": "string", - "pattern": "^\\S+\\.f(ast)?q\\.gz$" + "pattern": ".*.txt$" }, { "type": "string", @@ -31,6 +31,6 @@ ] } }, - "required": ["sample", "fastq_1"] + "required": ["sample", "nuclear_image", "spot_table"] } } diff --git a/lib/WorkflowMain.groovy b/lib/WorkflowMain.groovy index aebe9cc..8a01ac7 100755 --- a/lib/WorkflowMain.groovy +++ b/lib/WorkflowMain.groovy @@ -52,6 +52,7 @@ class WorkflowMain { // // Get attribute from genome config file e.g. fasta // + /* public static Object getGenomeAttribute(params, attribute) { if (params.genomes && params.genome && params.genomes.containsKey(params.genome)) { if (params.genomes[ params.genome ].containsKey(attribute)) { @@ -60,4 +61,5 @@ class WorkflowMain { } return null } + */ // TODO : } diff --git a/lib/WorkflowMolkart.groovy b/lib/WorkflowMolkart.groovy index f64d19e..2a78854 100755 --- a/lib/WorkflowMolkart.groovy +++ b/lib/WorkflowMolkart.groovy @@ -7,17 +7,19 @@ import groovy.text.SimpleTemplateEngine class WorkflowMolkart { + // // Check and validate parameters // public static void initialise(params, log) { - +/* //TODO : remove genomeExistsError(params, log) if (!params.fasta) { Nextflow.error "Genome fasta file not specified with e.g. '--fasta genome.fa' or via a detectable config file." } +*/ } // diff --git a/main.nf b/main.nf index ad5548c..d1dbaef 100644 --- a/main.nf +++ b/main.nf @@ -18,13 +18,14 @@ nextflow.enable.dsl = 2 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ */ -include { validateParameters; paramsHelp } from 'plugin/nf-validation' +include { validateParameters; paramsHelp; paramsSummaryLog; fromSamplesheet } from 'plugin/nf-validation' + // Print help message if needed if (params.help) { def logo = NfcoreTemplate.logo(workflow, params.monochrome_logs) def citation = '\n' + WorkflowMain.citation(workflow) + '\n' - def String command = "nextflow run ${workflow.manifest.name} --input samplesheet.csv --genome GRCh37 -profile docker" + def String command = "nextflow run ${workflow.manifest.name} --input samplesheet.csv -profile docker" log.info logo + paramsHelp(command) + citation + NfcoreTemplate.dashedLine(params.monochrome_logs) System.exit(0) } diff --git a/nextflow.config b/nextflow.config index 629d320..52e2b0a 100644 --- a/nextflow.config +++ b/nextflow.config @@ -175,7 +175,7 @@ singularity.registry = 'quay.io' // Nextflow plugins plugins { - id 'nf-validation' // Validation of pipeline parameters and creation of an input channel from a sample sheet + id 'nf-validation' } // Export these variables to prevent local Python/R libraries from conflicting with those in the container diff --git a/nextflow_schema.json b/nextflow_schema.json index a387957..f450d0d 100644 --- a/nextflow_schema.json +++ b/nextflow_schema.json @@ -20,7 +20,8 @@ "pattern": "^\\S+\\.csv$", "description": "Path to comma-separated file containing information about the samples in the experiment.", "help_text": "You will need to create a design file with information about the samples in your experiment before running the pipeline. Use this parameter to specify its location. It has to be a comma-separated file with 3 columns, and a header row. See [usage docs](https://nf-co.re/molkart/usage#samplesheet-input).", - "fa_icon": "fas fa-file-csv" + "fa_icon": "fas fa-file-csv", + "schema": "/assets/schema_input.json" }, "outdir": { "type": "string", diff --git a/workflows/molkart.nf b/workflows/molkart.nf index 1301296..bc7bbfb 100644 --- a/workflows/molkart.nf +++ b/workflows/molkart.nf @@ -4,7 +4,7 @@ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ */ -include { paramsSummaryLog; paramsSummaryMap } from 'plugin/nf-validation' +include { paramsSummaryLog; paramsSummaryMap; fromSamplesheet } from 'plugin/nf-validation' def logo = NfcoreTemplate.logo(workflow, params.monochrome_logs) def citation = '\n' + WorkflowMain.citation(workflow) + '\n' @@ -35,7 +35,7 @@ ch_multiqc_custom_methods_description = params.multiqc_methods_description ? fil // // SUBWORKFLOW: Consisting of a mix of local and nf-core/modules // -include { INPUT_CHECK } from '../subworkflows/local/input_check' +// include { INPUT_CHECK } from '../subworkflows/local/input_check' TODO: remove in the future /* ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ @@ -43,7 +43,7 @@ include { INPUT_CHECK } from '../subworkflows/local/input_check' ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ */ -// +//wge // MODULE: Installed directly from nf-core/modules // include { MULTIQC } from '../modules/nf-core/multiqc/main' @@ -70,22 +70,17 @@ workflow MOLKART { // // SUBWORKFLOW: Read in samplesheet, validate and stage input files // - INPUT_CHECK ( - file(params.input) - ) - ch_versions = ch_versions.mix(INPUT_CHECK.out.versions) - // TODO: OPTIONAL, you can use nf-validation plugin to create an input channel from the samplesheet with Channel.fromSamplesheet("input") - // See the documentation https://nextflow-io.github.io/nf-validation/samplesheets/fromSamplesheet/ - // ! There is currently no tooling to help you write a sample sheet schema + ch_from_samplesheet = Channel.fromSamplesheet("input") + ch_from_samplesheet.view() + ch_from_samplesheet + .map { sample_id, nuclear_image, spot_table -> tuple([id: sample_id], nuclear_image) } + .set { image_tuple } // // MODULE: Run Mindagap_mindagap // - FASTQC ( - INPUT_CHECK.out.reads - ) - ch_versions = ch_versions.mix(FASTQC.out.versions.first()) + MINDAGAP_MINDAGAP(image_tuple, 7, 100) CUSTOM_DUMPSOFTWAREVERSIONS ( ch_versions.unique().collectFile(name: 'collated_versions.yml') @@ -97,10 +92,15 @@ workflow MOLKART { // MODULE: Apply Contract-limited adaptive histogram equalization (CLAHE) // + // APPLY_CLAHE_DASK(MKIMG_STACKS.out.mcimage) TODO : Add local module for testing + // // MODULE: Cellpose segmentation // + // Cellpose segmentation and quantification + CELLPOSE(MINDAGAP_MINDAGAP.out.tiff, "") + // // MODULE: Run Module Mindagap duplicatefinder // @@ -133,7 +133,7 @@ workflow MOLKART { ch_multiqc_files = ch_multiqc_files.mix(ch_workflow_summary.collectFile(name: 'workflow_summary_mqc.yaml')) ch_multiqc_files = ch_multiqc_files.mix(ch_methods_description.collectFile(name: 'methods_description_mqc.yaml')) ch_multiqc_files = ch_multiqc_files.mix(CUSTOM_DUMPSOFTWAREVERSIONS.out.mqc_yml.collect()) - ch_multiqc_files = ch_multiqc_files.mix(FASTQC.out.zip.collect{it[1]}.ifEmpty([])) + /// ch_multiqc_files = ch_multiqc_files.mix(FASTQC.out.zip.collect{it[1]}.ifEmpty([])) TODO: remove MULTIQC ( ch_multiqc_files.collect(), From de520768a5ae60bb864f9d620086084d6912a2ba Mon Sep 17 00:00:00 2001 From: Florian Wuennemann Date: Tue, 19 Sep 2023 21:57:59 +0000 Subject: [PATCH 007/149] Added mindagap and project spots to pipeline. --- bin/project_spots.dask.py | 75 +++++++++++++++++++++++++++++++++++++++ 1 file changed, 75 insertions(+) create mode 100755 bin/project_spots.dask.py diff --git a/bin/project_spots.dask.py b/bin/project_spots.dask.py new file mode 100755 index 0000000..4eac828 --- /dev/null +++ b/bin/project_spots.dask.py @@ -0,0 +1,75 @@ +#!/usr/bin/env python + +#### This script takes a table of Molecular Cartography spots as input and projects them +#### onto a reference image. The output is a stack of images, one for each spot, with +#### the spot projected onto the reference image shape. + +## Import packages +import argparse +import pandas as pd +import numpy as np +import dask.array as da +import dask.dataframe as dd +import tifffile +from rich.progress import track +from aicsimageio.writers import OmeTiffWriter + +# Make a function to project a table of spots with x,y coordinates onto a 2d plane based on reference image shape and add any duplicate spots to increase their pixel value in the output image +def project_spots(spot_table,img): + # Initialize an empty image with the same shape as the reference image + img = np.zeros_like(img, dtype= 'int8') + # Iterate through each spot in the table + for spot in spot_table.itertuples(): + # Add the corresponding spot count to the pixel value at the spot's x,y coordinates + img[spot.y, spot.x] += spot.counts + return img + +if __name__ == "__main__": + # Add a python argument parser with options for input, output and image size in x and y + parser = argparse.ArgumentParser() + parser.add_argument( + "-i", + "--input", + help="Spot table to project." + ) + parser.add_argument( + "-s", + "--sample_id", + help="Sample ID." + ) + parser.add_argument( + "-d", + "--img_dims", + dest="img_dims", + help="Corresponding image to get dimensions from." + ) + + args = parser.parse_args() + + #spots = pd.read_csv(args.input) + spots = dd.read_table(args.input, sep='\t', names=['x', 'y', 'z', 'gene']).compute() + img = tifffile.imread(args.img_dims) + + spots = spots[["y","x", "gene"]] + + ## Filter any genes marked with Duplicated + spots = spots[~spots.gene.str.contains("Duplicated")] + + # Sum spots by z-axis + spots_zsum = spots.value_counts().to_frame('counts').reset_index() + + # Project each gene into a 2d plane and add to list + # Add a printed message that says "Projecting spots for gene X" for each gene in the list + spots_2d_list = [project_spots(spots_zsum[spots_zsum.gene == gene], img) for gene in track(spots_zsum.gene.unique(), description='[green]Projecting spots...')] + + # Stack images on the c-axis + spot_2d_stack = da.stack(spots_2d_list, axis=0) + + ## Write a csv file containing the channel names + channel_names = spots_zsum.gene.unique().tolist() + pd.DataFrame(channel_names).to_csv(args.sample_id + ".channel_names.csv", index=False, header=False) + + #tifffile.imwrite(args.output, spot_2d_stack, metadata={'axes': 'CYX'}) + OmeTiffWriter.save(spot_2d_stack, + args.sample_id + ".tiff", + dim_order = "CYX") From f3e4de9fe3851a1cfa51714c5efa48393ba07ade Mon Sep 17 00:00:00 2001 From: Florian Wuennemann Date: Tue, 19 Sep 2023 22:03:46 +0000 Subject: [PATCH 008/149] Added local modules --- modules/local/mindagap_duplicatefinder.nf | 33 +++++++++++++++++++++++ modules/local/project_spots.nf | 22 +++++++++++++++ workflows/molkart.nf | 29 ++++++++++++++++++-- 3 files changed, 82 insertions(+), 2 deletions(-) create mode 100644 modules/local/mindagap_duplicatefinder.nf create mode 100644 modules/local/project_spots.nf diff --git a/modules/local/mindagap_duplicatefinder.nf b/modules/local/mindagap_duplicatefinder.nf new file mode 100644 index 0000000..3a11015 --- /dev/null +++ b/modules/local/mindagap_duplicatefinder.nf @@ -0,0 +1,33 @@ +process MINDAGAP_DUPLICATEFINDER { + tag "$meta.id" + label 'process_single' + + conda "bioconda::mindagap=0.0.2" + container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? + 'https://depot.galaxyproject.org/singularity/mindagap:0.0.2--pyhdfd78af_1': + 'quay.io/biocontainers/mindagap:0.0.2--pyhdfd78af_1' }" + + input: + tuple val(meta), path(spot_table) + + output: + tuple val(meta), path("*markedDups.txt"), emit: marked_dups_spots + path "versions.yml" , emit: versions + + when: + task.ext.when == null || task.ext.when + + script: + def args = task.ext.args ?: '' + def prefix = task.ext.prefix ?: "${meta.id}" + """ + duplicate_finder.py \\ + $spot_table \\ + $args + + cat <<-END_VERSIONS > versions.yml + "${task.process}": + mindagap: \$(mindagap.py test -v) + END_VERSIONS + """ +} diff --git a/modules/local/project_spots.nf b/modules/local/project_spots.nf new file mode 100644 index 0000000..e21f47c --- /dev/null +++ b/modules/local/project_spots.nf @@ -0,0 +1,22 @@ +process PROJECT_SPOTS{ + debug true + tag "Projecting spots $meta" + + container 'wuennemannflorian/project_spots:latest' + + input: + tuple val(meta), path(spots) + path(img) + + output: + tuple val(meta), path("${spots.baseName}.tiff"), emit: img_spots + tuple val(meta), path("${spots.baseName}.channel_names.csv"), emit: channel_names + + script: + """ + project_spots.dask.py \ + --input ${spots} \ + --sample_id ${spots.baseName} \ + --img_dims $img + """ +} diff --git a/workflows/molkart.nf b/workflows/molkart.nf index bc7bbfb..64a94bc 100644 --- a/workflows/molkart.nf +++ b/workflows/molkart.nf @@ -32,6 +32,9 @@ ch_multiqc_custom_methods_description = params.multiqc_methods_description ? fil ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ */ +include { MINDAGAP_DUPLICATEFINDER } from '../modules/local/mindagap_duplicatefinder' +include { PROJECT_SPOTS } from '../modules/local/project_spots' + // // SUBWORKFLOW: Consisting of a mix of local and nf-core/modules // @@ -71,7 +74,6 @@ workflow MOLKART { // SUBWORKFLOW: Read in samplesheet, validate and stage input files // ch_from_samplesheet = Channel.fromSamplesheet("input") - ch_from_samplesheet.view() ch_from_samplesheet .map { sample_id, nuclear_image, spot_table -> tuple([id: sample_id], nuclear_image) } @@ -99,12 +101,28 @@ workflow MOLKART { // // Cellpose segmentation and quantification - CELLPOSE(MINDAGAP_MINDAGAP.out.tiff, "") + // CELLPOSE(MINDAGAP_MINDAGAP.out.tiff, []) // // MODULE: Run Module Mindagap duplicatefinder // // Filter out potential duplicate spots from the spots table + ch_from_samplesheet + .map { sample_id, nuclear_image, spot_table -> tuple([id: sample_id], spot_table) } + .set { spot_tuple } + + MINDAGAP_DUPLICATEFINDER(spot_tuple) + + dedup_spots = MINDAGAP_DUPLICATEFINDER.out.marked_dups_spots + .join(image_tuple) + dedup_spots.view() + + qc_spots = dedup_spots.map(it -> tuple([id: it[0]],it[1])) + + PROJECT_SPOTS( + dedup_spots.map(it -> tuple(it[0],it[1])), + dedup_spots.map(it -> it[2]) + ) // // MODULE: PROJECT SPOTS @@ -112,6 +130,13 @@ workflow MOLKART { // Transform spot table to 2 dimensional numpy array to use with MCQUANT + /// Prepare input for MCQuant using images and spots + mcquant_cellpose_in = PROJECT_SPOTS.out.img_spots + .join(PROJECT_SPOTS.out.channel_names) + .map{ + meta,tiff,channels -> [meta,tiff,channels]} + .join(cellpose_mask_filt) + // // MODULE: MCQuant // From 4235a641b74625a4661f3cba729d31a6746b34cd Mon Sep 17 00:00:00 2001 From: Florian Wuennemann Date: Wed, 20 Sep 2023 07:56:43 +0000 Subject: [PATCH 009/149] Modified main workflow. --- workflows/molkart.nf | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/workflows/molkart.nf b/workflows/molkart.nf index 64a94bc..2db26ed 100644 --- a/workflows/molkart.nf +++ b/workflows/molkart.nf @@ -101,7 +101,7 @@ workflow MOLKART { // // Cellpose segmentation and quantification - // CELLPOSE(MINDAGAP_MINDAGAP.out.tiff, []) + CELLPOSE(MINDAGAP_MINDAGAP.out.tiff, []) // // MODULE: Run Module Mindagap duplicatefinder @@ -135,7 +135,7 @@ workflow MOLKART { .join(PROJECT_SPOTS.out.channel_names) .map{ meta,tiff,channels -> [meta,tiff,channels]} - .join(cellpose_mask_filt) + .join(CELLPOSE.out.mask) // // MODULE: MCQuant From 9cc6e15f6789ab92e3f02494f9557b428181e307 Mon Sep 17 00:00:00 2001 From: Florian Wuennemann Date: Wed, 20 Sep 2023 08:35:26 +0000 Subject: [PATCH 010/149] Removed Fastqc module. Added parametre for project_spots. --- assets/schema_input.json | 16 +++------- modules.json | 5 ---- modules/nf-core/fastqc/main.nf | 51 -------------------------------- modules/nf-core/fastqc/meta.yml | 52 --------------------------------- nextflow.config | 7 +++++ workflows/molkart.nf | 17 ++++++----- 6 files changed, 21 insertions(+), 127 deletions(-) delete mode 100644 modules/nf-core/fastqc/main.nf delete mode 100644 modules/nf-core/fastqc/meta.yml diff --git a/assets/schema_input.json b/assets/schema_input.json index 671ac7e..dc5883b 100644 --- a/assets/schema_input.json +++ b/assets/schema_input.json @@ -15,20 +15,12 @@ "nuclear_image": { "type": "string", "pattern": ".*.tiff$", - "errorMessage": "FastQ file for reads 1 must be provided, cannot contain spaces and must have extension '.fq.gz' or '.fastq.gz'" + "errorMessage": "Nuclear image must be provided, cannot contain spaces and must have extension '.tiff'" }, "spot_table": { - "errorMessage": "FastQ file for reads 2 cannot contain spaces and must have extension '.fq.gz' or '.fastq.gz'", - "anyOf": [ - { - "type": "string", - "pattern": ".*.txt$" - }, - { - "type": "string", - "maxLength": 0 - } - ] + "type": "string", + "pattern": ".*.txt$", + "errorMessage": "Spot table must be provided, has to have shape x,y,z,gene with sep = '\t', cannot contain spaces and must have extension '.txt'" } }, "required": ["sample", "nuclear_image", "spot_table"] diff --git a/modules.json b/modules.json index ccab519..612cb9f 100644 --- a/modules.json +++ b/modules.json @@ -20,11 +20,6 @@ "git_sha": "b9829e1064382745d8dff7f1d74d2138d2864f71", "installed_by": ["modules"] }, - "fastqc": { - "branch": "master", - "git_sha": "c8e35eb2055c099720a75538d1b8adb3fb5a464c", - "installed_by": ["modules"] - }, "ilastik/multicut": { "branch": "master", "git_sha": "6f150e1503c0826c21fedf1fa566cdbecbe98ec7", diff --git a/modules/nf-core/fastqc/main.nf b/modules/nf-core/fastqc/main.nf deleted file mode 100644 index 9ae5838..0000000 --- a/modules/nf-core/fastqc/main.nf +++ /dev/null @@ -1,51 +0,0 @@ -process FASTQC { - tag "$meta.id" - label 'process_medium' - - conda "bioconda::fastqc=0.11.9" - container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? - 'https://depot.galaxyproject.org/singularity/fastqc:0.11.9--0' : - 'quay.io/biocontainers/fastqc:0.11.9--0' }" - - input: - tuple val(meta), path(reads) - - output: - tuple val(meta), path("*.html"), emit: html - tuple val(meta), path("*.zip") , emit: zip - path "versions.yml" , emit: versions - - when: - task.ext.when == null || task.ext.when - - script: - def args = task.ext.args ?: '' - def prefix = task.ext.prefix ?: "${meta.id}" - // Make list of old name and new name pairs to use for renaming in the bash while loop - def old_new_pairs = reads instanceof Path || reads.size() == 1 ? [[ reads, "${prefix}.${reads.extension}" ]] : reads.withIndex().collect { entry, index -> [ entry, "${prefix}_${index + 1}.${entry.extension}" ] } - def rename_to = old_new_pairs*.join(' ').join(' ') - def renamed_files = old_new_pairs.collect{ old_name, new_name -> new_name }.join(' ') - """ - printf "%s %s\\n" $rename_to | while read old_name new_name; do - [ -f "\${new_name}" ] || ln -s \$old_name \$new_name - done - fastqc $args --threads $task.cpus $renamed_files - - cat <<-END_VERSIONS > versions.yml - "${task.process}": - fastqc: \$( fastqc --version | sed -e "s/FastQC v//g" ) - END_VERSIONS - """ - - stub: - def prefix = task.ext.prefix ?: "${meta.id}" - """ - touch ${prefix}.html - touch ${prefix}.zip - - cat <<-END_VERSIONS > versions.yml - "${task.process}": - fastqc: \$( fastqc --version | sed -e "s/FastQC v//g" ) - END_VERSIONS - """ -} diff --git a/modules/nf-core/fastqc/meta.yml b/modules/nf-core/fastqc/meta.yml deleted file mode 100644 index 4da5bb5..0000000 --- a/modules/nf-core/fastqc/meta.yml +++ /dev/null @@ -1,52 +0,0 @@ -name: fastqc -description: Run FastQC on sequenced reads -keywords: - - quality control - - qc - - adapters - - fastq -tools: - - fastqc: - description: | - FastQC gives general quality metrics about your reads. - It provides information about the quality score distribution - across your reads, the per base sequence content (%A/C/G/T). - You get information about adapter contamination and other - overrepresented sequences. - homepage: https://www.bioinformatics.babraham.ac.uk/projects/fastqc/ - documentation: https://www.bioinformatics.babraham.ac.uk/projects/fastqc/Help/ - licence: ["GPL-2.0-only"] -input: - - meta: - type: map - description: | - Groovy Map containing sample information - e.g. [ id:'test', single_end:false ] - - reads: - type: file - description: | - List of input FastQ files of size 1 and 2 for single-end and paired-end data, - respectively. -output: - - meta: - type: map - description: | - Groovy Map containing sample information - e.g. [ id:'test', single_end:false ] - - html: - type: file - description: FastQC report - pattern: "*_{fastqc.html}" - - zip: - type: file - description: FastQC report archive - pattern: "*_{fastqc.zip}" - - versions: - type: file - description: File containing software versions - pattern: "versions.yml" -authors: - - "@drpatelh" - - "@grst" - - "@ewels" - - "@FelixKrueger" diff --git a/nextflow.config b/nextflow.config index 52e2b0a..4907b9e 100644 --- a/nextflow.config +++ b/nextflow.config @@ -256,3 +256,10 @@ def check_max(obj, type) { } } } + +/// TODO: Make sure to use label 'process_medium' for this or optimize python code! This is a temporary fix to make it work for testing +process { + withName: "PROJECT_SPOTS" { + memory = "16GB" + } +} diff --git a/workflows/molkart.nf b/workflows/molkart.nf index 2db26ed..138cd35 100644 --- a/workflows/molkart.nf +++ b/workflows/molkart.nf @@ -96,13 +96,6 @@ workflow MOLKART { // APPLY_CLAHE_DASK(MKIMG_STACKS.out.mcimage) TODO : Add local module for testing - // - // MODULE: Cellpose segmentation - // - - // Cellpose segmentation and quantification - CELLPOSE(MINDAGAP_MINDAGAP.out.tiff, []) - // // MODULE: Run Module Mindagap duplicatefinder // @@ -129,6 +122,14 @@ workflow MOLKART { // // Transform spot table to 2 dimensional numpy array to use with MCQUANT +/* + + // + // MODULE: Cellpose segmentation + // + + // Cellpose segmentation and quantification + CELLPOSE(MINDAGAP_MINDAGAP.out.tiff, []) /// Prepare input for MCQuant using images and spots mcquant_cellpose_in = PROJECT_SPOTS.out.img_spots @@ -137,6 +138,8 @@ workflow MOLKART { meta,tiff,channels -> [meta,tiff,channels]} .join(CELLPOSE.out.mask) +*/ + // // MODULE: MCQuant // From b5855098926e4b8e1b150522749dfb83a083866a Mon Sep 17 00:00:00 2001 From: Florian Wuennemann Date: Wed, 20 Sep 2023 13:35:20 +0000 Subject: [PATCH 011/149] Fully working minimal pipeline. --- bin/apply_clahe.dask.py | 181 +++++++++++++++++++++++++++++++++ bin/collect_QC.py | 84 +++++++++++++++ conf/modules.config | 19 ++-- conf/test.config | 6 +- modules/local/clahe_dask.nf | 25 +++++ modules/local/molcart_qc.nf | 27 +++++ modules/local/project_spots.nf | 4 +- nextflow.config | 7 -- workflows/molkart.nf | 58 +++++++---- 9 files changed, 371 insertions(+), 40 deletions(-) create mode 100755 bin/apply_clahe.dask.py create mode 100755 bin/collect_QC.py create mode 100644 modules/local/clahe_dask.nf create mode 100644 modules/local/molcart_qc.nf diff --git a/bin/apply_clahe.dask.py b/bin/apply_clahe.dask.py new file mode 100755 index 0000000..2f51491 --- /dev/null +++ b/bin/apply_clahe.dask.py @@ -0,0 +1,181 @@ +#!/usr/bin/env python +from __future__ import print_function, division +from distutils.log import error +import time +import argparse +from argparse import ArgumentParser as AP +from os.path import abspath +import os +import numpy as np +import tifffile as tf +from skimage.exposure import equalize_adapthist +from multiprocessing.spawn import import_main_path +import sys +import copy +import argparse +import numpy as np +import tifffile +import zarr +import skimage.transform +from aicsimageio import aics_image as AI +from ome_types import from_tiff, to_xml +from os.path import abspath +from argparse import ArgumentParser as AP +import time +#from memory_profiler import profile +# This API is apparently changing in skimage 1.0 but it's not clear to +# me what the replacement will be, if any. We'll explicitly import +# this so it will break loudly if someone tries this with skimage 1.0. +try: + from skimage.util.dtype import _convert as dtype_convert +except ImportError: + from skimage.util.dtype import convert as dtype_convert + + +def get_args(): + # Script description + description="""Easy-to-use, large scale CLAHE""" + + # Add parser + parser = AP(description=description, formatter_class=argparse.RawDescriptionHelpFormatter) + + # Sections + inputs = parser.add_argument_group(title="Required Input", description="Path to required input file") + inputs.add_argument("-r", "--raw", dest="raw", action="store", required=True, help="File path to input image.") + inputs.add_argument("-o", "--output", dest="output", action="store", required=True, help="Path to output image.") + inputs.add_argument("-c", "--channel", dest="channel", action="store", required=True, help="Channel on which CLAHE will be applied") + inputs.add_argument("-l", "--cliplimit", dest="clip", action="store", required=True, help="Clip Limit for CLAHE") + inputs.add_argument("--kernel", dest="kernel", action="store", required=False, default=None, help="Kernel size for CLAHE") + inputs.add_argument("-g", "--nbins", dest="nbins", action="store", required=False, default=256, help="Number of bins for CLAHE") + inputs.add_argument("-p", "--pixel-size", dest="pixel_size", action="store", required=True, help="Image pixel size") + + arg = parser.parse_args() + + # Standardize paths + arg.raw = abspath(arg.raw) + arg.channel = int(arg.channel) + arg.clip = float(arg.clip) + arg.pixel_size = float(arg.pixel_size) + arg.nbins = int(arg.nbins) + arg.kernel = int(arg.kernel) + + return arg + +def preduce(coords, img_in, img_out): + print(img_in.dtype) + (iy1, ix1), (iy2, ix2) = coords + (oy1, ox1), (oy2, ox2) = np.array(coords) // 2 + tile = skimage.img_as_float32(img_in[iy1:iy2, ix1:ix2]) + tile = skimage.transform.downscale_local_mean(tile, (2, 2)) + tile = dtype_convert(tile, 'uint16') + #tile = dtype_convert(tile, img_in.dtype) + img_out[oy1:oy2, ox1:ox2] = tile + +def format_shape(shape): + return "%dx%d" % (shape[1], shape[0]) + +def subres_tiles(level, level_full_shapes, tile_shapes, outpath, scale): + print(f"\n processing level {level}") + assert level >= 1 + num_channels, h, w = level_full_shapes[level] + tshape = tile_shapes[level] or (h, w) + tiff = tifffile.TiffFile(outpath) + zimg = zarr.open(tiff.aszarr(series=0, level=level-1, squeeze=False)) + for c in range(num_channels): + sys.stdout.write( + f"\r processing channel {c + 1}/{num_channels}" + ) + sys.stdout.flush() + th = tshape[0] * scale + tw = tshape[1] * scale + for y in range(0, zimg.shape[1], th): + for x in range(0, zimg.shape[2], tw): + a = zimg[c, y:y+th, x:x+tw, 0] + a = skimage.transform.downscale_local_mean( + a, (scale, scale) + ) + if np.issubdtype(zimg.dtype, np.integer): + a = np.around(a) + a = a.astype('uint16') + yield a + +def main(args): + print(f"Head directory = {args.raw}") + print(f"Channel = {args.channel}, ClipLimit = {args.clip}, nbins = {args.nbins}, kernel_size = {args.kernel}, pixel_size = {args.pixel_size}") + + #clahe = cv2.createCLAHE(clipLimit = int(args.clip), tileGridSize=tuple(map(int, args.grid))) + + img_raw = AI.AICSImage(args.raw) + img_dask = img_raw.get_image_dask_data("CYX").astype('uint16') + adapted = img_dask[args.channel].compute()/65535 + adapted = (equalize_adapthist(adapted, kernel_size=args.kernel, clip_limit=args.clip, nbins=args.nbins)*65535).astype('uint16') + img_dask[args.channel] = adapted + + # construct levels + tile_size = 1024 + scale = 2 + + pixel_size = args.pixel_size + dtype = img_dask.dtype + base_shape = img_dask[0].shape + num_channels = img_dask.shape[0] + num_levels = (np.ceil(np.log2(max(base_shape) / tile_size)) + 1).astype(int) + factors = 2 ** np.arange(num_levels) + shapes = (np.ceil(np.array(base_shape) / factors[:,None])).astype(int) + + print("Pyramid level sizes: ") + for i, shape in enumerate(shapes): + print(f" level {i+1}: {format_shape(shape)}", end="") + if i == 0: + print("(original size)", end="") + print() + print() + print(shapes) + + level_full_shapes = [] + for shape in shapes: + level_full_shapes.append((num_channels, shape[0], shape[1])) + level_shapes = shapes + tip_level = np.argmax(np.all(level_shapes < tile_size, axis=1)) + tile_shapes = [ + (tile_size, tile_size) if i <= tip_level else None + for i in range(len(level_shapes)) + ] + + # write pyramid + with tifffile.TiffWriter(args.output, ome=True, bigtiff=True) as tiff: + tiff.write( + data = img_dask, + shape = level_full_shapes[0], + subifds=int(num_levels-1), + dtype=dtype, + resolution=(10000 / pixel_size, 10000 / pixel_size, "centimeter"), + tile=tile_shapes[0] + ) + for level, (shape, tile_shape) in enumerate( + zip(level_full_shapes[1:], tile_shapes[1:]), 1 + ): + tiff.write( + data = subres_tiles(level, level_full_shapes, tile_shapes, args.output, scale), + shape=shape, + subfiletype=1, + dtype=dtype, + tile=tile_shape + ) + + # note about metadata: the channels, planes etc were adjusted not to include the removed channels, however + # the channel ids have stayed the same as before removal. E.g if channels 1 and 2 are removed, + # the channel ids in the metadata will skip indices 1 and 2 (channel_id:0, channel_id:3, channel_id:4 ...) + #tifffile.tiffcomment(args.output, to_xml(metadata)) + print() + + +if __name__ == '__main__': + # Read in arguments + args = get_args() + + # Run script + st = time.time() + main(args) + rt = time.time() - st + print(f"Script finished in {rt // 60:.0f}m {rt % 60:.0f}s") diff --git a/bin/collect_QC.py b/bin/collect_QC.py new file mode 100755 index 0000000..54992e2 --- /dev/null +++ b/bin/collect_QC.py @@ -0,0 +1,84 @@ +#!/usr/bin/env python + +#### This script takes regionprops_tabe output from mcquant and the raw spot tables from Resolve bioscience as input +#### and calculates some QC metrics for masks and spot assignments + +import argparse +import pandas as pd + +def summarize_spots(spot_table): + ## Calculate number of spots per gene + tx_per_gene = spot_table.groupby('gene').count().reset_index() + + ## Calculate the total number of spots in spot_table + total_spots = spot_table.shape[0] + + return(tx_per_gene,total_spots) + +def summarize_segmasks(mcquant,spots_summary): + ## Calculate the total number of cells (rows) in mcquant + total_cells = mcquant.shape[0] + + ## Calculate the average segmentation area from column Area in mcquant + avg_area = mcquant['Area'].mean() + + ## Calculate the % of spots assigned + ## Subset mcquant for all columns with _intensity_sum in the column name and sum the column values + spot_assign = mcquant.filter(regex='_intensity_sum').sum(axis=1) + spot_assign_total = int(sum(spot_assign)) + spot_assign_per_cell = total_cells and spot_assign_total / total_cells or 0 + #spot_assign_per_cell = spot_assign_total / total_cells + spot_assign_percent = spot_assign_total / spots_summary[1] * 100 + + return(total_cells,avg_area,spot_assign_per_cell,spot_assign_total,spot_assign_percent) + +if __name__ == "__main__": + # Write an argparse with input options mcquant_in, spots and output options outdir, sample_id + parser = argparse.ArgumentParser() + parser.add_argument( + "-i", + "--mcquant", + help="mcquant regionprops_table." + ) + parser.add_argument( + "-s", + "--spots", + help="Resolve biosciences spot table." + ) + parser.add_argument( + "-o", + "--outdir", + help="Output directory." + ) + + parser.add_argument( + "-d", + "--sample_id", + help="Sample ID." + ) + + parser.add_argument( + "-g", + "--segmentation_method", + help="Segmentation method used." + ) + + args = parser.parse_args() + + ## Read in mcquant table + mcquant = pd.read_csv(args.mcquant) + + ## Read in spot table + spots = pd.read_table(args.spots, sep='\t', names=['x', 'y', 'z', 'gene']) + spots = spots[~spots.gene.str.contains("Duplicated")] + + ## Summarize spots table + summary_spots = summarize_spots(spots) + summary_segmentation = summarize_segmasks(mcquant,summary_spots) + + ## Create pandas data frame with one row per parameter and write each value in summary_segmentation to a new row in the data frame + summary_df = pd.DataFrame(columns=['sample_id','segmentation_method','total_cells','avg_area','total_spots','spot_assign_per_cell','spot_assign_total','spot_assign_percent',]) + summary_df.loc[0] = [args.sample_id + "_" + args.segmentation_method,args.segmentation_method,summary_segmentation[0],summary_segmentation[1],summary_spots[1],summary_segmentation[2],summary_segmentation[3],summary_segmentation[4]] + + # Write summary_df to a csv file + summary_df.to_csv(f"{args.outdir}/{args.sample_id}.{args.segmentation_method}.spot_QC.csv", header = True, index=False) diff --git a/conf/modules.config b/conf/modules.config index da58a5d..2c5b1fa 100644 --- a/conf/modules.config +++ b/conf/modules.config @@ -18,24 +18,23 @@ process { saveAs: { filename -> filename.equals('versions.yml') ? null : filename } ] - withName: SAMPLESHEET_CHECK { + withName: CUSTOM_DUMPSOFTWAREVERSIONS { publishDir = [ path: { "${params.outdir}/pipeline_info" }, mode: params.publish_dir_mode, - saveAs: { filename -> filename.equals('versions.yml') ? null : filename } + pattern: '*_versions.yml' ] } - withName: FASTQC { - ext.args = '--quiet' + withName: "PROJECT_SPOTS" { + memory = "16GB" } - withName: CUSTOM_DUMPSOFTWAREVERSIONS { - publishDir = [ - path: { "${params.outdir}/pipeline_info" }, - mode: params.publish_dir_mode, - pattern: '*_versions.yml' - ] + withName: "DEEPCELL_MESMER" { + memory = "16GB" + cpus = 8 + ext.args = '--image-mpp=0.138 --nuclear-channel 0 --compartment nuclear' + containerOptions = '--entrypoint ""' } } diff --git a/conf/test.config b/conf/test.config index f593198..d74ce0e 100644 --- a/conf/test.config +++ b/conf/test.config @@ -15,9 +15,9 @@ params { config_profile_description = 'Minimal test dataset to check pipeline function' // Limit resources so that this can run on GitHub Actions - max_cpus = 2 - max_memory = '6.GB' - max_time = '6.h' + max_cpus = + max_memory = '16.GB' + max_time = '4.h' // Input data // TODO nf-core: Specify the paths to your test data on nf-core/test-datasets diff --git a/modules/local/clahe_dask.nf b/modules/local/clahe_dask.nf new file mode 100644 index 0000000..c3fece4 --- /dev/null +++ b/modules/local/clahe_dask.nf @@ -0,0 +1,25 @@ +process CLAHE_DASK{ + debug false + tag "Applying CLAHE to $meta.id" + + container 'ghcr.io/schapirolabor/background_subtraction:v0.3.3' + + input: + tuple val(meta), path(image) + + output: + tuple val(meta), path("*.clahe.tiff") , emit: img_clahe + + script: + """ + apply_clahe.dask.py \ + --raw ${image} \ + --output ${image.baseName}.clahe.tiff \ + --cliplimit 0.01 \ + --kernel 25 \ + --nbins 256 \ + --channel 0 \ + --pixel-size 0.138 + """ + +} diff --git a/modules/local/molcart_qc.nf b/modules/local/molcart_qc.nf new file mode 100644 index 0000000..1226414 --- /dev/null +++ b/modules/local/molcart_qc.nf @@ -0,0 +1,27 @@ +process MOLCART_QC{ + tag "$meta.id" + container 'wuennemannflorian/project_spots:latest' + + input: + tuple val(meta), path(mcquant) + tuple val(meta2), path(spot_table) + val(segmethod) + + output: + path("*.csv"), emit: qc + + when: + task.ext.when == null || task.ext.when + + script: + def args = task.ext.args ?: '' + def sample_id = "${meta.id}" + """ + collect_QC.py \ + --mcquant $mcquant \ + --spots $spot_table \ + --sample_id $sample_id \ + --segmentation_method $segmethod \ + --outdir . + """ +} diff --git a/modules/local/project_spots.nf b/modules/local/project_spots.nf index e21f47c..f713b24 100644 --- a/modules/local/project_spots.nf +++ b/modules/local/project_spots.nf @@ -1,6 +1,6 @@ process PROJECT_SPOTS{ - debug true - tag "Projecting spots $meta" + debug false + tag "Projecting spots $meta.id" container 'wuennemannflorian/project_spots:latest' diff --git a/nextflow.config b/nextflow.config index 4907b9e..52e2b0a 100644 --- a/nextflow.config +++ b/nextflow.config @@ -256,10 +256,3 @@ def check_max(obj, type) { } } } - -/// TODO: Make sure to use label 'process_medium' for this or optimize python code! This is a temporary fix to make it work for testing -process { - withName: "PROJECT_SPOTS" { - memory = "16GB" - } -} diff --git a/workflows/molkart.nf b/workflows/molkart.nf index 138cd35..2a7ed69 100644 --- a/workflows/molkart.nf +++ b/workflows/molkart.nf @@ -32,8 +32,10 @@ ch_multiqc_custom_methods_description = params.multiqc_methods_description ? fil ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ */ +include { CLAHE_DASK } from '../modules/local/clahe_dask' include { MINDAGAP_DUPLICATEFINDER } from '../modules/local/mindagap_duplicatefinder' include { PROJECT_SPOTS } from '../modules/local/project_spots' +include { MOLCART_QC } from '../modules/local/molcart_qc' // // SUBWORKFLOW: Consisting of a mix of local and nf-core/modules @@ -94,10 +96,10 @@ workflow MOLKART { // MODULE: Apply Contract-limited adaptive histogram equalization (CLAHE) // - // APPLY_CLAHE_DASK(MKIMG_STACKS.out.mcimage) TODO : Add local module for testing + CLAHE_DASK(MINDAGAP_MINDAGAP.out.tiff) // TODO : Add local module for testing // - // MODULE: Run Module Mindagap duplicatefinder + // MODULE: MINDAGAP Duplicatefinder // // Filter out potential duplicate spots from the spots table ch_from_samplesheet @@ -106,9 +108,13 @@ workflow MOLKART { MINDAGAP_DUPLICATEFINDER(spot_tuple) + // + // MODULE: PROJECT SPOTS + // + // Transform spot table to 2 dimensional numpy array to use with MCQUANT + dedup_spots = MINDAGAP_DUPLICATEFINDER.out.marked_dups_spots .join(image_tuple) - dedup_spots.view() qc_spots = dedup_spots.map(it -> tuple([id: it[0]],it[1])) @@ -117,33 +123,49 @@ workflow MOLKART { dedup_spots.map(it -> it[2]) ) - // - // MODULE: PROJECT SPOTS + DEEPCELL_MESMER(CLAHE_DASK.out.img_clahe, [[:],[]]) + + /// Prepare input for MCQuant using images and spots + mcquant_in = PROJECT_SPOTS.out.img_spots + .join(PROJECT_SPOTS.out.channel_names) + .map{ + meta,tiff,channels -> [meta,tiff,channels] + } + .join(DEEPCELL_MESMER.out.mask) + + // + // MODULE: MCQuant // - // Transform spot table to 2 dimensional numpy array to use with MCQUANT -/* + MCQUANT( + mcquant_in.map{it -> tuple([id:it[0]],it[1])}, + mcquant_in.map{it -> tuple([id:it[0]],it[3])}, + mcquant_in.map{it -> tuple([id:it[0]],it[2])} + ) // - // MODULE: Cellpose segmentation + // MODULE: MOLCART_QC // - // Cellpose segmentation and quantification - CELLPOSE(MINDAGAP_MINDAGAP.out.tiff, []) + molcart_qc = MCQUANT.out.csv + .join(qc_spots) - /// Prepare input for MCQuant using images and spots - mcquant_cellpose_in = PROJECT_SPOTS.out.img_spots - .join(PROJECT_SPOTS.out.channel_names) - .map{ - meta,tiff,channels -> [meta,tiff,channels]} - .join(CELLPOSE.out.mask) + MOLCART_QC( + molcart_qc.map{it -> tuple(it[0],it[1])}, + molcart_qc.map{it -> tuple(it[0],it[2])}, + "Mesmer" + ) -*/ +/* // - // MODULE: MCQuant + // MODULE: Cellpose segmentation // + // Cellpose segmentation and quantification + CELLPOSE(MINDAGAP_MINDAGAP.out.tiff, []) +*/ + // // MODULE: Run Module MOLCART_QC // From f67dd2bf38b172c6b69598e52f17f79d3901342c Mon Sep 17 00:00:00 2001 From: Florian Wuennemann Date: Wed, 20 Sep 2023 13:51:59 +0000 Subject: [PATCH 012/149] Added version parsing for modules. --- workflows/molkart.nf | 31 +++++++++++++++++++------------ 1 file changed, 19 insertions(+), 12 deletions(-) diff --git a/workflows/molkart.nf b/workflows/molkart.nf index 2a7ed69..5aaf127 100644 --- a/workflows/molkart.nf +++ b/workflows/molkart.nf @@ -86,9 +86,7 @@ workflow MOLKART { // MINDAGAP_MINDAGAP(image_tuple, 7, 100) - CUSTOM_DUMPSOFTWAREVERSIONS ( - ch_versions.unique().collectFile(name: 'collated_versions.yml') - ) + ch_versions = ch_versions.mix(MINDAGAP_MINDAGAP.out.versions) // Stack images @@ -108,6 +106,8 @@ workflow MOLKART { MINDAGAP_DUPLICATEFINDER(spot_tuple) + ch_versions = ch_versions.mix(MINDAGAP_DUPLICATEFINDER.out.versions) + // // MODULE: PROJECT SPOTS // @@ -125,6 +125,18 @@ workflow MOLKART { DEEPCELL_MESMER(CLAHE_DASK.out.img_clahe, [[:],[]]) + ch_versions = ch_versions.mix(DEEPCELL_MESMER.out.versions) + + /* + + // + // MODULE: Cellpose segmentation + // + + // Cellpose segmentation and quantification + CELLPOSE(MINDAGAP_MINDAGAP.out.tiff, []) + */ + /// Prepare input for MCQuant using images and spots mcquant_in = PROJECT_SPOTS.out.img_spots .join(PROJECT_SPOTS.out.channel_names) @@ -143,6 +155,7 @@ workflow MOLKART { mcquant_in.map{it -> tuple([id:it[0]],it[2])} ) + ch_versions = ch_versions.mix(MCQUANT.out.versions) // // MODULE: MOLCART_QC // @@ -156,15 +169,9 @@ workflow MOLKART { "Mesmer" ) -/* - - // - // MODULE: Cellpose segmentation - // - - // Cellpose segmentation and quantification - CELLPOSE(MINDAGAP_MINDAGAP.out.tiff, []) -*/ + CUSTOM_DUMPSOFTWAREVERSIONS ( + ch_versions.unique().collectFile(name: 'collated_versions.yml') + ) // // MODULE: Run Module MOLCART_QC From 75aff2731f4d59e3364109b610464a5be549245b Mon Sep 17 00:00:00 2001 From: Florian Wuennemann Date: Wed, 20 Sep 2023 15:28:47 +0000 Subject: [PATCH 013/149] Minimal pipeline completely working. --- conf/modules.config | 4 ++++ workflows/molkart.nf | 3 +-- 2 files changed, 5 insertions(+), 2 deletions(-) diff --git a/conf/modules.config b/conf/modules.config index 2c5b1fa..90b3a7d 100644 --- a/conf/modules.config +++ b/conf/modules.config @@ -37,4 +37,8 @@ process { containerOptions = '--entrypoint ""' } + withName: "MCQUANT" { + ext.args = "--intensity_props intensity_sum" + } + } diff --git a/workflows/molkart.nf b/workflows/molkart.nf index 5aaf127..72fdf76 100644 --- a/workflows/molkart.nf +++ b/workflows/molkart.nf @@ -134,7 +134,7 @@ workflow MOLKART { // // Cellpose segmentation and quantification - CELLPOSE(MINDAGAP_MINDAGAP.out.tiff, []) + CELLPOSE(CLAHE_DASK.out.tiff, []) */ /// Prepare input for MCQuant using images and spots @@ -190,7 +190,6 @@ workflow MOLKART { ch_multiqc_files = ch_multiqc_files.mix(ch_workflow_summary.collectFile(name: 'workflow_summary_mqc.yaml')) ch_multiqc_files = ch_multiqc_files.mix(ch_methods_description.collectFile(name: 'methods_description_mqc.yaml')) ch_multiqc_files = ch_multiqc_files.mix(CUSTOM_DUMPSOFTWAREVERSIONS.out.mqc_yml.collect()) - /// ch_multiqc_files = ch_multiqc_files.mix(FASTQC.out.zip.collect{it[1]}.ifEmpty([])) TODO: remove MULTIQC ( ch_multiqc_files.collect(), From 3a1dcd83b6521e984d702ccb009caf047348ca6b Mon Sep 17 00:00:00 2001 From: nf-core-bot Date: Mon, 25 Sep 2023 15:16:25 +0000 Subject: [PATCH 014/149] Template update for nf-core/tools version 2.10 --- .devcontainer/devcontainer.json | 1 + .github/CONTRIBUTING.md | 4 +- .github/workflows/linting.yml | 2 +- .github/workflows/release-announcments.yml | 68 +++++++++ CITATIONS.md | 2 +- CODE_OF_CONDUCT.md | 133 ++++++++++++++---- README.md | 21 +-- assets/multiqc_config.yml | 4 +- conf/modules.config | 9 ++ docs/output.md | 5 +- docs/usage.md | 16 ++- lib/NfcoreTemplate.groovy | 16 +++ lib/WorkflowMolkart.groovy | 2 +- main.nf | 3 + modules.json | 6 +- .../custom/dumpsoftwareversions/main.nf | 2 +- modules/nf-core/fastqc/main.nf | 8 +- modules/nf-core/multiqc/main.nf | 2 +- nextflow.config | 7 +- nextflow_schema.json | 15 -- workflows/molkart.nf | 1 + 21 files changed, 251 insertions(+), 76 deletions(-) create mode 100644 .github/workflows/release-announcments.yml diff --git a/.devcontainer/devcontainer.json b/.devcontainer/devcontainer.json index ea27a58..4ecfbfe 100644 --- a/.devcontainer/devcontainer.json +++ b/.devcontainer/devcontainer.json @@ -2,6 +2,7 @@ "name": "nfcore", "image": "nfcore/gitpod:latest", "remoteUser": "gitpod", + "runArgs": ["--privileged"], // Configure tool-specific properties. "customizations": { diff --git a/.github/CONTRIBUTING.md b/.github/CONTRIBUTING.md index 393a6c0..016168f 100644 --- a/.github/CONTRIBUTING.md +++ b/.github/CONTRIBUTING.md @@ -9,7 +9,9 @@ Please use the pre-filled template to save time. However, don't be put off by this template - other more general issues and suggestions are welcome! Contributions to the code are even more welcome ;) -> If you need help using or modifying nf-core/molkart then the best place to ask is on the nf-core Slack [#molkart](https://nfcore.slack.com/channels/molkart) channel ([join our Slack here](https://nf-co.re/join/slack)). +:::info +If you need help using or modifying nf-core/molkart then the best place to ask is on the nf-core Slack [#molkart](https://nfcore.slack.com/channels/molkart) channel ([join our Slack here](https://nf-co.re/join/slack)). +::: ## Contribution workflow diff --git a/.github/workflows/linting.yml b/.github/workflows/linting.yml index 888cb4b..b8bdd21 100644 --- a/.github/workflows/linting.yml +++ b/.github/workflows/linting.yml @@ -78,7 +78,7 @@ jobs: - uses: actions/setup-python@v4 with: - python-version: "3.8" + python-version: "3.11" architecture: "x64" - name: Install dependencies diff --git a/.github/workflows/release-announcments.yml b/.github/workflows/release-announcments.yml new file mode 100644 index 0000000..6ad3392 --- /dev/null +++ b/.github/workflows/release-announcments.yml @@ -0,0 +1,68 @@ +name: release-announcements +# Automatic release toot and tweet anouncements +on: + release: + types: [published] + workflow_dispatch: + +jobs: + toot: + runs-on: ubuntu-latest + steps: + - uses: rzr/fediverse-action@master + with: + access-token: ${{ secrets.MASTODON_ACCESS_TOKEN }} + host: "mstdn.science" # custom host if not "mastodon.social" (default) + # GitHub event payload + # https://docs.github.com/en/developers/webhooks-and-events/webhooks/webhook-events-and-payloads#release + message: | + Pipeline release! ${{ github.repository }} v${{ github.event.release.tag_name }} - ${{ github.event.release.name }}! + + Please see the changelog: ${{ github.event.release.html_url }} + + send-tweet: + runs-on: ubuntu-latest + + steps: + - uses: actions/setup-python@v4 + with: + python-version: "3.10" + - name: Install dependencies + run: pip install tweepy==4.14.0 + - name: Send tweet + shell: python + run: | + import os + import tweepy + + client = tweepy.Client( + access_token=os.getenv("TWITTER_ACCESS_TOKEN"), + access_token_secret=os.getenv("TWITTER_ACCESS_TOKEN_SECRET"), + consumer_key=os.getenv("TWITTER_CONSUMER_KEY"), + consumer_secret=os.getenv("TWITTER_CONSUMER_SECRET"), + ) + tweet = os.getenv("TWEET") + client.create_tweet(text=tweet) + env: + TWEET: | + Pipeline release! ${{ github.repository }} v${{ github.event.release.tag_name }} - ${{ github.event.release.name }}! + + Please see the changelog: ${{ github.event.release.html_url }} + TWITTER_CONSUMER_KEY: ${{ secrets.TWITTER_CONSUMER_KEY }} + TWITTER_CONSUMER_SECRET: ${{ secrets.TWITTER_CONSUMER_SECRET }} + TWITTER_ACCESS_TOKEN: ${{ secrets.TWITTER_ACCESS_TOKEN }} + TWITTER_ACCESS_TOKEN_SECRET: ${{ secrets.TWITTER_ACCESS_TOKEN_SECRET }} + + bsky-post: + runs-on: ubuntu-latest + steps: + - uses: zentered/bluesky-post-action@v0.0.2 + with: + post: | + Pipeline release! ${{ github.repository }} v${{ github.event.release.tag_name }} - ${{ github.event.release.name }}! + + Please see the changelog: ${{ github.event.release.html_url }} + env: + BSKY_IDENTIFIER: ${{ secrets.BSKY_IDENTIFIER }} + BSKY_PASSWORD: ${{ secrets.BSKY_PASSWORD }} + # diff --git a/CITATIONS.md b/CITATIONS.md index 0be89c4..0f74f5d 100644 --- a/CITATIONS.md +++ b/CITATIONS.md @@ -12,7 +12,7 @@ - [FastQC](https://www.bioinformatics.babraham.ac.uk/projects/fastqc/) - > Andrews, S. (2010). FastQC: A Quality Control Tool for High Throughput Sequence Data [Online]. Available online https://www.bioinformatics.babraham.ac.uk/projects/fastqc/. + > Andrews, S. (2010). FastQC: A Quality Control Tool for High Throughput Sequence Data [Online]. - [MultiQC](https://pubmed.ncbi.nlm.nih.gov/27312411/) diff --git a/CODE_OF_CONDUCT.md b/CODE_OF_CONDUCT.md index f4fd052..c089ec7 100644 --- a/CODE_OF_CONDUCT.md +++ b/CODE_OF_CONDUCT.md @@ -1,18 +1,20 @@ -# Code of Conduct at nf-core (v1.0) +# Code of Conduct at nf-core (v1.4) ## Our Pledge -In the interest of fostering an open, collaborative, and welcoming environment, we as contributors and maintainers of nf-core, pledge to making participation in our projects and community a harassment-free experience for everyone, regardless of: +In the interest of fostering an open, collaborative, and welcoming environment, we as contributors and maintainers of nf-core pledge to making participation in our projects and community a harassment-free experience for everyone, regardless of: - Age +- Ability - Body size +- Caste - Familial status - Gender identity and expression - Geographical location - Level of experience - Nationality and national origins - Native language -- Physical and neurological ability +- Neurodiversity - Race or ethnicity - Religion - Sexual identity and orientation @@ -22,80 +24,133 @@ Please note that the list above is alphabetised and is therefore not ranked in a ## Preamble -> Note: This Code of Conduct (CoC) has been drafted by the nf-core Safety Officer and been edited after input from members of the nf-core team and others. "We", in this document, refers to the Safety Officer and members of the nf-core core team, both of whom are deemed to be members of the nf-core community and are therefore required to abide by this Code of Conduct. This document will amended periodically to keep it up-to-date, and in case of any dispute, the most current version will apply. +:::note +This Code of Conduct (CoC) has been drafted by Renuka Kudva, Cris Tuñí, and Michael Heuer, with input from the nf-core Core Team and Susanna Marquez from the nf-core community. "We", in this document, refers to the Safety Officers and members of the nf-core Core Team, both of whom are deemed to be members of the nf-core community and are therefore required to abide by this Code of Conduct. This document will be amended periodically to keep it up-to-date. In case of any dispute, the most current version will apply. +::: -An up-to-date list of members of the nf-core core team can be found [here](https://nf-co.re/about). Our current safety officer is Renuka Kudva. +An up-to-date list of members of the nf-core core team can be found [here](https://nf-co.re/about). + +Our Safety Officers are Saba Nafees, Cris Tuñí, and Michael Heuer. nf-core is a young and growing community that welcomes contributions from anyone with a shared vision for [Open Science Policies](https://www.fosteropenscience.eu/taxonomy/term/8). Open science policies encompass inclusive behaviours and we strive to build and maintain a safe and inclusive environment for all individuals. -We have therefore adopted this code of conduct (CoC), which we require all members of our community and attendees in nf-core events to adhere to in all our workspaces at all times. Workspaces include but are not limited to Slack, meetings on Zoom, Jitsi, YouTube live etc. +We have therefore adopted this CoC, which we require all members of our community and attendees of nf-core events to adhere to in all our workspaces at all times. Workspaces include, but are not limited to, Slack, meetings on Zoom, gather.town, YouTube live etc. -Our CoC will be strictly enforced and the nf-core team reserve the right to exclude participants who do not comply with our guidelines from our workspaces and future nf-core activities. +Our CoC will be strictly enforced and the nf-core team reserves the right to exclude participants who do not comply with our guidelines from our workspaces and future nf-core activities. -We ask all members of our community to help maintain a supportive and productive workspace and to avoid behaviours that can make individuals feel unsafe or unwelcome. Please help us maintain and uphold this CoC. +We ask all members of our community to help maintain supportive and productive workspaces and to avoid behaviours that can make individuals feel unsafe or unwelcome. Please help us maintain and uphold this CoC. -Questions, concerns or ideas on what we can include? Contact safety [at] nf-co [dot] re +Questions, concerns, or ideas on what we can include? Contact members of the Safety Team on Slack or email safety [at] nf-co [dot] re. ## Our Responsibilities -The safety officer is responsible for clarifying the standards of acceptable behavior and are expected to take appropriate and fair corrective action in response to any instances of unacceptable behaviour. +Members of the Safety Team (the Safety Officers) are responsible for clarifying the standards of acceptable behavior and are expected to take appropriate and fair corrective action in response to any instances of unacceptable behaviour. -The safety officer in consultation with the nf-core core team have the right and responsibility to remove, edit, or reject comments, commits, code, wiki edits, issues, and other contributions that are not aligned to this Code of Conduct, or to ban temporarily or permanently any contributor for other behaviors that they deem inappropriate, threatening, offensive, or harmful. +The Safety Team, in consultation with the nf-core core team, have the right and responsibility to remove, edit, or reject comments, commits, code, wiki edits, issues, and other contributions that are not aligned to this CoC, or to ban temporarily or permanently any contributor for other behaviors that they deem inappropriate, threatening, offensive, or harmful. -Members of the core team or the safety officer who violate the CoC will be required to recuse themselves pending investigation. They will not have access to any reports of the violations and be subject to the same actions as others in violation of the CoC. +Members of the core team or the Safety Team who violate the CoC will be required to recuse themselves pending investigation. They will not have access to any reports of the violations and will be subject to the same actions as others in violation of the CoC. -## When are where does this Code of Conduct apply? +## When and where does this Code of Conduct apply? -Participation in the nf-core community is contingent on following these guidelines in all our workspaces and events. This includes but is not limited to the following listed alphabetically and therefore in no order of preference: +Participation in the nf-core community is contingent on following these guidelines in all our workspaces and events, such as hackathons, workshops, bytesize, and collaborative workspaces on gather.town. These guidelines include, but are not limited to, the following (listed alphabetically and therefore in no order of preference): - Communicating with an official project email address. - Communicating with community members within the nf-core Slack channel. - Participating in hackathons organised by nf-core (both online and in-person events). -- Participating in collaborative work on GitHub, Google Suite, community calls, mentorship meetings, email correspondence. -- Participating in workshops, training, and seminar series organised by nf-core (both online and in-person events). This applies to events hosted on web-based platforms such as Zoom, Jitsi, YouTube live etc. +- Participating in collaborative work on GitHub, Google Suite, community calls, mentorship meetings, email correspondence, and on the nf-core gather.town workspace. +- Participating in workshops, training, and seminar series organised by nf-core (both online and in-person events). This applies to events hosted on web-based platforms such as Zoom, gather.town, Jitsi, YouTube live etc. - Representing nf-core on social media. This includes both official and personal accounts. ## nf-core cares 😊 -nf-core's CoC and expectations of respectful behaviours for all participants (including organisers and the nf-core team) include but are not limited to the following (listed in alphabetical order): +nf-core's CoC and expectations of respectful behaviours for all participants (including organisers and the nf-core team) include, but are not limited to, the following (listed in alphabetical order): - Ask for consent before sharing another community member’s personal information (including photographs) on social media. - Be respectful of differing viewpoints and experiences. We are all here to learn from one another and a difference in opinion can present a good learning opportunity. -- Celebrate your accomplishments at events! (Get creative with your use of emojis 🎉 🥳 💯 🙌 !) +- Celebrate your accomplishments! (Get creative with your use of emojis 🎉 🥳 💯 🙌 !) - Demonstrate empathy towards other community members. (We don’t all have the same amount of time to dedicate to nf-core. If tasks are pending, don’t hesitate to gently remind members of your team. If you are leading a task, ask for help if you feel overwhelmed.) - Engage with and enquire after others. (This is especially important given the geographically remote nature of the nf-core community, so let’s do this the best we can) - Focus on what is best for the team and the community. (When in doubt, ask) -- Graciously accept constructive criticism, yet be unafraid to question, deliberate, and learn. +- Accept feedback, yet be unafraid to question, deliberate, and learn. - Introduce yourself to members of the community. (We’ve all been outsiders and we know that talking to strangers can be hard for some, but remember we’re interested in getting to know you and your visions for open science!) -- Show appreciation and **provide clear feedback**. (This is especially important because we don’t see each other in person and it can be harder to interpret subtleties. Also remember that not everyone understands a certain language to the same extent as you do, so **be clear in your communications to be kind.**) +- Show appreciation and **provide clear feedback**. (This is especially important because we don’t see each other in person and it can be harder to interpret subtleties. Also remember that not everyone understands a certain language to the same extent as you do, so **be clear in your communication to be kind.**) - Take breaks when you feel like you need them. -- Using welcoming and inclusive language. (Participants are encouraged to display their chosen pronouns on Zoom or in communication on Slack.) +- Use welcoming and inclusive language. (Participants are encouraged to display their chosen pronouns on Zoom or in communication on Slack) ## nf-core frowns on 😕 -The following behaviours from any participants within the nf-core community (including the organisers) will be considered unacceptable under this code of conduct. Engaging or advocating for any of the following could result in expulsion from nf-core workspaces. +The following behaviours from any participants within the nf-core community (including the organisers) will be considered unacceptable under this CoC. Engaging or advocating for any of the following could result in expulsion from nf-core workspaces: - Deliberate intimidation, stalking or following and sustained disruption of communication among participants of the community. This includes hijacking shared screens through actions such as using the annotate tool in conferencing software such as Zoom. - “Doxing” i.e. posting (or threatening to post) another person’s personal identifying information online. - Spamming or trolling of individuals on social media. -- Use of sexual or discriminatory imagery, comments, or jokes and unwelcome sexual attention. -- Verbal and text comments that reinforce social structures of domination related to gender, gender identity and expression, sexual orientation, ability, physical appearance, body size, race, age, religion or work experience. +- Use of sexual or discriminatory imagery, comments, jokes, or unwelcome sexual attention. +- Verbal and text comments that reinforce social structures of domination related to gender, gender identity and expression, sexual orientation, ability, physical appearance, body size, race, age, religion, or work experience. ### Online Trolling -The majority of nf-core interactions and events are held online. Unfortunately, holding events online comes with the added issue of online trolling. This is unacceptable, reports of such behaviour will be taken very seriously, and perpetrators will be excluded from activities immediately. +The majority of nf-core interactions and events are held online. Unfortunately, holding events online comes with the risk of online trolling. This is unacceptable — reports of such behaviour will be taken very seriously and perpetrators will be excluded from activities immediately. -All community members are required to ask members of the group they are working within for explicit consent prior to taking screenshots of individuals during video calls. +All community members are **required** to ask members of the group they are working with for explicit consent prior to taking screenshots of individuals during video calls. -## Procedures for Reporting CoC violations +## Procedures for reporting CoC violations If someone makes you feel uncomfortable through their behaviours or actions, report it as soon as possible. -You can reach out to members of the [nf-core core team](https://nf-co.re/about) and they will forward your concerns to the safety officer(s). +You can reach out to members of the Safety Team (Saba Nafees, Cris Tuñí, and Michael Heuer) on Slack. Alternatively, contact a member of the nf-core core team [nf-core core team](https://nf-co.re/about), and they will forward your concerns to the Safety Team. + +Issues directly concerning members of the Core Team or the Safety Team will be dealt with by other members of the core team and the safety manager — possible conflicts of interest will be taken into account. nf-core is also in discussions about having an ombudsperson and details will be shared in due course. + +All reports will be handled with the utmost discretion and confidentiality. + +You can also report any CoC violations to safety [at] nf-co [dot] re. In your email report, please do your best to include: + +- Your contact information. +- Identifying information (e.g. names, nicknames, pseudonyms) of the participant who has violated the Code of Conduct. +- The behaviour that was in violation and the circumstances surrounding the incident. +- The approximate time of the behaviour (if different than the time the report was made). +- Other people involved in the incident, if applicable. +- If you believe the incident is ongoing. +- If there is a publicly available record (e.g. mailing list record, a screenshot). +- Any additional information. + +After you file a report, one or more members of our Safety Team will contact you to follow up on your report. + +## Who will read and handle reports + +All reports will be read and handled by the members of the Safety Team at nf-core. + +If members of the Safety Team are deemed to have a conflict of interest with a report, they will be required to recuse themselves as per our Code of Conduct and will not have access to any follow-ups. + +To keep this first report confidential from any of the Safety Team members, please submit your first report by direct messaging on Slack/direct email to any of the nf-core members you are comfortable disclosing the information to, and be explicit about which member(s) you do not consent to sharing the information with. + +## Reviewing reports + +After receiving the report, members of the Safety Team will review the incident report to determine whether immediate action is required, for example, whether there is immediate threat to participants’ safety. + +The Safety Team, in consultation with members of the nf-core core team, will assess the information to determine whether the report constitutes a Code of Conduct violation, for them to decide on a course of action. + +In the case of insufficient information, one or more members of the Safety Team may contact the reporter, the reportee, or any other attendees to obtain more information. -Issues directly concerning members of the core team will be dealt with by other members of the core team and the safety manager, and possible conflicts of interest will be taken into account. nf-core is also in discussions about having an ombudsperson, and details will be shared in due course. +Once additional information is gathered, the Safety Team will collectively review and decide on the best course of action to take, if any. The Safety Team reserves the right to not act on a report. -All reports will be handled with utmost discretion and confidentially. +## Confidentiality + +All reports, and any additional information included, are only shared with the team of safety officers (and possibly members of the core team, in case the safety officer is in violation of the CoC). We will respect confidentiality requests for the purpose of protecting victims of abuse. + +We will not name harassment victims, beyond discussions between the safety officer and members of the nf-core team, without the explicit consent of the individuals involved. + +## Enforcement + +Actions taken by the nf-core’s Safety Team may include, but are not limited to: + +- Asking anyone to stop a behaviour. +- Asking anyone to leave the event and online spaces either temporarily, for the remainder of the event, or permanently. +- Removing access to the gather.town and Slack, either temporarily or permanently. +- Communicating to all participants to reinforce our expectations for conduct and remind what is unacceptable behaviour; this may be public for practical reasons. +- Communicating to all participants that an incident has taken place and how we will act or have acted — this may be for the purpose of letting event participants know we are aware of and dealing with the incident. +- Banning anyone from participating in nf-core-managed spaces, future events, and activities, either temporarily or permanently. +- No action. ## Attribution and Acknowledgements @@ -106,6 +161,22 @@ All reports will be handled with utmost discretion and confidentially. ## Changelog -### v1.0 - March 12th, 2021 +### v1.4 - February 8th, 2022 + +- Included a new member of the Safety Team. Corrected a typographical error in the text. + +### v1.3 - December 10th, 2021 + +- Added a statement that the CoC applies to nf-core gather.town workspaces. Corrected typographical errors in the text. + +### v1.2 - November 12th, 2021 + +- Removed information specific to reporting CoC violations at the Hackathon in October 2021. + +### v1.1 - October 14th, 2021 + +- Updated with names of new Safety Officers and specific information for the hackathon in October 2021. + +### v1.0 - March 15th, 2021 - Complete rewrite from original [Contributor Covenant](http://contributor-covenant.org/) CoC. diff --git a/README.md b/README.md index 10079c1..1db01e2 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,7 @@ # ![nf-core/molkart](docs/images/nf-core-molkart_logo_light.png#gh-light-mode-only) ![nf-core/molkart](docs/images/nf-core-molkart_logo_dark.png#gh-dark-mode-only) -[![AWS CI](https://img.shields.io/badge/CI%20tests-full%20size-FF9900?labelColor=000000&logo=Amazon%20AWS)](https://nf-co.re/molkart/results)[![Cite with Zenodo](http://img.shields.io/badge/DOI-10.5281/zenodo.XXXXXXX-1073c8?labelColor=000000)](https://doi.org/10.5281/zenodo.XXXXXXX) +[![GitHub Actions CI Status](https://github.com/nf-core/molkart/workflows/nf-core%20CI/badge.svg)](https://github.com/nf-core/molkart/actions?query=workflow%3A%22nf-core+CI%22) +[![GitHub Actions Linting Status](https://github.com/nf-core/molkart/workflows/nf-core%20linting/badge.svg)](https://github.com/nf-core/molkart/actions?query=workflow%3A%22nf-core+linting%22)[![AWS CI](https://img.shields.io/badge/CI%20tests-full%20size-FF9900?labelColor=000000&logo=Amazon%20AWS)](https://nf-co.re/molkart/results)[![Cite with Zenodo](http://img.shields.io/badge/DOI-10.5281/zenodo.XXXXXXX-1073c8?labelColor=000000)](https://doi.org/10.5281/zenodo.XXXXXXX) [![Nextflow](https://img.shields.io/badge/nextflow%20DSL2-%E2%89%A523.04.0-23aa62.svg)](https://www.nextflow.io/) [![run with conda](http://img.shields.io/badge/run%20with-conda-3EB049?labelColor=000000&logo=anaconda)](https://docs.conda.io/en/latest/) @@ -29,10 +30,11 @@ ## Usage -> **Note** -> If you are new to Nextflow and nf-core, please refer to [this page](https://nf-co.re/docs/usage/installation) on how -> to set-up Nextflow. Make sure to [test your setup](https://nf-co.re/docs/usage/introduction#how-to-run-a-pipeline) -> with `-profile test` before running the workflow on actual data. +:::note +If you are new to Nextflow and nf-core, please refer to [this page](https://nf-co.re/docs/usage/installation) on how +to set-up Nextflow. Make sure to [test your setup](https://nf-co.re/docs/usage/introduction#how-to-run-a-pipeline) +with `-profile test` before running the workflow on actual data. +::: - ## Pipeline overview The pipeline is built using [Nextflow](https://www.nextflow.io/) and processes data using the following steps: -- [FastQC](#fastqc) - Raw read QC -- [MultiQC](#multiqc) - Aggregate report describing results and QC from the whole pipeline -- [Pipeline information](#pipeline-information) - Report metrics generated during the workflow execution +- [Mindagap](#Mindagap) - Fill empty grid lines in a panorama image with neighbor-weighted values. +- [CLAHE](#CLAHE) - perform contrast-limited adaptive histogram equalization. +- [Create stacks](#Create_stacks) - If a second image is provided, combine both into one stack as input for segmentation modules. +- [segmentation](#segmentation) - Segment single cells from provided image using segmentation method of choice (Cellpose, Mesmer, ilastik). +- [Mindagap_duplicatefinder](#Mindagap) - Take a spot table and search for duplicates along grid lines. +- [Spot2cell](#spot2cell) - Assign non-duplicated spots to segmented cells based on segmentation mask and extract cell shape information. +- [molkartqc](#molkartqc) - Produce QC metrics specific to this pipeline. +- [MultiQC](#multiqc) - Aggregate report describing results and QC from the whole pipeline. +- [Pipeline information](#pipeline-information) - Report metrics generated during the workflow execution. + +### Mindagap + +
    +Output files + +- `mindagap/` + - `*_gridfilled.tiff`: Gridfilled panorama file(s). + - `*_markedDups.txt`: Spot table with duplicated spots marked as 'Duplicated'. + +
    + +[Mindagap](https://github.com/ViriatoII/MindaGap) fills empty grids of a panorama made from several tiles using the mean of the immediate neighborhood, as well as marking duplicated spots near the grid from the spot table. + +### CLAHE + +
    +Output files + +- `clahe/` + - `*.clahe.tiff`: Image with contrast-limited adaptive histogram equalization applied. + +
    + +[CLAHE](https://scikit-image.org/docs/stable/api/skimage.exposure.html#skimage.exposure.equalize_adapthist) is a algorithm from [scikit-image](https://scikit-image.org) for local contrast enhancement, that uses histograms computed over different tile regions of the image. Local details can therefore be enhanced even in regions that are darker or lighter than most of the image. -### FastQC +### Create_stacks
    Output files -- `fastqc/` - - `*_fastqc.html`: FastQC report containing quality metrics. - - `*_fastqc.zip`: Zip archive containing the FastQC report, tab-delimited data file and plot images. +- `stack/` + - `*.ome.tif`: Image containing provided input images as channels.
    -[FastQC](http://www.bioinformatics.babraham.ac.uk/projects/fastqc/) gives general quality metrics about your sequenced reads. It provides information about the quality score distribution across your reads, per base sequence content (%A/T/G/C), adapter contamination and overrepresented sequences. For further reading and documentation see the [FastQC help pages](http://www.bioinformatics.babraham.ac.uk/projects/fastqc/Help/). +Create stack is a local module used to merge images into a stack as preparation for segmentation processes. -![MultiQC - FastQC sequence counts plot](images/mqc_fastqc_counts.png) +### Segmentation -![MultiQC - FastQC mean quality scores plot](images/mqc_fastqc_quality.png) +
    +Output files + +- `segmentation/` + - `cellpose/` + - `*_cellpose_mask.tif`: Segmentation masks created by Cellpose. + - `ilastik/` + - `*_probability_maps.hdf5`: Probability maps created by ilastik's Pixel Classifier workflow. + - `*_ilastik_mask.tif`: Segmentation masks created by ilastik's Boundary prediction with Multicut workflow. + - `mesmer/`: + - `*_mesmer_mask.tif`: Segmentation masks created by Mesmer. + +
    -![MultiQC - FastQC adapter content plot](images/mqc_fastqc_adapter.png) +[Cellpose](https://www.cellpose.org) is a segmentation tool that provides pretrained models as well as additional human-in-the loop training. If additional training is performed, the envisioned way of doing it is creating the training subset (`tiff`), and training the model in the [Cellpose GUI](https://cellpose.readthedocs.io/en/latest/gui.html) on the subset, then giving the trained model as an argument within the pipeline to complete the pipeline run. + +[ilastik](https://www.ilastik.org) is an interactive learning and segmentation toolkit, with its application here envisioned as - create training subset (`hdf5`), create Pixel Classifier and Boundary prediction with Multicut projects with specified parameters. Within Molkart, the project files can be given and batch processing would be applied on the full images. + +[Mesmer](https://deepcell.readthedocs.io/en/master/API/deepcell.applications.html#mesmer) is a segmentation tool that provides pretrained models for whole-cell and nuclear segmentation. + +### Spot2cell + +
    +Output files + +- `spot2cell/` + - `*.cellxgene.csv`: Cell-by-transcript `csv` file containing transcript counts per cell, as well as cell shape properties. + +
    + +Spot2cell is a local module that assigns spots (without Duplicates) to cells via a spot table and segmentation mask. + +### MolkartQC + +
    +Output files + +- `molkartqc/` + - `*.spot_QC.csv`: ### Spot2cell + +
    +Output files + +- `molkartqc/` + - `*.cellxgene.csv`: Sheet containing useful quality-control metrics specific to spot-based image processing methods. + +
    -:::note -The FastQC plots displayed in the MultiQC report shows _untrimmed_ reads. They may contain adapter sequence and potentially regions with low quality. -::: +MolkartQC is a local module used for gathering useful quality-control metrics for spot-based image processing methods, including: sample ID, used segmentation method, total number of cells, average cell area, total number of spots, average spot assignment per cell, total number of assigned spots, percentage of assigned spots, number of duplicated spots. ### MultiQC @@ -62,7 +132,7 @@ Results generated by MultiQC collate pipeline QC from supported tools e.g. FastQ - `pipeline_info/` - Reports generated by Nextflow: `execution_report.html`, `execution_timeline.html`, `execution_trace.txt` and `pipeline_dag.dot`/`pipeline_dag.svg`. - - Reports generated by the pipeline: `pipeline_report.html`, `pipeline_report.txt` and `software_versions.yml`. The `pipeline_report*` files will only be present if the `--email` / `--email_on_fail` parameter's are used when running the pipeline. + - Reports generated by the pipeline: `pipeline_report.html`, `pipeline_report.txt` and `software_versions.yml`. The `pipeline_report*` files will only be present if the `--email` / `--email_on_fail` parameters are used when running the pipeline. - Reformatted samplesheet files used as input to the pipeline: `samplesheet.valid.csv`. - Parameters used by the pipeline run: `params.json`. diff --git a/modules.json b/modules.json index 4915732..e6d566d 100644 --- a/modules.json +++ b/modules.json @@ -7,37 +7,37 @@ "nf-core": { "cellpose": { "branch": "master", - "git_sha": "716ef3019b66772a817b417078edce2f7b337858", + "git_sha": "516189e968feb4ebdd9921806988b4c12b4ac2dc", "installed_by": ["modules"] }, "custom/dumpsoftwareversions": { "branch": "master", - "git_sha": "911696ea0b62df80e900ef244d7867d177971f73", + "git_sha": "fc6caedab1c71113aa440900e5989dd1c03ec58f", "installed_by": ["modules"] }, "deepcell/mesmer": { "branch": "master", - "git_sha": "bd8092b67b5103bdd52e300f75889442275c3117", + "git_sha": "516189e968feb4ebdd9921806988b4c12b4ac2dc", "installed_by": ["modules"] }, "ilastik/multicut": { "branch": "master", - "git_sha": "6f150e1503c0826c21fedf1fa566cdbecbe98ec7", + "git_sha": "516189e968feb4ebdd9921806988b4c12b4ac2dc", "installed_by": ["modules"] }, "ilastik/pixelclassification": { "branch": "master", - "git_sha": "6f150e1503c0826c21fedf1fa566cdbecbe98ec7", + "git_sha": "516189e968feb4ebdd9921806988b4c12b4ac2dc", "installed_by": ["modules"] }, "mindagap/mindagap": { "branch": "master", - "git_sha": "240937a2a9c30298110753292be041188891f2cb", + "git_sha": "8fc1d24c710ebe1d5de0f2447ec9439fd3d9d66a", "installed_by": ["modules"] }, "multiqc": { "branch": "master", - "git_sha": "911696ea0b62df80e900ef244d7867d177971f73", + "git_sha": "8fc1d24c710ebe1d5de0f2447ec9439fd3d9d66a", "installed_by": ["modules"] } } diff --git a/modules/nf-core/cellpose/environment.yml b/modules/nf-core/cellpose/environment.yml new file mode 100644 index 0000000..bcd3a8b --- /dev/null +++ b/modules/nf-core/cellpose/environment.yml @@ -0,0 +1,4 @@ +channels: + - conda-forge + - bioconda + - defaults diff --git a/modules/nf-core/cellpose/meta.yml b/modules/nf-core/cellpose/meta.yml index b452f57..647e1f9 100644 --- a/modules/nf-core/cellpose/meta.yml +++ b/modules/nf-core/cellpose/meta.yml @@ -12,7 +12,6 @@ tools: tool_dev_url: "https://github.com/MouseLand/cellpose" doi: 10.1038/s41592-022-01663-4 licence: "BSD 3-Clause" - input: - meta: type: map @@ -26,7 +25,6 @@ input: - model: type: file description: Optional input file. Cellpose 2 model trained by user using human-in-the-loop approach. - output: - meta: type: map @@ -41,6 +39,7 @@ output: type: file description: labelled mask output from cellpose in tif format pattern: "*.{tif, tiff}" - authors: - "@josenimo" +maintainers: + - "@josenimo" diff --git a/modules/nf-core/custom/dumpsoftwareversions/environment.yml b/modules/nf-core/custom/dumpsoftwareversions/environment.yml new file mode 100644 index 0000000..9d0e6b2 --- /dev/null +++ b/modules/nf-core/custom/dumpsoftwareversions/environment.yml @@ -0,0 +1,6 @@ +channels: + - conda-forge + - bioconda + - defaults +dependencies: + - bioconda::multiqc=1.17 diff --git a/modules/nf-core/custom/dumpsoftwareversions/main.nf b/modules/nf-core/custom/dumpsoftwareversions/main.nf index ebc8727..7685b33 100644 --- a/modules/nf-core/custom/dumpsoftwareversions/main.nf +++ b/modules/nf-core/custom/dumpsoftwareversions/main.nf @@ -2,10 +2,10 @@ process CUSTOM_DUMPSOFTWAREVERSIONS { label 'process_single' // Requires `pyyaml` which does not have a dedicated container but is in the MultiQC container - conda "bioconda::multiqc=1.14" + conda "${moduleDir}/environment.yml" container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? - 'https://depot.galaxyproject.org/singularity/multiqc:1.14--pyhdfd78af_0' : - 'biocontainers/multiqc:1.14--pyhdfd78af_0' }" + 'https://depot.galaxyproject.org/singularity/multiqc:1.17--pyhdfd78af_0' : + 'biocontainers/multiqc:1.17--pyhdfd78af_0' }" input: path versions diff --git a/modules/nf-core/custom/dumpsoftwareversions/meta.yml b/modules/nf-core/custom/dumpsoftwareversions/meta.yml index c32657d..9414c32 100644 --- a/modules/nf-core/custom/dumpsoftwareversions/meta.yml +++ b/modules/nf-core/custom/dumpsoftwareversions/meta.yml @@ -16,7 +16,6 @@ input: type: file description: YML file containing software versions pattern: "*.yml" - output: - yml: type: file @@ -30,7 +29,9 @@ output: type: file description: File containing software versions pattern: "versions.yml" - authors: - "@drpatelh" - "@grst" +maintainers: + - "@drpatelh" + - "@grst" diff --git a/modules/nf-core/custom/dumpsoftwareversions/templates/dumpsoftwareversions.py b/modules/nf-core/custom/dumpsoftwareversions/templates/dumpsoftwareversions.py index e55b8d4..da03340 100755 --- a/modules/nf-core/custom/dumpsoftwareversions/templates/dumpsoftwareversions.py +++ b/modules/nf-core/custom/dumpsoftwareversions/templates/dumpsoftwareversions.py @@ -4,11 +4,10 @@ """Provide functions to merge multiple versions.yml files.""" +import yaml import platform from textwrap import dedent -import yaml - def _make_versions_html(versions): """Generate a tabular HTML output of all versions for MultiQC.""" diff --git a/modules/nf-core/custom/dumpsoftwareversions/tests/main.nf.test b/modules/nf-core/custom/dumpsoftwareversions/tests/main.nf.test new file mode 100644 index 0000000..eec1db1 --- /dev/null +++ b/modules/nf-core/custom/dumpsoftwareversions/tests/main.nf.test @@ -0,0 +1,38 @@ +nextflow_process { + + name "Test Process CUSTOM_DUMPSOFTWAREVERSIONS" + script "../main.nf" + process "CUSTOM_DUMPSOFTWAREVERSIONS" + tag "modules" + tag "modules_nfcore" + tag "custom" + tag "dumpsoftwareversions" + tag "custom/dumpsoftwareversions" + + test("Should run without failures") { + when { + process { + """ + def tool1_version = ''' + TOOL1: + tool1: 0.11.9 + '''.stripIndent() + + def tool2_version = ''' + TOOL2: + tool2: 1.9 + '''.stripIndent() + + input[0] = Channel.of(tool1_version, tool2_version).collectFile() + """ + } + } + + then { + assertAll( + { assert process.success }, + { assert snapshot(process.out).match() } + ) + } + } +} diff --git a/modules/nf-core/custom/dumpsoftwareversions/tests/main.nf.test.snap b/modules/nf-core/custom/dumpsoftwareversions/tests/main.nf.test.snap new file mode 100644 index 0000000..4274ed5 --- /dev/null +++ b/modules/nf-core/custom/dumpsoftwareversions/tests/main.nf.test.snap @@ -0,0 +1,27 @@ +{ + "Should run without failures": { + "content": [ + { + "0": [ + "software_versions.yml:md5,1c851188476409cda5752ce971b20b58" + ], + "1": [ + "software_versions_mqc.yml:md5,2570f4ba271ad08357b0d3d32a9cf84d" + ], + "2": [ + "versions.yml:md5,3843ac526e762117eedf8825b40683df" + ], + "mqc_yml": [ + "software_versions_mqc.yml:md5,2570f4ba271ad08357b0d3d32a9cf84d" + ], + "versions": [ + "versions.yml:md5,3843ac526e762117eedf8825b40683df" + ], + "yml": [ + "software_versions.yml:md5,1c851188476409cda5752ce971b20b58" + ] + } + ], + "timestamp": "2023-11-03T14:43:22.157011" + } +} diff --git a/modules/nf-core/custom/dumpsoftwareversions/tests/tags.yml b/modules/nf-core/custom/dumpsoftwareversions/tests/tags.yml new file mode 100644 index 0000000..405aa24 --- /dev/null +++ b/modules/nf-core/custom/dumpsoftwareversions/tests/tags.yml @@ -0,0 +1,2 @@ +custom/dumpsoftwareversions: + - modules/nf-core/custom/dumpsoftwareversions/** diff --git a/modules/nf-core/deepcell/mesmer/environment.yml b/modules/nf-core/deepcell/mesmer/environment.yml new file mode 100644 index 0000000..bcd3a8b --- /dev/null +++ b/modules/nf-core/deepcell/mesmer/environment.yml @@ -0,0 +1,4 @@ +channels: + - conda-forge + - bioconda + - defaults diff --git a/modules/nf-core/deepcell/mesmer/meta.yml b/modules/nf-core/deepcell/mesmer/meta.yml index 49fd391..729b7ad 100644 --- a/modules/nf-core/deepcell/mesmer/meta.yml +++ b/modules/nf-core/deepcell/mesmer/meta.yml @@ -12,7 +12,6 @@ tools: tool_dev_url: "https://githu/b.com/vanvalenlab/deepcell-tf" doi: 10.1038/s41587-021-01094-0 licence: "APACHE2" - input: # Only when we have meta - meta: @@ -25,7 +24,6 @@ input: type: file description: Multichannel image file pattern: "*.{tiff,tif,h5,hdf5}" - output: #Only when we have meta - meta: @@ -38,12 +36,13 @@ output: type: file description: File containing software versions pattern: "versions.yml" - - mask: type: file description: File containing the mask. pattern: "*.{tif, tiff}" - authors: - "@migueLib" - "@chiarasch" +maintainers: + - "@migueLib" + - "@chiarasch" diff --git a/modules/nf-core/ilastik/multicut/environment.yml b/modules/nf-core/ilastik/multicut/environment.yml new file mode 100644 index 0000000..bcd3a8b --- /dev/null +++ b/modules/nf-core/ilastik/multicut/environment.yml @@ -0,0 +1,4 @@ +channels: + - conda-forge + - bioconda + - defaults diff --git a/modules/nf-core/ilastik/multicut/meta.yml b/modules/nf-core/ilastik/multicut/meta.yml index 39493df..cb2af37 100644 --- a/modules/nf-core/ilastik/multicut/meta.yml +++ b/modules/nf-core/ilastik/multicut/meta.yml @@ -1,5 +1,4 @@ name: "ilastik_multicut" - description: Ilastik is a tool that utilizes machine learning algorithms to classify pixels, segment, track and count cells in images. Ilastik contains a graphical user interface to interactively label pixels. However, this nextflow module will implement the --headless mode, to apply pixel classification using a pre-trained .ilp file on an input image. keywords: - multicut @@ -12,7 +11,6 @@ tools: documentation: "https://www.ilastik.org/documentation/" tool_dev_url: "https://github.com/ilastik/ilastik" licence: "GPL3" - input: - meta: type: map @@ -23,7 +21,6 @@ input: type: file description: h5 file containing image stack to classify file pattern: "*.{h5,hdf5}" - - meta2: type: map description: | @@ -33,7 +30,6 @@ input: type: file description: Trained ilastik .ilp project file pattern: "*.{ilp}" - - meta3: type: map description: | @@ -43,7 +39,6 @@ input: type: file description: Probability map for boundary based segmentation pattern: "*.{h5,,hdf5}" - output: - meta: type: map @@ -54,11 +49,11 @@ output: type: file description: File containing software versions pattern: "versions.yml" - - out_tiff: type: file description: Multicut segmentation mask output. pattern: "*.{tiff}" - authors: - "@FloWuenne" +maintainers: + - "@FloWuenne" diff --git a/modules/nf-core/ilastik/pixelclassification/environment.yml b/modules/nf-core/ilastik/pixelclassification/environment.yml new file mode 100644 index 0000000..bcd3a8b --- /dev/null +++ b/modules/nf-core/ilastik/pixelclassification/environment.yml @@ -0,0 +1,4 @@ +channels: + - conda-forge + - bioconda + - defaults diff --git a/modules/nf-core/ilastik/pixelclassification/meta.yml b/modules/nf-core/ilastik/pixelclassification/meta.yml index 017ea84..6a9e8ba 100644 --- a/modules/nf-core/ilastik/pixelclassification/meta.yml +++ b/modules/nf-core/ilastik/pixelclassification/meta.yml @@ -1,5 +1,4 @@ name: "ilastik_pixelclassification" - description: Ilastik is a tool that utilizes machine learning algorithms to classify pixels, segment, track and count cells in images. Ilastik contains a graphical user interface to interactively label pixels. However, this nextflow module will implement the --headless mode, to apply pixel classification using a pre-trained .ilp file on an input image. keywords: - pixel_classification @@ -12,44 +11,38 @@ tools: documentation: "https://www.ilastik.org/documentation/" tool_dev_url: "https://github.com/ilastik/ilastik" licence: "GPL3" - input: - meta: type: map description: | Groovy Map containing sample information for h5 file e.g. [ id:'test', single_end:false ] - - input_img: type: file description: Input img file containing image stack to classify - - meta2: type: map description: | Groovy Map containing sample information for ilp file e.g. [ id:'test', single_end:false ] - - ilp: type: file description: Trained ilastik pixel classification .ilp project file pattern: "*.{ilp}" - output: - meta: type: map description: | Groovy Map containing sample information e.g. [ id:'test', single_end:false ] - - versions: type: file description: File containing software versions pattern: "versions.yml" - - output: type: file description: Output file from ilastik pixel classification. - authors: - "@FloWuenne" +maintainers: + - "@FloWuenne" diff --git a/modules/nf-core/mindagap/mindagap/environment.yml b/modules/nf-core/mindagap/mindagap/environment.yml new file mode 100644 index 0000000..8476017 --- /dev/null +++ b/modules/nf-core/mindagap/mindagap/environment.yml @@ -0,0 +1,6 @@ +channels: + - conda-forge + - bioconda + - defaults +dependencies: + - bioconda::mindagap=0.0.2 diff --git a/modules/nf-core/mindagap/mindagap/main.nf b/modules/nf-core/mindagap/mindagap/main.nf index 8d339ba..5d59a66 100644 --- a/modules/nf-core/mindagap/mindagap/main.nf +++ b/modules/nf-core/mindagap/mindagap/main.nf @@ -2,7 +2,7 @@ process MINDAGAP_MINDAGAP { tag "$meta.id" label 'process_low' - conda "bioconda::mindagap=0.0.2" + conda "${moduleDir}/environment.yml" container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? 'https://depot.galaxyproject.org/singularity/mindagap:0.0.2--pyhdfd78af_0' : 'biocontainers/mindagap:0.0.2--pyhdfd78af_0' }" diff --git a/modules/nf-core/mindagap/mindagap/meta.yml b/modules/nf-core/mindagap/mindagap/meta.yml index 022886a..5bd562a 100644 --- a/modules/nf-core/mindagap/mindagap/meta.yml +++ b/modules/nf-core/mindagap/mindagap/meta.yml @@ -11,7 +11,6 @@ tools: documentation: "https://github.com/ViriatoII/MindaGap/blob/main/README.md" tool_dev_url: "https://github.com/ViriatoII/MindaGap" licence: "BSD-3-Clause license" - input: - meta: type: map @@ -28,24 +27,23 @@ input: - loopnum: type: integer description: The number of times gaussian blur is run consecutively on the gridlines. A smaller number is faster, but the result is less good. - output: - meta: type: map description: | Groovy Map containing sample information e.g. [ id:'test', single_end:false ] - - versions: type: file description: File containing software versions pattern: "versions.yml" - - tiff: type: file description: A tiff file with gridlines filled based on consecutive gaussian blurring. pattern: "*.{tiff}" - authors: - "@ViriatoII" - "@flowuenne" +maintainers: + - "@ViriatoII" + - "@flowuenne" diff --git a/modules/nf-core/multiqc/environment.yml b/modules/nf-core/multiqc/environment.yml new file mode 100644 index 0000000..9d0e6b2 --- /dev/null +++ b/modules/nf-core/multiqc/environment.yml @@ -0,0 +1,6 @@ +channels: + - conda-forge + - bioconda + - defaults +dependencies: + - bioconda::multiqc=1.17 diff --git a/modules/nf-core/multiqc/main.nf b/modules/nf-core/multiqc/main.nf index 1fc387b..2bbc398 100644 --- a/modules/nf-core/multiqc/main.nf +++ b/modules/nf-core/multiqc/main.nf @@ -1,10 +1,10 @@ process MULTIQC { label 'process_single' - conda "bioconda::multiqc=1.14" + conda "${moduleDir}/environment.yml" container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? - 'https://depot.galaxyproject.org/singularity/multiqc:1.14--pyhdfd78af_0' : - 'biocontainers/multiqc:1.14--pyhdfd78af_0' }" + 'https://depot.galaxyproject.org/singularity/multiqc:1.17--pyhdfd78af_0' : + 'biocontainers/multiqc:1.17--pyhdfd78af_0' }" input: path multiqc_files, stageAs: "?/*" diff --git a/modules/nf-core/multiqc/meta.yml b/modules/nf-core/multiqc/meta.yml index f93b5ee..a61223e 100644 --- a/modules/nf-core/multiqc/meta.yml +++ b/modules/nf-core/multiqc/meta.yml @@ -13,7 +13,6 @@ tools: homepage: https://multiqc.info/ documentation: https://multiqc.info/docs/ licence: ["GPL-3.0-or-later"] - input: - multiqc_files: type: file @@ -31,7 +30,6 @@ input: type: file description: Optional logo file for MultiQC pattern: "*.{png}" - output: - report: type: file @@ -54,3 +52,8 @@ authors: - "@bunop" - "@drpatelh" - "@jfy133" +maintainers: + - "@abhi18av" + - "@bunop" + - "@drpatelh" + - "@jfy133" From 3b138c6b2187b7029528f2067dcaffc61218ee15 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Fri, 10 Nov 2023 14:38:03 +0000 Subject: [PATCH 048/149] removed fastqc plots as they are not releveant for this pipeline --- docs/images/mqc_fastqc_adapter.png | Bin 23458 -> 0 bytes docs/images/mqc_fastqc_counts.png | Bin 33918 -> 0 bytes docs/images/mqc_fastqc_quality.png | Bin 55769 -> 0 bytes 3 files changed, 0 insertions(+), 0 deletions(-) delete mode 100755 docs/images/mqc_fastqc_adapter.png delete mode 100755 docs/images/mqc_fastqc_counts.png delete mode 100755 docs/images/mqc_fastqc_quality.png diff --git a/docs/images/mqc_fastqc_adapter.png b/docs/images/mqc_fastqc_adapter.png deleted file mode 100755 index 361d0e47acfb424dea1f326590d1eb2f6dfa26b5..0000000000000000000000000000000000000000 GIT binary patch literal 0 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zXwhtT%ei{n#FzEH|C;yZ>+$!u_x#*+`=L8{b9SH^9&27u3G_Gxqxe`L2UJtdxghk z&-wzDFvLvW{chK5u3{n6GSKKy!P&C6w^IFpbD0bcp^A{{2lcLh_DXj@ybtYvc^;(2 M)78&qol`;+0Fu7JivR!s From b7971d68d499399cd157d247a987a2b79aacfd2b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Fri, 10 Nov 2023 15:02:10 +0000 Subject: [PATCH 049/149] Specified usage --- docs/usage.md | 52 +++++++++++++++++++-------------------------------- 1 file changed, 19 insertions(+), 33 deletions(-) diff --git a/docs/usage.md b/docs/usage.md index f4a48c0..0af5a34 100644 --- a/docs/usage.md +++ b/docs/usage.md @@ -10,45 +10,32 @@ ## Samplesheet input -You will need to create a samplesheet with information about the samples you would like to analyse before running the pipeline. Use this parameter to specify its location. It has to be a comma-separated file with 3 columns, and a header row as shown in the examples below. +You will need to create a samplesheet with information about the samples you would like to analyse before running the pipeline. Use this parameter to specify its location. It has to be a comma-separated file with 3 columns (4th column optional), and a header row as shown in the examples below. ```bash --input '[path to samplesheet file]' ``` -### Multiple runs of the same sample - -The `sample` identifiers have to be the same when you have re-sequenced the same sample more than once e.g. to increase sequencing depth. The pipeline will concatenate the raw reads before performing any downstream analysis. Below is an example for the same sample sequenced across 3 lanes: - -```console -sample,fastq_1,fastq_2 -CONTROL_REP1,AEG588A1_S1_L002_R1_001.fastq.gz,AEG588A1_S1_L002_R2_001.fastq.gz -CONTROL_REP1,AEG588A1_S1_L003_R1_001.fastq.gz,AEG588A1_S1_L003_R2_001.fastq.gz -CONTROL_REP1,AEG588A1_S1_L004_R1_001.fastq.gz,AEG588A1_S1_L004_R2_001.fastq.gz -``` - ### Full samplesheet -The pipeline will auto-detect whether a sample is single- or paired-end using the information provided in the samplesheet. The samplesheet can have as many columns as you desire, however, there is a strict requirement for the first 3 columns to match those defined in the table below. +The pipeline requires that the first column specifies the sample ID. If multiple rows are provided, their sample tags must be different. The samplesheet needs to have the three column names exactly as specified below, with the optional fourth column specifying the `membrane_image` (it does not have to be a membrane image necessarily, but the second image can be provided here to help with segmentation). -A final samplesheet file consisting of both single- and paired-end data may look something like the one below. This is for 6 samples, where `TREATMENT_REP3` has been sequenced twice. +A final samplesheet file that can be used to process a full dataset (after segmentation optimization), where a matching membrane image is provided would look like: ```console -sample,fastq_1,fastq_2 -CONTROL_REP1,AEG588A1_S1_L002_R1_001.fastq.gz,AEG588A1_S1_L002_R2_001.fastq.gz -CONTROL_REP2,AEG588A2_S2_L002_R1_001.fastq.gz,AEG588A2_S2_L002_R2_001.fastq.gz -CONTROL_REP3,AEG588A3_S3_L002_R1_001.fastq.gz,AEG588A3_S3_L002_R2_001.fastq.gz -TREATMENT_REP1,AEG588A4_S4_L003_R1_001.fastq.gz, -TREATMENT_REP2,AEG588A5_S5_L003_R1_001.fastq.gz, -TREATMENT_REP3,AEG588A6_S6_L003_R1_001.fastq.gz, -TREATMENT_REP3,AEG588A6_S6_L004_R1_001.fastq.gz, +sample,nuclear_image,spot_table,membrane_image +SAMPLE1,SAMPLE1.DAPI.tiff,SAMPLE1.spots.txt,SAMPLE1.WGA.tiff +SAMPLE2,SAMPLE2.DAPI.tiff,SAMPLE2.spots.txt,SAMPLE2.WGA.tiff +SAMPLE3,SAMPLE3.DAPI.tiff,SAMPLE3.spots.txt,SAMPLE3.WGA.tiff +SAMPLE4,SAMPLE4.DAPI.tiff,SAMPLE4.spots.txt,SAMPLE4.WGA.tiff ``` -| Column | Description | -| --------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| `sample` | Custom sample name. This entry will be identical for multiple sequencing libraries/runs from the same sample. Spaces in sample names are automatically converted to underscores (`_`). | -| `fastq_1` | Full path to FastQ file for Illumina short reads 1. File has to be gzipped and have the extension ".fastq.gz" or ".fq.gz". | -| `fastq_2` | Full path to FastQ file for Illumina short reads 2. File has to be gzipped and have the extension ".fastq.gz" or ".fq.gz". | +| Column | Description | +| ---------------- | ------------------------------------------------------------------------------------------------------------------------- | +| `sample` | Custom sample name. If multiple images are being processed, their sample tags must be different. Must not contain spaces. | +| `nuclear_image` | Full path to nuclear image (DAPI, Hoechst). | +| `spot_table` | Full path to tsv or txt spot table provided by Resolve. | +| `membrane_image` | Full path to membrane image (e.g WGA) or second channel to help with segmentation (optional). | An [example samplesheet](../assets/samplesheet.csv) has been provided with the pipeline. @@ -57,7 +44,7 @@ An [example samplesheet](../assets/samplesheet.csv) has been provided with the p The typical command for running the pipeline is as follows: ```bash -nextflow run nf-core/molkart --input ./samplesheet.csv --outdir ./results --genome GRCh37 -profile docker +nextflow run nf-core/molkart --input ./samplesheet.csv --outdir ./results -profile docker ``` This will launch the pipeline with the `docker` configuration profile. See below for more information about profiles. @@ -90,7 +77,6 @@ with `params.yaml` containing: ```yaml input: './samplesheet.csv' outdir: './results/' -genome: 'GRCh37' <...> ``` @@ -112,7 +98,7 @@ First, go to the [nf-core/molkart releases page](https://github.com/nf-core/molk This version number will be logged in reports when you run the pipeline, so that you'll know what you used when you look back in the future. For example, at the bottom of the MultiQC reports. -To further assist in reproducbility, you can use share and re-use [parameter files](#running-the-pipeline) to repeat pipeline runs with the same settings without having to write out a command with every single parameter. +To further assist in reproducibility, you can use share and re-use [parameter files](#running-the-pipeline) to repeat pipeline runs with the same settings without having to write out a command with every single parameter. :::tip If you wish to share such profile (such as upload as supplementary material for academic publications), make sure to NOT include cluster specific paths to files, nor institutional specific profiles. @@ -131,7 +117,7 @@ Use this parameter to choose a configuration profile. Profiles can give configur Several generic profiles are bundled with the pipeline which instruct the pipeline to use software packaged using different methods (Docker, Singularity, Podman, Shifter, Charliecloud, Apptainer, Conda) - see below. :::info -We highly recommend the use of Docker or Singularity containers for full pipeline reproducibility, however when this is not possible, Conda is also supported. +We highly recommend the use of Docker or Singularity containers for full pipeline reproducibility -- currently, Conda is not supported for this pipeline. ::: The pipeline also dynamically loads configurations from [https://github.com/nf-core/configs](https://github.com/nf-core/configs) when it runs, making multiple config profiles for various institutional clusters available at run time. For more information and to see if your system is available in these configs please see the [nf-core/configs documentation](https://github.com/nf-core/configs#documentation). @@ -139,7 +125,7 @@ The pipeline also dynamically loads configurations from [https://github.com/nf-c Note that multiple profiles can be loaded, for example: `-profile test,docker` - the order of arguments is important! They are loaded in sequence, so later profiles can overwrite earlier profiles. -If `-profile` is not specified, the pipeline will run locally and expect all software to be installed and available on the `PATH`. This is _not_ recommended, since it can lead to different results on different machines dependent on the computer enviroment. +If `-profile` is not specified, the pipeline will run locally and expect all software to be installed and available on the `PATH`. This is _not_ recommended, since it can lead to different results on different machines dependent on the computer environment. - `test` - A profile with a complete configuration for automated testing @@ -157,7 +143,7 @@ If `-profile` is not specified, the pipeline will run locally and expect all sof - `apptainer` - A generic configuration profile to be used with [Apptainer](https://apptainer.org/) - `conda` - - A generic configuration profile to be used with [Conda](https://conda.io/docs/). Please only use Conda as a last resort i.e. when it's not possible to run the pipeline with Docker, Singularity, Podman, Shifter, Charliecloud, or Apptainer. + - A generic configuration profile to be used with [Conda](https://conda.io/docs/). Please only use Conda as a last resort i.e. when it's not possible to run the pipeline with Docker, Singularity, Podman, Shifter, Charliecloud, or Apptainer. Currently not supported. ### `-resume` From d8068fb64b1206a2ed317af4d32b2667eee835de Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Fri, 10 Nov 2023 15:04:19 +0000 Subject: [PATCH 050/149] Updated usage --- docs/usage.md | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/docs/usage.md b/docs/usage.md index 0af5a34..ddd0acb 100644 --- a/docs/usage.md +++ b/docs/usage.md @@ -6,8 +6,6 @@ ## Introduction - - ## Samplesheet input You will need to create a samplesheet with information about the samples you would like to analyse before running the pipeline. Use this parameter to specify its location. It has to be a comma-separated file with 3 columns (4th column optional), and a header row as shown in the examples below. @@ -41,7 +39,7 @@ An [example samplesheet](../assets/samplesheet.csv) has been provided with the p ## Running the pipeline -The typical command for running the pipeline is as follows: +The typical command for running the pipeline with default values is as follows: ```bash nextflow run nf-core/molkart --input ./samplesheet.csv --outdir ./results -profile docker From 0635f33ab9bf6bd1b9d92d584076550aaddd7beb Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Fri, 10 Nov 2023 15:50:48 +0000 Subject: [PATCH 051/149] Updated changelog, added segmentation overhead folder --- CHANGELOG.md | 12 ++++++++++++ conf/modules.config | 8 ++++---- docs/output.md | 21 ++++++++++++++++++++- docs/usage.md | 12 ++++++++++++ 4 files changed, 48 insertions(+), 5 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 79527d7..9d6101c 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -3,6 +3,18 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/) and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html). +## v1.0.1dev - [2023.10.11] + +Added documentation - usage.md and output.md + +### `Added` + +- usage.md documentation +- output.md documentation +- segmentation outputs are all moved to a segmentation folder. +- updated nf-core module versions +- + ## v1.0.1dev - [2023.25.10] Implemented the tilesize parameter for Mindagap_mindagap and mindagap_duplicatefinder so that smaller representative images can be used as test. diff --git a/conf/modules.config b/conf/modules.config index fe79db4..bdfa4d0 100644 --- a/conf/modules.config +++ b/conf/modules.config @@ -75,7 +75,7 @@ process { withName: "ILASTIK_PIXELCLASSIFICATION" { publishDir = [ - path: { "${params.outdir}/ilastik" }, + path: { "${params.outdir}/segmentation/ilastik" }, pattern: "*.{h5}", saveAs: { filename -> "${meta.id}_probability_$filename" } ] @@ -83,7 +83,7 @@ process { withName: "ILASTIK_MULTICUT" { publishDir = [ - path: { "${params.outdir}/ilastik" }, + path: { "${params.outdir}/segmentation/ilastik" }, pattern: "*.tiff", saveAs: { filename -> "${meta.id}_ilastik_$filename" } ] @@ -126,7 +126,7 @@ process { ].join(" ").trim() containerOptions = '--entrypoint ""' publishDir = [ - path: "${params.outdir}/mesmer", + path: "${params.outdir}/segmentation/mesmer", pattern: "*.tif", saveAs: { filename -> "${meta.id}_mesmer_$filename" } ] @@ -149,7 +149,7 @@ process { ].join(" ").trim() containerOptions = '--entrypoint ""' publishDir = [ - path: "${params.outdir}/cellpose", + path: "${params.outdir}/segmentation/cellpose", pattern: "*_cp_masks.tif", saveAs: { filename -> "${meta.id}_cellpose_mask.tif" } ] diff --git a/docs/output.md b/docs/output.md index 6a2c170..7c8d592 100644 --- a/docs/output.md +++ b/docs/output.md @@ -12,7 +12,7 @@ The pipeline is built using [Nextflow](https://www.nextflow.io/) and processes d - [Mindagap](#Mindagap) - Fill empty grid lines in a panorama image with neighbor-weighted values. - [CLAHE](#CLAHE) - perform contrast-limited adaptive histogram equalization. -- [Create stacks](#Create_stacks) - If a second image is provided, combine both into one stack as input for segmentation modules. +- [Create stacks](#create_stacks) - If a second image is provided, combine both into one stack as input for segmentation modules. - [segmentation](#segmentation) - Segment single cells from provided image using segmentation method of choice (Cellpose, Mesmer, ilastik). - [Mindagap_duplicatefinder](#Mindagap) - Take a spot table and search for duplicates along grid lines. - [Spot2cell](#spot2cell) - Assign non-duplicated spots to segmented cells based on segmentation mask and extract cell shape information. @@ -20,6 +20,8 @@ The pipeline is built using [Nextflow](https://www.nextflow.io/) and processes d - [MultiQC](#multiqc) - Aggregate report describing results and QC from the whole pipeline. - [Pipeline information](#pipeline-information) - Report metrics generated during the workflow execution. +- [Create training subset](#create-training-subset) - creates crops for segmentation training (Cellpose, ilastik). + ### Mindagap
    @@ -136,6 +138,23 @@ Results generated by MultiQC collate pipeline QC from supported tools e.g. FastQ - Reformatted samplesheet files used as input to the pipeline: `samplesheet.valid.csv`. - Parameters used by the pipeline run: `params.json`. +### create-training-subset + +
    +Output files + +- `training_subset/` + - `hdf5/` + - `*_crop[0-9]+.hdf5`: `hdf5` crops for training Pixel classification and Multicut models with ilastik for segmentation. + - `*CropSummary.txt`: Summary of the created crops - used by tiff crops and for overview creation. + - `tiff/` + - `*_crop[0-9]+.tiff`: `tiff` crops for training Cellpose to create a custom segmentation model. + - `*.crop_overview.png`: Crop overview for visual assessment of crop placement on the whole sample. + +
    + +Spot2cell is a local module that assigns spots (without Duplicates) to cells via a spot table and segmentation mask. +
    [Nextflow](https://www.nextflow.io/docs/latest/tracing.html) provides excellent functionality for generating various reports relevant to the running and execution of the pipeline. This will allow you to troubleshoot errors with the running of the pipeline, and also provide you with other information such as launch commands, run times and resource usage. diff --git a/docs/usage.md b/docs/usage.md index ddd0acb..c11c992 100644 --- a/docs/usage.md +++ b/docs/usage.md @@ -80,6 +80,18 @@ outdir: './results/' You can also generate such `YAML`/`JSON` files via [nf-core/launch](https://nf-co.re/launch). +To run the pipeline so that the training subset is created with default values, run: + +```bash +nextflow run nf-core/molkart --input ./samplesheet.csv --outdir ./results -profile docker --create_training_subset +``` + +After training a Cellpose 2.0 model, or creating ilastik Pixel Classification and Multicut projects, make sure you match the parameters (e.g cell diameter, flow threshold) in the run to your training and continue the default pipeline run with: + +```bash +nextflow run nf-core/molkart --input ./samplesheet.csv --outdir ./results -profile docker --segmentation_method cellpose,ilastik --cellpose_custom_model /path/to/model --ilastik_pixel_project /path/to/pixel_classifier.ilp --ilastik_multicut_project /path/to/multicut.ilp +``` + ### Updating the pipeline When you run the above command, Nextflow automatically pulls the pipeline code from GitHub and stores it as a cached version. When running the pipeline after this, it will always use the cached version if available - even if the pipeline has been updated since. To make sure that you're running the latest version of the pipeline, make sure that you regularly update the cached version of the pipeline: From 28dbee7ab45fe24a9afb3cdcc695dcfb4bc62493 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Fri, 10 Nov 2023 16:10:19 +0000 Subject: [PATCH 052/149] Added optional params to documentation --- docs/usage.md | 36 +++++++++++++++++++++++++++++++++--- 1 file changed, 33 insertions(+), 3 deletions(-) diff --git a/docs/usage.md b/docs/usage.md index c11c992..2a6111e 100644 --- a/docs/usage.md +++ b/docs/usage.md @@ -73,9 +73,39 @@ nextflow run nf-core/molkart -profile docker -params-file params.yaml with `params.yaml` containing: ```yaml -input: './samplesheet.csv' -outdir: './results/' -<...> +input: "./samplesheet.csv" +outdir: "./results/" +``` + +Additionally, `params.yaml` can contain optional parameters: + +```yaml +input: "./samplesheet.csv" +outdir: "./results/" +segmentation_method: "mesmer" +cellpose_save_flows: false +cellpose_diameter: 30 +cellpose_chan: 0 +cellpose_chan2: null +cellpose_pretrained_model: "cyto" +cellpose_custom_model: null +cellpose_flow_threshold: 0.4 +cellpose_edge_exclude: true +mesmer_image_mpp: 0.138 +mesmer_compartment: "whole-cell" +ilastik_pixel_project: null +ilastik_multicut_project: null +tilesize: 2144 +skip_clahe: false +clahe_cliplimit: 0.01 +clahe_nbins: 256 +clahe_pixel_size: 0.138 +clahe_kernel: 25 +create_training_subset: false +crop_amount: 4 +crop_nonzero_fraction: 0.4 +crop_size_x: 400 +crop_size_y: 400 ``` You can also generate such `YAML`/`JSON` files via [nf-core/launch](https://nf-co.re/launch). From 4ab90b6ae7aa5bfebb4d60ce827b1ad906e4f98f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Mon, 13 Nov 2023 17:05:46 +0000 Subject: [PATCH 053/149] Updated CHANGELOG, README, CITATIONS --- CHANGELOG.md | 4 +++- CITATIONS.md | 17 +++++++++++-- README.md | 49 ++++++++++++++++++-------------------- lib/WorkflowMolkart.groovy | 17 +++++++------ 4 files changed, 51 insertions(+), 36 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 9d6101c..aff56ec 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -13,7 +13,9 @@ Added documentation - usage.md and output.md - output.md documentation - segmentation outputs are all moved to a segmentation folder. - updated nf-core module versions -- +- CITATIONS.md updated +- README.md updated +- WorkflowMolkart.groovy updated to return citations if tools are used ## v1.0.1dev - [2023.25.10] diff --git a/CITATIONS.md b/CITATIONS.md index 0f74f5d..6b93761 100644 --- a/CITATIONS.md +++ b/CITATIONS.md @@ -10,9 +10,22 @@ ## Pipeline tools -- [FastQC](https://www.bioinformatics.babraham.ac.uk/projects/fastqc/) +- [Cellpose](https://www.cellpose.org/) - > Andrews, S. (2010). FastQC: A Quality Control Tool for High Throughput Sequence Data [Online]. + > Stringer, C., Wang, T., Michaelos, M. et al. Cellpose: a generalist algorithm for cellular segmentation. Nat Methods 18, 100–106 (2021). https://doi.org/10.1038/s41592-020-01018-x + > Pachitariu, M., Stringer, C. Cellpose 2.0: how to train your own model. Nat Methods 19, 1634–1641 (2022). https://doi.org/10.1038/s41592-022-01663-4 + +- [ilastik](https://www.ilastik.org/) + +> Berg, S., Kutra, D., Kroeger, T. et al. ilastik: interactive machine learning for (bio)image analysis. Nat Methods 16, 1226–1232 (2019). https://doi.org/10.1038/s41592-019-0582-9 + +- [Mesmer](https://deepcell.readthedocs.io/en/master/API/deepcell.applications.html) + +> Greenwald NF, Miller G, Moen E, Kong A, Kagel A, Dougherty T, Fullaway CC, McIntosh BJ, Leow KX, Schwartz MS, Pavelchek C, Cui S, Camplisson I, Bar-Tal O, Singh J, Fong M, Chaudhry G, Abraham Z, Moseley J, Warshawsky S, Soon E, Greenbaum S, Risom T, Hollmann T, Bendall SC, Keren L, Graf W, Angelo M, Van Valen D. Whole-cell segmentation of tissue images with human-level performance using large-scale data annotation and deep learning. Nat Biotechnol. 2022 Apr;40(4):555-565. doi: 10.1038/s41587-021-01094-0. Epub 2021 Nov 18. PMID: 34795433; PMCID: PMC9010346. + +- [Mindagap](https://github.com/ViriatoII/MindaGap) + + > Ricardo Guerreiro, Florian Wuennemann, & pvtodorov. (2023). ViriatoII/MindaGap: v0.0.3 (0.0.3). Zenodo. https://doi.org/10.5281/zenodo.8120559 - [MultiQC](https://pubmed.ncbi.nlm.nih.gov/27312411/) diff --git a/README.md b/README.md index 5d3eb60..46db397 100644 --- a/README.md +++ b/README.md @@ -11,20 +11,28 @@ [![Get help on Slack](http://img.shields.io/badge/slack-nf--core%20%23molkart-4A154B?labelColor=000000&logo=slack)](https://nfcore.slack.com/channels/molkart)[![Follow on Twitter](http://img.shields.io/badge/twitter-%40nf__core-1DA1F2?labelColor=000000&logo=twitter)](https://twitter.com/nf_core)[![Follow on Mastodon](https://img.shields.io/badge/mastodon-nf__core-6364ff?labelColor=FFFFFF&logo=mastodon)](https://mstdn.science/@nf_core)[![Watch on YouTube](http://img.shields.io/badge/youtube-nf--core-FF0000?labelColor=000000&logo=youtube)](https://www.youtube.com/c/nf-core) -## Important note - -This pipeline is under active development and does not work at this point. If you want to process your Resolve Bioscience data in the meantime, please go to https://github.com/FloWuenne/nf-MolKart, where you can find a working nextflow pipeline, outside the nf-core ecosystem. In the coming weeks, nf-MolKart will be completely transitioned into nf-core/molkart for future use. - ## Introduction -**nf-core/molkart** is a pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH). It takes as input a table of FISH spot positions (x,y,z,gene), a corresponding DAPI image (tiff format) and optionally a membrane staining image in tiff format. nf-core/molkart performs end-to-end processing of the data including image processing, QC filtering of spots, cell segmentation, spot to cell assignment and reports quality metrics such as the spot assignment rate, average spots per cell and segmentation mask size ranges. +**nf-core/molkart** is a pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH). It takes as input a table of FISH spot positions (x,y,z,gene), a corresponding DAPI image (`tiff` format) and optionally a membrane staining image in the `tiff` format. nf-core/molkart performs end-to-end processing of the data including image processing, QC filtering of spots, cell segmentation, spot-to-cell assignment and reports quality metrics such as the spot assignment rate, average spots per cell and segmentation mask size ranges. - - + +

    + +

    -1. Read QC ([`FastQC`](https://www.bioinformatics.babraham.ac.uk/projects/fastqc/)) -2. Present QC for raw reads ([`MultiQC`](http://multiqc.info/)) +Image preprocessing + +- Fill the grid pattern in provided images ([`Mindagap`](https://github.com/ViriatoII/MindaGap)) +- Optionally apply contrast-limited adaptive histogram equalization +- If a second (membrane) image is present, combine images into a multichannel stack + Cell segmentation +- Apply cell segmentation based on provided images, available options are: - [`Cellpose`](https://www.cellpose.org/) - [`Mesmer `](https://deepcell.readthedocs.io/en/master/API/deepcell.applications.html#mesmer) - [`ilastik`](https://www.ilastik.org/) + Spot processing +- Find duplicated spots near grid lines ([`Mindagap`](https://github.com/ViriatoII/MindaGap)) +- Assign spots to segmented cells + Quality control +- Create quality-control metrics specific to this pipeline +- provide them to ([`MultiQC`](http://multiqc.info/)) to create a report ## Usage @@ -34,25 +42,18 @@ to set-up Nextflow. Make sure to [test your setup](https://nf-co.re/docs/usage/i with `-profile test` before running the workflow on actual data. ::: - - -Now, you can run the pipeline using: - - +Now, you can run the pipeline using all default values with: ```bash nextflow run nf-core/molkart \ @@ -77,11 +78,9 @@ For more details about the output files and reports, please refer to the ## Credits -nf-core/molkart was originally written by @FloWuenne. +nf-core/molkart was originally written by [Florian Wuennemann](https://github.com/FloWuenne) and [Kresimir Bestak](https://github.com/kbestak). -We thank the following people for their extensive assistance in the development of this pipeline: - - +We thank the [Maxime U Garcia](https://github.com/maxulysse) for his assistance and support in the development of this pipeline. ## Contributions and Support @@ -94,8 +93,6 @@ For further information or help, don't hesitate to get in touch on the [Slack `# - - An extensive list of references for the tools used by the pipeline can be found in the [`CITATIONS.md`](CITATIONS.md) file. You can cite the `nf-core` publication as follows: diff --git a/lib/WorkflowMolkart.groovy b/lib/WorkflowMolkart.groovy index 30ae445..35fc684 100755 --- a/lib/WorkflowMolkart.groovy +++ b/lib/WorkflowMolkart.groovy @@ -55,12 +55,14 @@ class WorkflowMolkart { public static String toolCitationText(params) { - // TODO nf-core: Optionally add in-text citation tools to this list. // Can use ternary operators to dynamically construct based conditions, e.g. params["run_xyz"] ? "Tool (Foo et al. 2023)" : "", // Uncomment function in methodsDescriptionText to render in MultiQC report def citation_text = [ "Tools used in the workflow included:", - "FastQC (Andrews 2010),", + "Mindagap (Guerreiro et al. 2023)" + params.segmentation_method.split(',').contains('mesmer') ? "Mesmer (Greenwald et al. 2021)" : "", + params.segmentation_method.split(',').contains('ilastik') ? "ilastik (Berg et al. 2019)" : "", + params.segmentation_method.split(',').contains('cellpose') ? "Cellpose (Stringer et al. 2021; Pachitariu et al 2022)" : "", "MultiQC (Ewels et al. 2016)", "." ].join(' ').trim() @@ -70,11 +72,13 @@ class WorkflowMolkart { public static String toolBibliographyText(params) { - // TODO Optionally add bibliographic entries to this list. // Can use ternary operators to dynamically construct based conditions, e.g. params["run_xyz"] ? "
  • Author (2023) Pub name, Journal, DOI
  • " : "", // Uncomment function in methodsDescriptionText to render in MultiQC report def reference_text = [ - "
  • Andrews S, (2010) FastQC, URL: https://www.bioinformatics.babraham.ac.uk/projects/fastqc/).
  • ", + "
  • Guerreiro R, Wuennemann F & pvtodorov (2023). ViriatoII/MindaGap: v0.0.3 (0.0.3).
  • ", + params.segmentation_method.split(',').contains('mesmer') ? "
  • Greenwald NF, Miller G, Moen E, Kong A, Kagel A, Dougherty T, Fullaway CC, McIntosh BJ, Leow KX, Schwartz MS, Pavelchek C, Cui S, Camplisson I, Bar-Tal O, Singh J, Fong M, Chaudhry G, Abraham Z, Moseley J, Warshawsky S, Soon E, Greenbaum S, Risom T, Hollmann T, Bendall SC, Keren L, Graf W, Angelo M, Van Valen D. Whole-cell segmentation of tissue images with human-level performance using large-scale data annotation and deep learning. Nat Biotechnol. 2022 Apr;40(4):555-565. doi: 10.1038/s41587-021-01094-0. Epub 2021 Nov 18. PMID: 34795433; PMCID: PMC9010346.
  • " : "", + params.segmentation_method.split(',').contains('ilastik') ? "
  • Berg, S., Kutra, D., Kroeger, T. et al. ilastik: interactive machine learning for (bio)image analysis. Nat Methods 16, 1226–1232 (2019). https://doi.org/10.1038/s41592-019-0582-9
  • " : "", + params.segmentation_method.split(',').contains('cellpose') ? "
  • Stringer, C., Wang, T., Michaelos, M. et al. Cellpose: a generalist algorithm for cellular segmentation. Nat Methods 18, 100–106 (2021). https://doi.org/10.1038/s41592-020-01018-x
  • " : "", "
  • Ewels, P., Magnusson, M., Lundin, S., & Käller, M. (2016). MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics , 32(19), 3047–3048. doi: /10.1093/bioinformatics/btw354
  • " ].join(' ').trim() @@ -95,9 +99,8 @@ class WorkflowMolkart { meta["tool_citations"] = "" meta["tool_bibliography"] = "" - // TODO Only uncomment below if logic in toolCitationText/toolBibliographyText has been filled! - //meta["tool_citations"] = toolCitationText(params).replaceAll(", \\.", ".").replaceAll("\\. \\.", ".").replaceAll(", \\.", ".") - //meta["tool_bibliography"] = toolBibliographyText(params) + meta["tool_citations"] = toolCitationText(params).replaceAll(", \\.", ".").replaceAll("\\. \\.", ".").replaceAll(", \\.", ".") + meta["tool_bibliography"] = toolBibliographyText(params) def methods_text = mqc_methods_yaml.text From 9f2e1ea3d2639b7f0d92312a4537df334c84a852 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Mon, 13 Nov 2023 17:14:21 +0000 Subject: [PATCH 054/149] Updated date in changelog --- CHANGELOG.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index aff56ec..6b1a1b7 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -3,7 +3,7 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/) and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html). -## v1.0.1dev - [2023.10.11] +## v1.0.1dev - [2023.11.13] Added documentation - usage.md and output.md From 0e5e4a2ced2f1bb954ef53fe8ed556a9009118b5 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Tue, 14 Nov 2023 09:32:44 +0000 Subject: [PATCH 055/149] Fixed WorkflowMolkart.groovy --- CHANGELOG.md | 2 +- lib/WorkflowMolkart.groovy | 8 ++++---- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 6b1a1b7..29e0de0 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -15,7 +15,7 @@ Added documentation - usage.md and output.md - updated nf-core module versions - CITATIONS.md updated - README.md updated -- WorkflowMolkart.groovy updated to return citations if tools are used +- WorkflowMolkart.groovy updated to return citations if tools are used (added commas) ## v1.0.1dev - [2023.25.10] diff --git a/lib/WorkflowMolkart.groovy b/lib/WorkflowMolkart.groovy index 35fc684..55ef7a0 100755 --- a/lib/WorkflowMolkart.groovy +++ b/lib/WorkflowMolkart.groovy @@ -59,10 +59,10 @@ class WorkflowMolkart { // Uncomment function in methodsDescriptionText to render in MultiQC report def citation_text = [ "Tools used in the workflow included:", - "Mindagap (Guerreiro et al. 2023)" - params.segmentation_method.split(',').contains('mesmer') ? 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    From e88a4c399d363876a0775a2359f80db55664c9dc Mon Sep 17 00:00:00 2001 From: Florian Wuennemann Date: Tue, 14 Nov 2023 10:56:37 +0000 Subject: [PATCH 058/149] Prettier changes. --- docs/usage.md | 20 ++++++++++---------- 1 file changed, 10 insertions(+), 10 deletions(-) diff --git a/docs/usage.md b/docs/usage.md index 2a6111e..54b3d04 100644 --- a/docs/usage.md +++ b/docs/usage.md @@ -22,18 +22,18 @@ A final samplesheet file that can be used to process a full dataset (after segme ```console sample,nuclear_image,spot_table,membrane_image -SAMPLE1,SAMPLE1.DAPI.tiff,SAMPLE1.spots.txt,SAMPLE1.WGA.tiff -SAMPLE2,SAMPLE2.DAPI.tiff,SAMPLE2.spots.txt,SAMPLE2.WGA.tiff -SAMPLE3,SAMPLE3.DAPI.tiff,SAMPLE3.spots.txt,SAMPLE3.WGA.tiff -SAMPLE4,SAMPLE4.DAPI.tiff,SAMPLE4.spots.txt,SAMPLE4.WGA.tiff +SAMPLE1,SAMPLE1.nucleus.tiff,SAMPLE1.spots.txt,SAMPLE1.membrane.tiff +SAMPLE2,SAMPLE2.nucleus.tiff,SAMPLE2.spots.txt,SAMPLE2.membrane.tiff +SAMPLE3,SAMPLE3.nucleus.tiff,SAMPLE3.spots.txt,SAMPLE3.membrane.tiff +SAMPLE4,SAMPLE4.nucleus.tiff,SAMPLE4.spots.txt,SAMPLE4.membrane.tiff ``` -| Column | Description | -| ---------------- | ------------------------------------------------------------------------------------------------------------------------- | -| `sample` | Custom sample name. If multiple images are being processed, their sample tags must be different. Must not contain spaces. | -| `nuclear_image` | Full path to nuclear image (DAPI, Hoechst). | -| `spot_table` | Full path to tsv or txt spot table provided by Resolve. | -| `membrane_image` | Full path to membrane image (e.g WGA) or second channel to help with segmentation (optional). | +| Column | Description | +| ---------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------ | +| `sample` | Custom sample name. If multiple field-of-views (FOVs) are being processed for the same sample, their sample tags must be different. Must not contain spaces. | +| `nuclear_image` | Full path to nuclear image (DAPI, Hoechst). | +| `spot_table` | Full path to tsv or txt spot table provided by Resolve. Separartor must be `\t`. | +| `membrane_image` | Full path to membrane image (e.g WGA) or second channel to help with segmentation (optional). | An [example samplesheet](../assets/samplesheet.csv) has been provided with the pipeline. From 6b152d7f4cf7424e3659425bd7882782c7f86869 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Wed, 15 Nov 2023 16:40:00 +0000 Subject: [PATCH 059/149] Fixed Cellpose custom model multisample, added clahe_skip_pyramid --- CHANGELOG.md | 13 +++++ bin/apply_clahe.dask.py | 96 +++++++++++++++++-------------- conf/modules.config | 9 +-- docs/images/molkart_workflow.png | Bin 610652 -> 588219 bytes nextflow.config | 2 + nextflow_schema.json | 9 ++- workflows/molkart.nf | 9 ++- 7 files changed, 88 insertions(+), 50 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 29e0de0..d768e2d 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -3,6 +3,19 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/) and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html). +## v1.0.1dev - [2023.11.15] + +Upgraded workflow, fixed multisample cellpose segmentation with custom model. Added options necessary to make testing work on small images. + +### `Added` + +- white background in metromap +- clahe_skip_pyramid parameter to skip pyramid generation in the clahe step - necessary for smaller data + +### `Fixed` + +- Cellpose custom model functions with multiple samples now. + ## v1.0.1dev - [2023.11.13] Added documentation - usage.md and output.md diff --git a/bin/apply_clahe.dask.py b/bin/apply_clahe.dask.py index 545ae75..6112298 100755 --- a/bin/apply_clahe.dask.py +++ b/bin/apply_clahe.dask.py @@ -55,6 +55,13 @@ def get_args(): "-g", "--nbins", dest="nbins", action="store", required=False, default=256, help="Number of bins for CLAHE" ) inputs.add_argument("-p", "--pixel-size", dest="pixel_size", action="store", required=True, help="Image pixel size") + inputs.add_argument( + "--skip_pyramid", + dest="skip_pyramid", + action="store_true", + default=False, + help="Should pyramid creation be skipped", + ) arg = parser.parse_args() @@ -125,53 +132,58 @@ def main(args): # construct levels tile_size = 1024 scale = 2 - pixel_size = args.pixel_size - dtype = img_dask.dtype - base_shape = img_dask[0].shape - num_channels = img_dask.shape[0] - num_levels = (np.ceil(np.log2(max(base_shape) / tile_size)) + 1).astype(int) - factors = 2 ** np.arange(num_levels) - shapes = (np.ceil(np.array(base_shape) / factors[:, None])).astype(int) - - print("Pyramid level sizes: ") - for i, shape in enumerate(shapes): - print(f" level {i+1}: {format_shape(shape)}", end="") - if i == 0: - print("(original size)", end="") + + if args.skip_pyramid: + with tifffile.TiffWriter(args.output, ome=True, bigtiff=True) as tiff: + tiff.write( + data=img_dask, + shape=img_dask.shape, + dtype=img_dask.dtype, + resolution=(10000 / pixel_size, 10000 / pixel_size, "centimeter"), + ) + else: + dtype = img_dask.dtype + base_shape = img_dask[0].shape + num_channels = img_dask.shape[0] + num_levels = (np.ceil(np.log2(max(base_shape) / tile_size)) + 1).astype(int) + factors = 2 ** np.arange(num_levels) + shapes = (np.ceil(np.array(base_shape) / factors[:, None])).astype(int) + + print("Pyramid level sizes: ") + for i, shape in enumerate(shapes): + print(f" level {i+1}: {format_shape(shape)}", end="") + if i == 0: + print("(original size)", end="") + print() print() - print() - print(shapes) - - level_full_shapes = [] - for shape in shapes: - level_full_shapes.append((num_channels, shape[0], shape[1])) - level_shapes = shapes - tip_level = np.argmax(np.all(level_shapes < tile_size, axis=1)) - tile_shapes = [(tile_size, tile_size) if i <= tip_level else None for i in range(len(level_shapes))] - - # write pyramid - with tifffile.TiffWriter(args.output, ome=True, bigtiff=True) as tiff: - tiff.write( - data=img_dask, - shape=level_full_shapes[0], - subifds=int(num_levels - 1), - dtype=dtype, - resolution=(10000 / pixel_size, 10000 / pixel_size, "centimeter"), - tile=tile_shapes[0], - ) - for level, (shape, tile_shape) in enumerate(zip(level_full_shapes[1:], tile_shapes[1:]), 1): + print(shapes) + + level_full_shapes = [] + for shape in shapes: + level_full_shapes.append((num_channels, shape[0], shape[1])) + level_shapes = shapes + tip_level = np.argmax(np.all(level_shapes < tile_size, axis=1)) + tile_shapes = [(tile_size, tile_size) if i <= tip_level else None for i in range(len(level_shapes))] + + # write pyramid + with tifffile.TiffWriter(args.output, ome=True, bigtiff=True) as tiff: tiff.write( - data=subres_tiles(level, level_full_shapes, tile_shapes, args.output, scale), - shape=shape, - subfiletype=1, + data=img_dask, + shape=level_full_shapes[0], + subifds=int(num_levels - 1), dtype=dtype, - tile=tile_shape, + resolution=(10000 / pixel_size, 10000 / pixel_size, "centimeter"), + tile=tile_shapes[0], ) - - # note about metadata: the channels, planes etc were adjusted not to include the removed channels, however - # the channel ids have stayed the same as before removal. E.g if channels 1 and 2 are removed, - # the channel ids in the metadata will skip indices 1 and 2 (channel_id:0, channel_id:3, channel_id:4 ...) + for level, (shape, tile_shape) in enumerate(zip(level_full_shapes[1:], tile_shapes[1:]), 1): + tiff.write( + data=subres_tiles(level, level_full_shapes, tile_shapes, args.output, scale), + shape=shape, + subfiletype=1, + dtype=dtype, + tile=tile_shape + ) # tifffile.tiffcomment(args.output, to_xml(metadata)) print() diff --git a/conf/modules.config b/conf/modules.config index bdfa4d0..b5e52a6 100644 --- a/conf/modules.config +++ b/conf/modules.config @@ -108,10 +108,11 @@ process { ext.when = { !params.skip_clahe } ext.args = [ "", "--channel 0", - params.clahe_cliplimit ? "--cliplimit ${params.clahe_cliplimit}" : "", - params.clahe_nbins ? "--nbins ${params.clahe_nbins}" : "", - params.clahe_pixel_size ? "--pixel-size ${params.clahe_pixel_size}" : "", - params.clahe_kernel ? 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zywce{)945LVzfF!e4!iquy`nf7e@QLntDd3rPrwv5;6NnS53b}e;0M=T`X(+o^9`2 zi4s*$oI;+>vQzee99x>3-E~SS^J8R%^QYVQ73;+4La;SBG^CIfw?LC!sC-RdY&~(R zVP9}{oPF|D(|31hJ^Yi`VGZQ#_yJKs1qL(M67Tw?P-t1HdPxBQ2k#5DG)`=bChPwg z$Fh1-wYC~Fu20n+#J5YRI#ecNPp|&Jd$a$sV%LpEMnvi2OZkRW zQUV;VnsQZM^vWIBh+lm&!+X`VnV@}4ET$V4dx+rcr60fiHKUh&|G;m{M)3PjZ~rw9 zzklbSpS3Ulhh}W}(TV@|20FK%V;la<03zKwmr7OCpI}~mxl|8$^GpfES(3@*DK;8$ ze-Dybo!1h(;i><63G>~Yi+{cRfB(NdwV(b|yZ99=?*8u$z7Kio|Ay%MQ2f`m|Gy#n s-w=Htf$yLHzn>ugn?>Kpj`D4T>(kY@Y^z>66W>xhtZ^t)$>j3?16zc11ONa4 diff --git a/nextflow.config b/nextflow.config index 29d9fd2..a7610bb 100644 --- a/nextflow.config +++ b/nextflow.config @@ -35,6 +35,7 @@ params { clahe_nbins = 256 clahe_pixel_size = 0.138 clahe_kernel = 25 + clahe_skip_pyramid = false // Training subset command line create_training_subset = false @@ -136,6 +137,7 @@ profiles { shifter.enabled = false charliecloud.enabled = false apptainer.enabled = false + docker.runOptions = '--entrypoint ""' } arm { docker.runOptions = '-u $(id -u):$(id -g) --platform=linux/amd64' diff --git a/nextflow_schema.json b/nextflow_schema.json index 53ae9f6..e6f7a01 100644 --- a/nextflow_schema.json +++ b/nextflow_schema.json @@ -72,7 +72,8 @@ "cellpose_save_flows": { "type": "boolean", "description": "Should flow fields from Cellpose be saved?", - "fa_icon": "fas fa-arrows-alt" + "fa_icon": "fas fa-arrows-alt", + "hidden": true }, "ilastik_pixel_project": { "type": "string", @@ -131,6 +132,12 @@ "default": 2144, "description": "Tile size (distance between gridlines)", "fa_icon": "fas fa-th" + }, + "clahe_skip_pyramid": { + "type": "boolean", + "description": "Should pyramid generation be skipped for CLAHE", + "fa_icon": "fas fa-cubes", + "hidden": true } } }, diff --git a/workflows/molkart.nf b/workflows/molkart.nf index 3eaaaa4..96edee9 100644 --- a/workflows/molkart.nf +++ b/workflows/molkart.nf @@ -185,10 +185,13 @@ workflow MOLKART { } // // MODULE: Cellpose segmentation - // TODO: check if there is a problem with resume for Cellpose. - cellpose_custom_model = params.cellpose_custom_model ? Channel.fromPath(params.cellpose_custom_model) : [] + // + cellpose_custom_model = params.cellpose_custom_model ? stack_mix.combine(Channel.fromPath(params.cellpose_custom_model)) : [] if (params.segmentation_method.split(',').contains('cellpose')) { - CELLPOSE(stack_mix, cellpose_custom_model) + CELLPOSE( + stack_mix, + cellpose_custom_model ? cellpose_custom_model.map{it[2]} : [] + ) ch_versions = ch_versions.mix(CELLPOSE.out.versions) segmentation_masks = segmentation_masks .mix(CELLPOSE.out.mask From 15de9b07dd957f29c7c525af4dbcff127db7a337 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Wed, 15 Nov 2023 16:43:43 +0000 Subject: [PATCH 060/149] Added usage for clahe_skip_pyramid --- docs/usage.md | 1 + 1 file changed, 1 insertion(+) diff --git a/docs/usage.md b/docs/usage.md index 54b3d04..65364d0 100644 --- a/docs/usage.md +++ b/docs/usage.md @@ -101,6 +101,7 @@ clahe_cliplimit: 0.01 clahe_nbins: 256 clahe_pixel_size: 0.138 clahe_kernel: 25 +clahe_skip_pyramid: false create_training_subset: false crop_amount: 4 crop_nonzero_fraction: 0.4 From a74f79499249875095d1698e8f3eb022e80fc033 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Wed, 15 Nov 2023 18:13:13 +0000 Subject: [PATCH 061/149] Ran black on apply_clahe.dask.py --- bin/apply_clahe.dask.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/bin/apply_clahe.dask.py b/bin/apply_clahe.dask.py index 6112298..4d9f7ba 100755 --- a/bin/apply_clahe.dask.py +++ b/bin/apply_clahe.dask.py @@ -182,7 +182,7 @@ def main(args): shape=shape, subfiletype=1, dtype=dtype, - tile=tile_shape + tile=tile_shape, ) # tifffile.tiffcomment(args.output, to_xml(metadata)) print() From 3c5b0fe4e28cbdbcade5ace3aed0099301e2c998 Mon Sep 17 00:00:00 2001 From: Florian Wuennemann Date: Thu, 16 Nov 2023 12:20:22 +0000 Subject: [PATCH 062/149] Moved docker entrypoint fix from process to docker scope. --- conf/modules.config | 2 -- 1 file changed, 2 deletions(-) diff --git a/conf/modules.config b/conf/modules.config index b5e52a6..38426d8 100644 --- a/conf/modules.config +++ b/conf/modules.config @@ -125,7 +125,6 @@ process { params.mesmer_image_mpp ? "--image-mpp ${params.mesmer_image_mpp}" : "", "--nuclear-channel 0" ].join(" ").trim() - containerOptions = '--entrypoint ""' publishDir = [ path: "${params.outdir}/segmentation/mesmer", pattern: "*.tif", @@ -148,7 +147,6 @@ process { params.cellpose_flow_threshold ? "--flow_threshold ${params.cellpose_flow_threshold}" : "", params.cellpose_edge_exclude ? "--exclude_on_edges" : "" ].join(" ").trim() - containerOptions = '--entrypoint ""' publishDir = [ path: "${params.outdir}/segmentation/cellpose", pattern: "*_cp_masks.tif", From 07d1b30ec34f0742df3fd120188576994106a466 Mon Sep 17 00:00:00 2001 From: Florian Wuennemann Date: Mon, 20 Nov 2023 13:12:31 +0000 Subject: [PATCH 063/149] Updated cellpose and fixed singularity error. --- conf/modules.config | 1 + modules.json | 2 +- modules/nf-core/cellpose/environment.yml | 1 + modules/nf-core/cellpose/main.nf | 11 ++++++----- modules/nf-core/cellpose/meta.yml | 9 ++++++++- 5 files changed, 17 insertions(+), 7 deletions(-) diff --git a/conf/modules.config b/conf/modules.config index 38426d8..ed0b7a1 100644 --- a/conf/modules.config +++ b/conf/modules.config @@ -133,6 +133,7 @@ process { } withName: "CELLPOSE" { + singularity.runOptions = "--bind $HOME:$HOME" ext.when = { params.segmentation_method.split(',').contains('cellpose') } memory = "16GB" cpus = 8 diff --git a/modules.json b/modules.json index e6d566d..1bb0a68 100644 --- a/modules.json +++ b/modules.json @@ -7,7 +7,7 @@ "nf-core": { "cellpose": { "branch": "master", - "git_sha": "516189e968feb4ebdd9921806988b4c12b4ac2dc", + "git_sha": "0975c63a8ce4488c3259f595270b3f0d419abafe", "installed_by": ["modules"] }, "custom/dumpsoftwareversions": { diff --git a/modules/nf-core/cellpose/environment.yml b/modules/nf-core/cellpose/environment.yml index bcd3a8b..f8ca8bc 100644 --- a/modules/nf-core/cellpose/environment.yml +++ b/modules/nf-core/cellpose/environment.yml @@ -1,3 +1,4 @@ +name: cellpose channels: - conda-forge - bioconda diff --git a/modules/nf-core/cellpose/main.nf b/modules/nf-core/cellpose/main.nf index a2b2206..8fde76c 100644 --- a/modules/nf-core/cellpose/main.nf +++ b/modules/nf-core/cellpose/main.nf @@ -2,15 +2,16 @@ process CELLPOSE { tag "$meta.id" label 'process_medium' - container "docker.io/biocontainers/cellpose:2.1.1_cv2" + container "docker.io/biocontainers/cellpose:2.2.2_cv2" input: tuple val(meta), path(image) path(model) output: - tuple val(meta), path("*masks.tif"), emit: mask - path "versions.yml" , emit: versions + tuple val(meta), path("*masks.tif") , emit: mask + tuple val(meta), path("*flows.tif"), emit: flows, optional: true + path "versions.yml" , emit: versions when: task.ext.when == null || task.ext.when @@ -23,7 +24,7 @@ process CELLPOSE { def args = task.ext.args ?: '' def prefix = task.ext.prefix ?: "${meta.id}" def model_command = model ? "--pretrained_model $model" : "" - def VERSION = '2.1.1' + def VERSION = '2.2.2' """ cellpose \ --image_path $image \ @@ -43,7 +44,7 @@ process CELLPOSE { error "I did not manage to create a cellpose module in Conda that works in all OSes. Please use Docker / Singularity / Podman instead." } def prefix = task.ext.prefix ?: "${meta.id}" - def VERSION = "2.1.1" // WARN: Version information not provided by tool on CLI. Please update this string when bumping container versions. + def VERSION = "2.2.2" // WARN: Version information not provided by tool on CLI. Please update this string when bumping container versions. """ touch ${prefix}_cp_masks.tif diff --git a/modules/nf-core/cellpose/meta.yml b/modules/nf-core/cellpose/meta.yml index 647e1f9..32f59f9 100644 --- a/modules/nf-core/cellpose/meta.yml +++ b/modules/nf-core/cellpose/meta.yml @@ -11,7 +11,7 @@ tools: documentation: "https://cellpose.readthedocs.io/en/latest/command.html" tool_dev_url: "https://github.com/MouseLand/cellpose" doi: 10.1038/s41592-022-01663-4 - licence: "BSD 3-Clause" + licence: ["BSD 3-Clause"] input: - meta: type: map @@ -39,7 +39,14 @@ output: type: file description: labelled mask output from cellpose in tif format pattern: "*.{tif, tiff}" + - flows: + type: file + description: cell flow output from cellpose + pattern: "*.{tif}" + authors: - "@josenimo" + - "@FlowWuenne" maintainers: - "@josenimo" + - "@FlowWuenne" From bebee8887f961e7415b567e867f4dd1a766d17b4 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Fri, 24 Nov 2023 17:52:16 +0000 Subject: [PATCH 064/149] Added nf-test for pipeline main.nf --- nf-test.config | 8 ++++ tests/main.nf.test | 96 +++++++++++++++++++++++++++++++++++++++++ tests/main.nf.test.snap | 38 ++++++++++++++++ tests/nextflow.config | 13 ++++++ tests/tags.yml | 10 +++++ 5 files changed, 165 insertions(+) create mode 100644 nf-test.config create mode 100644 tests/main.nf.test create mode 100644 tests/main.nf.test.snap create mode 100644 tests/nextflow.config create mode 100644 tests/tags.yml diff --git a/nf-test.config b/nf-test.config new file mode 100644 index 0000000..870799d --- /dev/null +++ b/nf-test.config @@ -0,0 +1,8 @@ +config { + + testsDir "tests" + workDir ".nf-test" + configFile "tests/nextflow.config" + profile "" + +} diff --git a/tests/main.nf.test b/tests/main.nf.test new file mode 100644 index 0000000..0863c6a --- /dev/null +++ b/tests/main.nf.test @@ -0,0 +1,96 @@ +nextflow_pipeline { + + name "Test Workflow main.nf" + script "../main.nf" + config "./nextflow.config" + tag "pipeline" + tag "pipeline_molkart" + + test("Nuclear channel, mesmer and cellpose, without clahe") { + + when { + params { + input = 'https://raw.githubusercontent.com/nf-core/test-datasets/molkart/test_data/samplesheets/samplesheet_nuclear.csv' + outdir = "$outputDir" + skip_clahe = true + tilesize = 90 + segmentation_method = "cellpose,mesmer" + } + } + + then { + assert workflow.success + assert snapshot( + path("$outputDir/mindagap/nuclear_gridfilled.tiff"), + path("$outputDir/mindagap/spots_markedDups.txt"), + path("$outputDir/segmentation/cellpose/nuc_only_cellpose_mask.tif"), + path("$outputDir/segmentation/mesmer/nuc_only_mesmer_mask.tif"), + path("$outputDir/spot2cell/spots_markedDups.cellpose.cellxgene.csv"), + path("$outputDir/spot2cell/spots_markedDups.mesmer.cellxgene.csv"), + path("$outputDir/molcart_qc/nuc_only.cellpose.spot_QC.csv"), + path("$outputDir/molcart_qc/nuc_only.mesmer.spot_QC.csv") + ).match() + assert file("$outputDir/multiqc/multiqc_report.html").exists() + } + } + + test("Two channels, mesmer and cellpose, with clahe") { + + when { + params { + input = 'https://raw.githubusercontent.com/nf-core/test-datasets/molkart/test_data/samplesheets/samplesheet_membrane.csv' + outdir = "$outputDir" + tilesize = 90 + segmentation_method = "cellpose,mesmer" + } + } + + then { + assert workflow.success + assert snapshot( + path("$outputDir/mindagap/membrane_gridfilled.tiff"), + path("$outputDir/mindagap/spots_markedDups.txt"), + path("$outputDir/clahe/mem_only_0.clahe.tiff"), + path("$outputDir/clahe/mem_only_1.clahe.tiff"), + path("$outputDir/segmentation/cellpose/mem_only_cellpose_mask.tif"), + path("$outputDir/segmentation/mesmer/mem_only_mesmer_mask.tif"), + path("$outputDir/spot2cell/spots_markedDups.cellpose.cellxgene.csv"), + path("$outputDir/spot2cell/spots_markedDups.mesmer.cellxgene.csv"), + path("$outputDir/stack/mem_only.stack.ome.tif"), + path("$outputDir/molcart_qc/mem_only.cellpose.spot_QC.csv"), + path("$outputDir/molcart_qc/mem_only.mesmer.spot_QC.csv"), + ).match() + assert file("$outputDir/multiqc/multiqc_report.html").exists() + } + } + + test("Create training subset") { + + when { + params { + input = 'https://raw.githubusercontent.com/nf-core/test-datasets/molkart/test_data/samplesheets/samplesheet_nuclear.csv' + outdir = "$outputDir" + tilesize = 90 + create_training_subset = true + crop_amount = 2 + crop_size_x = 10 + crop_size_y = 10 + } + } + + then { + assert workflow.success + assert snapshot( + path("$outputDir/mindagap/nuclear_gridfilled.tiff"), + path("$outputDir/clahe/nuc_only_0.clahe.tiff") + ).match() + assert file("$outputDir/training_subset/hdf5/nuc_only_0.clahe_crop0.hdf5").exists() + assert file("$outputDir/training_subset/hdf5/nuc_only_0.clahe_crop1.hdf5").exists() + assert file("$outputDir/training_subset/hdf5/nuc_only_0.clahe_CropSummary.txt").exists() + assert file("$outputDir/training_subset/tiff/nuc_only_0.clahe_crop0.tiff").exists() + assert file("$outputDir/training_subset/tiff/nuc_only_0.clahe_crop1.tiff").exists() + assert file("$outputDir/training_subset/tiff/nuc_only_0.clahe.crop_overview.png").exists() + } + } + +} diff --git a/tests/main.nf.test.snap b/tests/main.nf.test.snap new file mode 100644 index 0000000..6f7dc14 --- /dev/null +++ b/tests/main.nf.test.snap @@ -0,0 +1,38 @@ +{ + "Two channels, mesmer and cellpose, with clahe": { + "content": [ + "membrane_gridfilled.tiff:md5,6e24160d758468d2de07ca200dfb62c2", + "spots_markedDups.txt:md5,4562caad05850d7dd7b6e9235e068a8b", + "mem_only_0.clahe.tiff:md5,49ddd621b8f389729c2e2610efd94082", + "mem_only_1.clahe.tiff:md5,9d875972fb697955ce459a212abf8181", + "mem_only_cellpose_mask.tif:md5,590591f541b6d3f17810cd44dd71b252", + "mem_only_mesmer_mask.tif:md5,6f8c792ccc4cca97b5696990fb4e3801", + "spots_markedDups.cellpose.cellxgene.csv:md5,f063c1ce5e93e1e73431af36c6bc1e79", + "spots_markedDups.mesmer.cellxgene.csv:md5,f54f2af6ce874e96f7973504bddd9bc9", + "mem_only.stack.ome.tif:md5,d8659ad7bf017fecc795b855785b74be", + "mem_only.cellpose.spot_QC.csv:md5,4b24962d8eae2579eab419179212fd27", + "mem_only.mesmer.spot_QC.csv:md5,d5c302ff76e8ce7a8d212f6d818cedbc" + ], + "timestamp": "2023-11-24T17:29:36.533136659" + }, + "Nuclear channel, mesmer and cellpose, without clahe": { + "content": [ + "nuclear_gridfilled.tiff:md5,123763d54f05b2274690b3b84f9690b1", + "spots_markedDups.txt:md5,4562caad05850d7dd7b6e9235e068a8b", + "nuc_only_cellpose_mask.tif:md5,2784d8c6683ad80c24d8df4121e1128f", + "nuc_only_mesmer_mask.tif:md5,e9719f53651b4bf76a37e9374db7f4e4", + "spots_markedDups.cellpose.cellxgene.csv:md5,0610a8713457c28acf1bc4c298bee8e3", + "spots_markedDups.mesmer.cellxgene.csv:md5,13d8f4fb05a400c94866404fc424a8e8", + "nuc_only.cellpose.spot_QC.csv:md5,3fa7f7d1f87d37428907a77236893330", + "nuc_only.mesmer.spot_QC.csv:md5,9779af541ceae4a0fe0ae20d75db2bee" + ], + "timestamp": "2023-11-24T16:28:34.810940773" + }, + "Create training subset": { + "content": [ + "nuclear_gridfilled.tiff:md5,123763d54f05b2274690b3b84f9690b1", + "nuc_only_0.clahe.tiff:md5,d68e4bfa536c00555bc7acb33425b82f" + ], + "timestamp": "2023-11-24T17:29:59.476151001" + } +} \ No newline at end of file diff --git a/tests/nextflow.config b/tests/nextflow.config new file mode 100644 index 0000000..c73633a --- /dev/null +++ b/tests/nextflow.config @@ -0,0 +1,13 @@ +/* +======================================================================================== + Nextflow config file for running tests +======================================================================================== +*/ + +process { + + withName: "CLAHE_DASK" { + ext.args = '--skip_pyramid -c 0 -l 0.01 -p 0.23 --kernel 25' + } + +} diff --git a/tests/tags.yml b/tests/tags.yml new file mode 100644 index 0000000..dce2348 --- /dev/null +++ b/tests/tags.yml @@ -0,0 +1,10 @@ +default: + - bin/** + - conf/** + - lib/** + - modules/** + - subworkflows/** + - tests/** + - workflows/** + - nextflow.config + - main.nf From 350d73c51db93baed68a91f0bab6a96bfde9a967 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Fri, 24 Nov 2023 17:55:17 +0000 Subject: [PATCH 065/149] Updated CHANGELOG --- CHANGELOG.md | 11 +++++++++++ 1 file changed, 11 insertions(+) diff --git a/CHANGELOG.md b/CHANGELOG.md index d768e2d..35e72e9 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -3,6 +3,17 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/) and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html). +## v1.0.1dev - [2023.11.24.] + +Added first nf-tests for the pipeline. + +### `Added` + +- nf-test for 3 runs +- main.nf where the input only has the nuclear channel (does not run clahe or ilastik) +- main.nf where the input has both nuclear and membrane image (runs clahe, does not run ilastik) +- main.nf where the input only has the nuclear channel (does not run clahe), creates training subset + ## v1.0.1dev - [2023.11.15] Upgraded workflow, fixed multisample cellpose segmentation with custom model. Added options necessary to make testing work on small images. From e9610774ea1240cad4e32d4fb1431275623141e1 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Fri, 24 Nov 2023 18:07:53 +0000 Subject: [PATCH 066/149] Added test.config specifications --- conf/test.config | 5 ++++- tests/main.nf.test | 1 + tests/main.nf.test.snap | 10 +++++----- 3 files changed, 10 insertions(+), 6 deletions(-) diff --git a/conf/test.config b/conf/test.config index 516d7f2..6e5e9fa 100644 --- a/conf/test.config +++ b/conf/test.config @@ -22,5 +22,8 @@ params { // Input data // TODO nf-core: Specify the paths to your test data on nf-core/test-datasets // TODO nf-core: Give any required params for the test so that command line flags are not needed - input = 'https://raw.githubusercontent.com/nf-core/test-datasets/viralrecon/samplesheet/samplesheet_test_illumina_amplicon.csv' + input = 'https://raw.githubusercontent.com/nf-core/test-datasets/molkart/test_data/samplesheets/samplesheet_membrane.csv' + tilesize = 90 + clahe_skip_pyramid = true + segmentation_method = "cellpose,mesmer" } diff --git a/tests/main.nf.test b/tests/main.nf.test index 0863c6a..6fee798 100644 --- a/tests/main.nf.test +++ b/tests/main.nf.test @@ -41,6 +41,7 @@ nextflow_pipeline { input = 'https://raw.githubusercontent.com/nf-core/test-datasets/molkart/test_data/samplesheets/samplesheet_membrane.csv' outdir = "$outputDir" tilesize = 90 + clahe_skip_pyramid = true segmentation_method = "cellpose,mesmer" } } diff --git a/tests/main.nf.test.snap b/tests/main.nf.test.snap index 6f7dc14..9572730 100644 --- a/tests/main.nf.test.snap +++ b/tests/main.nf.test.snap @@ -3,8 +3,8 @@ "content": [ "membrane_gridfilled.tiff:md5,6e24160d758468d2de07ca200dfb62c2", "spots_markedDups.txt:md5,4562caad05850d7dd7b6e9235e068a8b", - "mem_only_0.clahe.tiff:md5,49ddd621b8f389729c2e2610efd94082", - "mem_only_1.clahe.tiff:md5,9d875972fb697955ce459a212abf8181", + "mem_only_0.clahe.tiff:md5,d46db2f648f22977c1c024c52af3ada0", + "mem_only_1.clahe.tiff:md5,b36cf807080d205744dc1e3d38d54db3", "mem_only_cellpose_mask.tif:md5,590591f541b6d3f17810cd44dd71b252", "mem_only_mesmer_mask.tif:md5,6f8c792ccc4cca97b5696990fb4e3801", "spots_markedDups.cellpose.cellxgene.csv:md5,f063c1ce5e93e1e73431af36c6bc1e79", @@ -13,7 +13,7 @@ "mem_only.cellpose.spot_QC.csv:md5,4b24962d8eae2579eab419179212fd27", "mem_only.mesmer.spot_QC.csv:md5,d5c302ff76e8ce7a8d212f6d818cedbc" ], - "timestamp": "2023-11-24T17:29:36.533136659" + "timestamp": "2023-11-24T18:06:54.830322038" }, "Nuclear channel, mesmer and cellpose, without clahe": { "content": [ @@ -31,8 +31,8 @@ "Create training subset": { "content": [ "nuclear_gridfilled.tiff:md5,123763d54f05b2274690b3b84f9690b1", - "nuc_only_0.clahe.tiff:md5,d68e4bfa536c00555bc7acb33425b82f" + "nuc_only_0.clahe.tiff:md5,7f3b69eb6698af420de3956af9035689" ], - "timestamp": "2023-11-24T17:29:59.476151001" + "timestamp": "2023-11-24T18:07:19.513872664" } } \ No newline at end of file From 6becbbd438cf9bc74a0eed6f54f8ee4ad0db5e63 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Fri, 24 Nov 2023 23:07:19 +0000 Subject: [PATCH 067/149] Updated tests --- conf/test.config | 4 +--- tests/main.nf.test | 7 ++++--- tests/main.nf.test.snap | 9 +++------ tests/nextflow.config | 7 ------- 4 files changed, 8 insertions(+), 19 deletions(-) diff --git a/conf/test.config b/conf/test.config index 6e5e9fa..ba5ed84 100644 --- a/conf/test.config +++ b/conf/test.config @@ -16,12 +16,10 @@ params { // Limit resources so that this can run on GitHub Actions max_cpus = 4 - max_memory = '16.GB' + max_memory = '8.GB' max_time = '4.h' // Input data - // TODO nf-core: Specify the paths to your test data on nf-core/test-datasets - // TODO nf-core: Give any required params for the test so that command line flags are not needed input = 'https://raw.githubusercontent.com/nf-core/test-datasets/molkart/test_data/samplesheets/samplesheet_membrane.csv' tilesize = 90 clahe_skip_pyramid = true diff --git a/tests/main.nf.test b/tests/main.nf.test index 6fee798..1c7d90f 100644 --- a/tests/main.nf.test +++ b/tests/main.nf.test @@ -51,8 +51,6 @@ nextflow_pipeline { assert snapshot( path("$outputDir/mindagap/membrane_gridfilled.tiff"), path("$outputDir/mindagap/spots_markedDups.txt"), - path("$outputDir/clahe/mem_only_0.clahe.tiff"), - path("$outputDir/clahe/mem_only_1.clahe.tiff"), path("$outputDir/segmentation/cellpose/mem_only_cellpose_mask.tif"), path("$outputDir/segmentation/mesmer/mem_only_mesmer_mask.tif"), path("$outputDir/spot2cell/spots_markedDups.cellpose.cellxgene.csv"), @@ -61,6 +59,8 @@ nextflow_pipeline { path("$outputDir/molcart_qc/mem_only.cellpose.spot_QC.csv"), path("$outputDir/molcart_qc/mem_only.mesmer.spot_QC.csv"), ).match() + assert file("$outputDir/clahe/mem_only_0.clahe.tiff").exists() + assert file("$outputDir/clahe/mem_only_1.clahe.tiff").exists() assert file("$outputDir/multiqc/multiqc_report.html").exists() } } @@ -72,6 +72,7 @@ nextflow_pipeline { input = 'https://raw.githubusercontent.com/nf-core/test-datasets/molkart/test_data/samplesheets/samplesheet_nuclear.csv' outdir = "$outputDir" tilesize = 90 + clahe_skip_pyramid = true create_training_subset = true crop_amount = 2 crop_size_x = 10 @@ -83,8 +84,8 @@ nextflow_pipeline { assert workflow.success assert snapshot( path("$outputDir/mindagap/nuclear_gridfilled.tiff"), - path("$outputDir/clahe/nuc_only_0.clahe.tiff") ).match() + assert file("$outputDir/clahe/nuc_only_0.clahe.tiff").exists() assert file("$outputDir/training_subset/hdf5/nuc_only_0.clahe_crop0.hdf5").exists() assert file("$outputDir/training_subset/hdf5/nuc_only_0.clahe_crop1.hdf5").exists() assert file("$outputDir/training_subset/hdf5/nuc_only_0.clahe_CropSummary.txt").exists() diff --git a/tests/main.nf.test.snap b/tests/main.nf.test.snap index 9572730..a3696ac 100644 --- a/tests/main.nf.test.snap +++ b/tests/main.nf.test.snap @@ -3,8 +3,6 @@ "content": [ "membrane_gridfilled.tiff:md5,6e24160d758468d2de07ca200dfb62c2", "spots_markedDups.txt:md5,4562caad05850d7dd7b6e9235e068a8b", - "mem_only_0.clahe.tiff:md5,d46db2f648f22977c1c024c52af3ada0", - "mem_only_1.clahe.tiff:md5,b36cf807080d205744dc1e3d38d54db3", "mem_only_cellpose_mask.tif:md5,590591f541b6d3f17810cd44dd71b252", "mem_only_mesmer_mask.tif:md5,6f8c792ccc4cca97b5696990fb4e3801", "spots_markedDups.cellpose.cellxgene.csv:md5,f063c1ce5e93e1e73431af36c6bc1e79", @@ -13,7 +11,7 @@ "mem_only.cellpose.spot_QC.csv:md5,4b24962d8eae2579eab419179212fd27", "mem_only.mesmer.spot_QC.csv:md5,d5c302ff76e8ce7a8d212f6d818cedbc" ], - "timestamp": "2023-11-24T18:06:54.830322038" + "timestamp": "2023-11-24T22:58:21.520372411" }, "Nuclear channel, mesmer and cellpose, without clahe": { "content": [ @@ -30,9 +28,8 @@ }, "Create training subset": { "content": [ - "nuclear_gridfilled.tiff:md5,123763d54f05b2274690b3b84f9690b1", - "nuc_only_0.clahe.tiff:md5,7f3b69eb6698af420de3956af9035689" + "nuclear_gridfilled.tiff:md5,123763d54f05b2274690b3b84f9690b1" ], - "timestamp": "2023-11-24T18:07:19.513872664" + "timestamp": "2023-11-24T23:02:32.575286676" } } \ No newline at end of file diff --git a/tests/nextflow.config b/tests/nextflow.config index c73633a..08dc560 100644 --- a/tests/nextflow.config +++ b/tests/nextflow.config @@ -4,10 +4,3 @@ ======================================================================================== */ -process { - - withName: "CLAHE_DASK" { - ext.args = '--skip_pyramid -c 0 -l 0.01 -p 0.23 --kernel 25' - } - -} From 9d4ead6d5bc6fe7cec53b16a2c096ae7af8bfc77 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Fri, 24 Nov 2023 23:36:18 +0000 Subject: [PATCH 068/149] Removed hardcoded memory requirements --- conf/modules.config | 5 ----- 1 file changed, 5 deletions(-) diff --git a/conf/modules.config b/conf/modules.config index ed0b7a1..27a6329 100644 --- a/conf/modules.config +++ b/conf/modules.config @@ -104,7 +104,6 @@ process { } withName: "CLAHE_DASK" { - memory = "16GB" ext.when = { !params.skip_clahe } ext.args = [ "", "--channel 0", @@ -118,8 +117,6 @@ process { withName: "DEEPCELL_MESMER" { ext.when = { params.segmentation_method.split(',').contains('mesmer') } - memory = "16GB" - cpus = 8 ext.args = [ "", params.mesmer_compartment ? "--compartment ${params.mesmer_compartment}" : "", params.mesmer_image_mpp ? "--image-mpp ${params.mesmer_image_mpp}" : "", @@ -135,8 +132,6 @@ process { withName: "CELLPOSE" { singularity.runOptions = "--bind $HOME:$HOME" ext.when = { params.segmentation_method.split(',').contains('cellpose') } - memory = "16GB" - cpus = 8 ext.args = [ "", "--channel_axis 0", "--no_npy", From 12fd24bfae28b05674c5f7e63e75e81ec268262b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Tue, 28 Nov 2023 21:43:42 +0000 Subject: [PATCH 069/149] Filename overwrites for mindagap and spot2cell fixed --- CHANGELOG.md | 10 ++++++++++ bin/spot2cell.py | 12 +++++++++--- conf/modules.config | 19 ++++++++++++++++++- modules/local/spot2cell.nf | 8 ++++++-- tests/main.nf.test | 19 +++++++++---------- tests/main.nf.test.snap | 24 ++++++++++++------------ 6 files changed, 64 insertions(+), 28 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 35e72e9..14ba61e 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -3,6 +3,16 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/) and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html). +## v1.0.1dev - [2023.11.28.] + +Fixed file naming schema for mindagap and spot2cell. + +### `Fixed` + +- Mindagap outputs, in case the filenames were the same, would overwrite each other. +- spot2cell outputs, in case the filenames and segmentation method were the same, would overwrite each other. +- removed hardcoded memory requirement for CREATEILASTIKTRAININGSUBSET + ## v1.0.1dev - [2023.11.24.] Added first nf-tests for the pipeline. diff --git a/bin/spot2cell.py b/bin/spot2cell.py index eb218b3..cb9680c 100755 --- a/bin/spot2cell.py +++ b/bin/spot2cell.py @@ -112,6 +112,7 @@ def assign_spots2cell(spot_table, cell_mask): parser.add_argument("-s", "--spot_table", help="Spot table to project.") parser.add_argument("-c", "--cell_mask", help="Sample ID.") parser.add_argument("--tag", type=str, help="Additional tag to append to filename") + parser.add_argument("--output",type=str,help="Output path") args = parser.parse_args() @@ -124,6 +125,11 @@ def assign_spots2cell(spot_table, cell_mask): gene_counts_df, background = assign_spots2cell(spot_data, cell_mask) - basename = os.path.basename(args.spot_table) - basename = os.path.splitext(basename)[0] - gene_counts_df.to_csv(f"{basename}.{args.tag}.cellxgene.csv", sep=",", header=True, index=False) + if args.output: + outpath = args.output + + else: + basename = os.path.basename(args.spot_table) + basename = os.path.splitext(basename)[0] + outpath = f"{basename}.{args.tag}.cellxgene.csv" + gene_counts_df.to_csv(outpath, sep=",", header=True, index=False) diff --git a/conf/modules.config b/conf/modules.config index 27a6329..97cbc5a 100644 --- a/conf/modules.config +++ b/conf/modules.config @@ -53,12 +53,30 @@ process { ext.args = [ "", params.tilesize ? "-xt ${params.tilesize}" : "" ].join(" ").trim() + publishDir = [ + path: { "${params.outdir}/mindagap" }, + pattern: "*.{tiff,tif}", + saveAs: { filename -> "${meta.id}_$filename" } + ] } withName: "MINDAGAP_DUPLICATEFINDER" { ext.args = [ "", params.tilesize ? "${params.tilesize}" : "" ].join(" ").trim() + publishDir = [ + path: { "${params.outdir}/mindagap" }, + pattern: "*.{tsv,txt}", + saveAs: { filename -> "${meta.id}_$filename" } + ] + } + + withName: "SPOT2CELL" { + publishDir = [ + path: { "${params.outdir}/spot2cell" }, + pattern: "*.csv", + saveAs: { filename -> "cellxgene_$filename" } + ] } withName: "CREATETRAININGTIFF" { @@ -90,7 +108,6 @@ process { } withName: "CREATEILASTIKTRAININGSUBSET" { - memory = "16GB" publishDir = [ path: { "${params.outdir}/training_subset/hdf5" } ] diff --git a/modules/local/spot2cell.nf b/modules/local/spot2cell.nf index 7b8e3d8..b1a65cb 100644 --- a/modules/local/spot2cell.nf +++ b/modules/local/spot2cell.nf @@ -11,16 +11,20 @@ process SPOT2CELL{ val(tag) output: - tuple val(meta), path("*cellxgene.csv"), emit: cellxgene_table + tuple val(meta), path("*.csv"), emit: cellxgene_table when: task.ext.when == null || task.ext.when script: + def args = task.ext.args ?: '' + def prefix = task.ext.prefix ?: tag ? "${meta.id}_${tag}" : "${meta.id}" + """ spot2cell.py \ --spot_table ${spot_table} \ --cell_mask ${cell_mask} \ - --tag ${tag} + --tag ${tag} \ + --output ${prefix}.csv """ } diff --git a/tests/main.nf.test b/tests/main.nf.test index 1c7d90f..d44fdcf 100644 --- a/tests/main.nf.test +++ b/tests/main.nf.test @@ -21,12 +21,12 @@ nextflow_pipeline { then { assert workflow.success assert snapshot( - path("$outputDir/mindagap/nuclear_gridfilled.tiff"), - path("$outputDir/mindagap/spots_markedDups.txt"), + path("$outputDir/mindagap/nuc_only_nuclear_gridfilled.tiff"), + path("$outputDir/mindagap/nuc_only_spots_markedDups.txt"), path("$outputDir/segmentation/cellpose/nuc_only_cellpose_mask.tif"), path("$outputDir/segmentation/mesmer/nuc_only_mesmer_mask.tif"), - path("$outputDir/spot2cell/spots_markedDups.cellpose.cellxgene.csv"), - path("$outputDir/spot2cell/spots_markedDups.mesmer.cellxgene.csv"), + path("$outputDir/spot2cell/cellxgene_nuc_only_cellpose.csv"), + path("$outputDir/spot2cell/cellxgene_nuc_only_mesmer.csv"), path("$outputDir/molcart_qc/nuc_only.cellpose.spot_QC.csv"), path("$outputDir/molcart_qc/nuc_only.mesmer.spot_QC.csv") ).match() @@ -49,12 +49,12 @@ nextflow_pipeline { then { assert workflow.success assert snapshot( - path("$outputDir/mindagap/membrane_gridfilled.tiff"), - path("$outputDir/mindagap/spots_markedDups.txt"), + path("$outputDir/mindagap/mem_only_membrane_gridfilled.tiff"), + path("$outputDir/mindagap/mem_only_spots_markedDups.txt"), path("$outputDir/segmentation/cellpose/mem_only_cellpose_mask.tif"), path("$outputDir/segmentation/mesmer/mem_only_mesmer_mask.tif"), - path("$outputDir/spot2cell/spots_markedDups.cellpose.cellxgene.csv"), - path("$outputDir/spot2cell/spots_markedDups.mesmer.cellxgene.csv"), + path("$outputDir/spot2cell/cellxgene_mem_only_cellpose.csv"), + path("$outputDir/spot2cell/cellxgene_mem_only_mesmer.csv"), path("$outputDir/stack/mem_only.stack.ome.tif"), path("$outputDir/molcart_qc/mem_only.cellpose.spot_QC.csv"), path("$outputDir/molcart_qc/mem_only.mesmer.spot_QC.csv"), @@ -83,7 +83,7 @@ nextflow_pipeline { then { assert workflow.success assert snapshot( - path("$outputDir/mindagap/nuclear_gridfilled.tiff"), + path("$outputDir/mindagap/nuc_only_nuclear_gridfilled.tiff"), ).match() assert file("$outputDir/clahe/nuc_only_0.clahe.tiff").exists() assert file("$outputDir/training_subset/hdf5/nuc_only_0.clahe_crop0.hdf5").exists() @@ -94,5 +94,4 @@ nextflow_pipeline { assert file("$outputDir/training_subset/tiff/nuc_only_0.clahe.crop_overview.png").exists() } } - } diff --git a/tests/main.nf.test.snap b/tests/main.nf.test.snap index a3696ac..2aee6fa 100644 --- a/tests/main.nf.test.snap +++ b/tests/main.nf.test.snap @@ -1,35 +1,35 @@ { "Two channels, mesmer and cellpose, with clahe": { "content": [ - "membrane_gridfilled.tiff:md5,6e24160d758468d2de07ca200dfb62c2", - "spots_markedDups.txt:md5,4562caad05850d7dd7b6e9235e068a8b", + "mem_only_membrane_gridfilled.tiff:md5,6e24160d758468d2de07ca200dfb62c2", + "mem_only_spots_markedDups.txt:md5,4562caad05850d7dd7b6e9235e068a8b", "mem_only_cellpose_mask.tif:md5,590591f541b6d3f17810cd44dd71b252", "mem_only_mesmer_mask.tif:md5,6f8c792ccc4cca97b5696990fb4e3801", - "spots_markedDups.cellpose.cellxgene.csv:md5,f063c1ce5e93e1e73431af36c6bc1e79", - "spots_markedDups.mesmer.cellxgene.csv:md5,f54f2af6ce874e96f7973504bddd9bc9", + "cellxgene_mem_only_cellpose.csv:md5,f063c1ce5e93e1e73431af36c6bc1e79", + "cellxgene_mem_only_mesmer.csv:md5,f54f2af6ce874e96f7973504bddd9bc9", "mem_only.stack.ome.tif:md5,d8659ad7bf017fecc795b855785b74be", "mem_only.cellpose.spot_QC.csv:md5,4b24962d8eae2579eab419179212fd27", "mem_only.mesmer.spot_QC.csv:md5,d5c302ff76e8ce7a8d212f6d818cedbc" ], - "timestamp": "2023-11-24T22:58:21.520372411" + "timestamp": "2023-11-28T21:37:13.813957843" }, "Nuclear channel, mesmer and cellpose, without clahe": { "content": [ - "nuclear_gridfilled.tiff:md5,123763d54f05b2274690b3b84f9690b1", - "spots_markedDups.txt:md5,4562caad05850d7dd7b6e9235e068a8b", + "nuc_only_nuclear_gridfilled.tiff:md5,123763d54f05b2274690b3b84f9690b1", + "nuc_only_spots_markedDups.txt:md5,4562caad05850d7dd7b6e9235e068a8b", "nuc_only_cellpose_mask.tif:md5,2784d8c6683ad80c24d8df4121e1128f", "nuc_only_mesmer_mask.tif:md5,e9719f53651b4bf76a37e9374db7f4e4", - "spots_markedDups.cellpose.cellxgene.csv:md5,0610a8713457c28acf1bc4c298bee8e3", - "spots_markedDups.mesmer.cellxgene.csv:md5,13d8f4fb05a400c94866404fc424a8e8", + "cellxgene_nuc_only_cellpose.csv:md5,0610a8713457c28acf1bc4c298bee8e3", + "cellxgene_nuc_only_mesmer.csv:md5,13d8f4fb05a400c94866404fc424a8e8", "nuc_only.cellpose.spot_QC.csv:md5,3fa7f7d1f87d37428907a77236893330", "nuc_only.mesmer.spot_QC.csv:md5,9779af541ceae4a0fe0ae20d75db2bee" ], - "timestamp": "2023-11-24T16:28:34.810940773" + "timestamp": "2023-11-28T21:36:07.153599523" }, "Create training subset": { "content": [ - "nuclear_gridfilled.tiff:md5,123763d54f05b2274690b3b84f9690b1" + "nuc_only_nuclear_gridfilled.tiff:md5,123763d54f05b2274690b3b84f9690b1" ], - "timestamp": "2023-11-24T23:02:32.575286676" + "timestamp": "2023-11-28T21:40:40.925034909" } } \ No newline at end of file From 007afe4022b6a34b2d6e60559235f0f1502cc735 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Tue, 28 Nov 2023 22:06:18 +0000 Subject: [PATCH 070/149] Mesmer does not require stacks --- CHANGELOG.md | 3 ++- workflows/molkart.nf | 10 ++++++++-- 2 files changed, 10 insertions(+), 3 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 14ba61e..e5af3c7 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -5,13 +5,14 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 ## v1.0.1dev - [2023.11.28.] -Fixed file naming schema for mindagap and spot2cell. +Fixed file naming schema for mindagap and spot2cell. If only mesmer is used for segmentation, create stack does not have to be run. ### `Fixed` - Mindagap outputs, in case the filenames were the same, would overwrite each other. - spot2cell outputs, in case the filenames and segmentation method were the same, would overwrite each other. - removed hardcoded memory requirement for CREATEILASTIKTRAININGSUBSET +- if only mesmer is used for segmentation, create stack does not have to be run. ## v1.0.1dev - [2023.11.24.] diff --git a/workflows/molkart.nf b/workflows/molkart.nf index 96edee9..7baba71 100644 --- a/workflows/molkart.nf +++ b/workflows/molkart.nf @@ -139,8 +139,14 @@ workflow MOLKART { // // MODULE: Stack channels if membrane image provided for segmentation // - CREATE_STACK(create_stack_in) - stack_mix = CREATE_STACK.out.stack.mix(no_stack) + if (params.segmentation_method.split(',').contains('cellpose') || + params.segmentation_method.split(',').contains('ilastik') || + params.create_training_subset){ + CREATE_STACK(create_stack_in) + stack_mix = CREATE_STACK.out.stack.mix(no_stack) + } else { + stack_mix = no_stack + } if ( params.create_training_subset ) { // Create subsets of the image for training an ilastik model From d9b8149d763e242660942c02863a817b17f2072d Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Wed, 29 Nov 2023 08:05:38 +0000 Subject: [PATCH 071/149] Ran Python black on spot2cell.py --- bin/spot2cell.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/bin/spot2cell.py b/bin/spot2cell.py index cb9680c..0f786d8 100755 --- a/bin/spot2cell.py +++ b/bin/spot2cell.py @@ -112,7 +112,7 @@ def assign_spots2cell(spot_table, cell_mask): parser.add_argument("-s", "--spot_table", help="Spot table to project.") parser.add_argument("-c", "--cell_mask", help="Sample ID.") parser.add_argument("--tag", type=str, help="Additional tag to append to filename") - parser.add_argument("--output",type=str,help="Output path") + parser.add_argument("--output", type=str, help="Output path") args = parser.parse_args() From 1fa06a933dfdf1c02e21ce48919fa24d57e4f885 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Thu, 30 Nov 2023 16:59:02 +0000 Subject: [PATCH 072/149] CLAHE changes --- CHANGELOG.md | 21 +++++ bin/apply_clahe.dask.py | 162 ++++++++++++++++++++---------------- conf/modules.config | 18 ++-- modules/local/clahe_dask.nf | 18 ++-- nextflow.config | 4 +- nextflow_schema.json | 28 ++++--- tests/main.nf.test | 29 +++---- tests/main.nf.test.snap | 3 +- workflows/molkart.nf | 7 +- 9 files changed, 170 insertions(+), 120 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index e5af3c7..fc1de80 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -3,6 +3,27 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/) and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html). +## v1.0.1dev - [2023.11.30.] + +Changes to clahe - more nf-core compliant, script change, versions, updated tests. + +### `Added` + +- Clahe now outputs versions +- --clahe_pyramid_tile parameter (hidden) + +### `Fixed` + +- clahe local module now follows nf-core guidelines with output naming defined through ext.prefix +- In all cases, the same writer will be used for clahe now +- Fixed CLAHE metadata +- renamed process from CLAHE_DASK to CLAHE +- renamed tilesize parameter to mindagap_tilesize for clarity + +### `Removed` + +- clahe_skip_pyramid parameter + ## v1.0.1dev - [2023.11.28.] Fixed file naming schema for mindagap and spot2cell. If only mesmer is used for segmentation, create stack does not have to be run. diff --git a/bin/apply_clahe.dask.py b/bin/apply_clahe.dask.py index 4d9f7ba..2514fdb 100755 --- a/bin/apply_clahe.dask.py +++ b/bin/apply_clahe.dask.py @@ -42,32 +42,33 @@ def get_args(): # Sections inputs = parser.add_argument_group(title="Required Input", description="Path to required input file") - inputs.add_argument("-r", "--raw", dest="raw", action="store", required=True, help="File path to input image.") + inputs.add_argument("-r", "--input", dest="input", action="store", required=True, help="File path to input image.") inputs.add_argument("-o", "--output", dest="output", action="store", required=True, help="Path to output image.") inputs.add_argument( - "-c", "--channel", dest="channel", action="store", required=True, help="Channel on which CLAHE will be applied" + "--cliplimit", dest="clip", action="store", required=True, type=float, default=0.01, help="Clip Limit for CLAHE" ) - inputs.add_argument("-l", "--cliplimit", dest="clip", action="store", required=True, help="Clip Limit for CLAHE") inputs.add_argument( - "--kernel", dest="kernel", action="store", required=False, default=None, help="Kernel size for CLAHE" + "--kernel", dest="kernel", action="store", required=False, type=int, default=25, help="Kernel size for CLAHE" ) inputs.add_argument( - "-g", "--nbins", dest="nbins", action="store", required=False, default=256, help="Number of bins for CLAHE" + "--nbins", dest="nbins", action="store", required=False, type=int, default=256, help="Number of bins for CLAHE" ) - inputs.add_argument("-p", "--pixel-size", dest="pixel_size", action="store", required=True, help="Image pixel size") inputs.add_argument( - "--skip_pyramid", - dest="skip_pyramid", - action="store_true", - default=False, - help="Should pyramid creation be skipped", + "-p", "--pixel-size", dest="pixel_size", action="store", type=float, required=False, help="Image pixel size" ) - + inputs.add_argument( + "--tile-size", + dest="tile_size", + action="store", + type=int, + default=1072, + help="Tile size for pyramid generation (must be divisible by 16)", + ) + inputs.add_argument("--version", action="version", version="0.1.0") arg = parser.parse_args() # Standardize paths - arg.raw = abspath(arg.raw) - arg.channel = int(arg.channel) + arg.input = abspath(arg.input) arg.clip = float(arg.clip) arg.pixel_size = float(arg.pixel_size) arg.nbins = int(arg.nbins) @@ -113,78 +114,95 @@ def subres_tiles(level, level_full_shapes, tile_shapes, outpath, scale): yield a +def detect_pixel_size(img_path, pixel_size=None): + if pixel_size is None: + print("Pixel size overwrite not specified") + try: + metadata = ome_types.from_tiff(img_path) + pixel_size = metadata.images[0].pixels.physical_size_x + except Exception as err: + print(err) + print("Pixel size detection using ome-types failed") + pixel_size = None + return pixel_size + + def main(args): - print(f"Head directory = {args.raw}") - print( - f"Channel = {args.channel}, ClipLimit = {args.clip}, nbins = {args.nbins}, kernel_size = {args.kernel}, pixel_size = {args.pixel_size}" - ) + _version = "0.1.0" + print(f"Head directory = {args.input}") + print(f"ClipLimit = {args.clip}, nbins = {args.nbins}, kernel_size = {args.kernel}, pixel_size = {args.pixel_size}") # clahe = cv2.createCLAHE(clipLimit = int(args.clip), tileGridSize=tuple(map(int, args.grid))) - img_raw = AI.AICSImage(args.raw) - img_dask = img_raw.get_image_dask_data("CYX").astype("uint16") - adapted = img_dask[args.channel].compute() / 65535 + img_in = AI.AICSImage(args.input) + img_dask = img_in.get_image_dask_data("CYX").astype("uint16") + adapted = img_dask[0].compute() / 65535 adapted = ( equalize_adapthist(adapted, kernel_size=args.kernel, clip_limit=args.clip, nbins=args.nbins) * 65535 ).astype("uint16") - img_dask[args.channel] = adapted + img_dask[0] = adapted # construct levels - tile_size = 1024 + tile_size = args.tile_size scale = 2 - pixel_size = args.pixel_size - - if args.skip_pyramid: - with tifffile.TiffWriter(args.output, ome=True, bigtiff=True) as tiff: - tiff.write( - data=img_dask, - shape=img_dask.shape, - dtype=img_dask.dtype, - resolution=(10000 / pixel_size, 10000 / pixel_size, "centimeter"), - ) - else: - dtype = img_dask.dtype - base_shape = img_dask[0].shape - num_channels = img_dask.shape[0] - num_levels = (np.ceil(np.log2(max(base_shape) / tile_size)) + 1).astype(int) - factors = 2 ** np.arange(num_levels) - shapes = (np.ceil(np.array(base_shape) / factors[:, None])).astype(int) - - print("Pyramid level sizes: ") - for i, shape in enumerate(shapes): - print(f" level {i+1}: {format_shape(shape)}", end="") - if i == 0: - print("(original size)", end="") - print() + pixel_size = detect_pixel_size(args.input, args.pixel_size) + if pixel_size is None: + pixel_size = 1 + + dtype = img_dask.dtype + base_shape = img_dask[0].shape + num_channels = img_dask.shape[0] + num_levels = (np.ceil(np.log2(max(1, max(base_shape) / tile_size))) + 1).astype(int) + factors = 2 ** np.arange(num_levels) + shapes = (np.ceil(np.array(base_shape) / factors[:, None])).astype(int) + + print("Pyramid level sizes: ") + for i, shape in enumerate(shapes): + print(f" level {i+1}: {format_shape(shape)}", end="") + if i == 0: + print("(original size)", end="") print() - print(shapes) - - level_full_shapes = [] - for shape in shapes: - level_full_shapes.append((num_channels, shape[0], shape[1])) - level_shapes = shapes - tip_level = np.argmax(np.all(level_shapes < tile_size, axis=1)) - tile_shapes = [(tile_size, tile_size) if i <= tip_level else None for i in range(len(level_shapes))] - - # write pyramid - with tifffile.TiffWriter(args.output, ome=True, bigtiff=True) as tiff: + print() + print(shapes) + + level_full_shapes = [] + for shape in shapes: + level_full_shapes.append((num_channels, shape[0], shape[1])) + level_shapes = shapes + tip_level = np.argmax(np.all(level_shapes < tile_size, axis=1)) + tile_shapes = [(tile_size, tile_size) if i <= tip_level else None for i in range(len(level_shapes))] + + software = f"molkart_clahe {_version}" + pixel_size = pixel_size + metadata = { + "Creator": software, + "Pixels": { + "PhysicalSizeX": pixel_size, + "PhysicalSizeXUnit": "\u00b5m", + "PhysicalSizeY": pixel_size, + "PhysicalSizeYUnit": "\u00b5m", + }, + } + + # write pyramid + with tifffile.TiffWriter(args.output, ome=True, bigtiff=True) as tiff: + tiff.write( + data=img_dask, + metadata=metadata, + shape=level_full_shapes[0], + subifds=int(num_levels - 1), + dtype=dtype, + resolution=(10000 / pixel_size, 10000 / pixel_size, "centimeter"), + tile=tile_shapes[0], + ) + for level, (shape, tile_shape) in enumerate(zip(level_full_shapes[1:], tile_shapes[1:]), 1): tiff.write( - data=img_dask, - shape=level_full_shapes[0], - subifds=int(num_levels - 1), + data=subres_tiles(level, level_full_shapes, tile_shapes, args.output, scale), + shape=shape, + subfiletype=1, dtype=dtype, - resolution=(10000 / pixel_size, 10000 / pixel_size, "centimeter"), - tile=tile_shapes[0], + tile=tile_shape, ) - for level, (shape, tile_shape) in enumerate(zip(level_full_shapes[1:], tile_shapes[1:]), 1): - tiff.write( - data=subres_tiles(level, level_full_shapes, tile_shapes, args.output, scale), - shape=shape, - subfiletype=1, - dtype=dtype, - tile=tile_shape, - ) - # tifffile.tiffcomment(args.output, to_xml(metadata)) print() diff --git a/conf/modules.config b/conf/modules.config index 97cbc5a..f50e74e 100644 --- a/conf/modules.config +++ b/conf/modules.config @@ -51,7 +51,7 @@ process { withName: "MINDAGAP_MINDAGAP" { ext.args = [ "", - params.tilesize ? "-xt ${params.tilesize}" : "" + params.mindagap_tilesize ? "-xt ${params.mindagap_tilesize}" : "" ].join(" ").trim() publishDir = [ path: { "${params.outdir}/mindagap" }, @@ -62,7 +62,7 @@ process { withName: "MINDAGAP_DUPLICATEFINDER" { ext.args = [ "", - params.tilesize ? "${params.tilesize}" : "" + params.mindagap_tilesize ? "${params.mindagap_tilesize}" : "" ].join(" ").trim() publishDir = [ path: { "${params.outdir}/mindagap" }, @@ -120,15 +120,15 @@ process { ].join(" ").trim() } - withName: "CLAHE_DASK" { + withName: "CLAHE" { + ext.prefix = { "${meta.id}_${image.name.split("\\.")[0]}_clahe" } ext.when = { !params.skip_clahe } ext.args = [ "", - "--channel 0", - params.clahe_cliplimit ? "--cliplimit ${params.clahe_cliplimit}" : "", - params.clahe_nbins ? "--nbins ${params.clahe_nbins}" : "", - params.clahe_pixel_size ? "--pixel-size ${params.clahe_pixel_size}" : "", - params.clahe_kernel ? "--kernel ${params.clahe_kernel}" : "", - params.clahe_skip_pyramid ? "--skip_pyramid" : "" + params.clahe_pyramid_tile ? "--tile-size ${params.clahe_pyramid_tile}" : "", + params.clahe_cliplimit ? "--cliplimit ${params.clahe_cliplimit}" : "", + params.clahe_nbins ? "--nbins ${params.clahe_nbins}" : "", + params.clahe_pixel_size ? "--pixel-size ${params.clahe_pixel_size}" : "", + params.clahe_kernel ? "--kernel ${params.clahe_kernel}" : "" ].join(" ").trim() } diff --git a/modules/local/clahe_dask.nf b/modules/local/clahe_dask.nf index 65e83c6..493646b 100644 --- a/modules/local/clahe_dask.nf +++ b/modules/local/clahe_dask.nf @@ -1,6 +1,6 @@ -process CLAHE_DASK{ +process CLAHE{ debug false - tag "Applying CLAHE to $meta.id" + tag "$meta.id" label 'process_low' container 'ghcr.io/schapirolabor/background_subtraction:v0.3.3' @@ -9,19 +9,25 @@ process CLAHE_DASK{ tuple val(meta), path(image) output: - tuple val(meta), path("*.clahe.tiff") , emit: img_clahe + tuple val(meta), path("*.tiff") , emit: img_clahe + path "versions.yml" , emit: versions when: task.ext.when == null || task.ext.when script: def args = task.ext.args ?: '' - def prefix = task.ext.prefix ?: "${meta.id}_${meta.stain}" + def prefix = task.ext.prefix ?: "${meta.id}" """ apply_clahe.dask.py \\ - --raw ${image} \\ - --output ${prefix}.clahe.tiff \\ + --input ${image} \\ + --output ${prefix}.tiff \\ $args + + cat <<-END_VERSIONS > versions.yml + "${task.process}": + molkart_clahe: \$(apply_clahe.dask.py --version) + END_VERSIONS """ } diff --git a/nextflow.config b/nextflow.config index a7610bb..e4c8dec 100644 --- a/nextflow.config +++ b/nextflow.config @@ -29,13 +29,13 @@ params { // Preprocessing command line flags - tilesize = 2144 + mindagap_tilesize = 2144 skip_clahe = false clahe_cliplimit = 0.01 clahe_nbins = 256 clahe_pixel_size = 0.138 clahe_kernel = 25 - clahe_skip_pyramid = false + clahe_pyramid_tile = 1072 // Training subset command line create_training_subset = false diff --git a/nextflow_schema.json b/nextflow_schema.json index e6f7a01..170259d 100644 --- a/nextflow_schema.json +++ b/nextflow_schema.json @@ -57,6 +57,12 @@ "description": "Should cells detected near image edges be excluded.", "fa_icon": "fas fa-border-none" }, + "cellpose_save_flows": { + "type": "boolean", + "description": "Should flow fields from Cellpose be saved?", + "fa_icon": "fas fa-arrows-alt", + "hidden": true + }, "mesmer_image_mpp": { "type": "number", "default": 0.138, @@ -69,12 +75,6 @@ "description": "Compartment to be segmented with Mesmer (nuclear, whole-cell)", "fa_icon": "fas fa-border-all" }, - "cellpose_save_flows": { - "type": "boolean", - "description": "Should flow fields from Cellpose be saved?", - "fa_icon": "fas fa-arrows-alt", - "hidden": true - }, "ilastik_pixel_project": { "type": "string", "description": "Provide ilastik with a pixel classification project to produce probability maps.", @@ -127,17 +127,19 @@ "description": "Specifies whether contrast-limited adaptive histogram equalization should be skipped.", "fa_icon": "fab fa-buromobelexperte" }, - "tilesize": { + "mindagap_tilesize": { "type": "integer", "default": 2144, - "description": "Tile size (distance between gridlines)", - "fa_icon": "fas fa-th" + "description": "Tile size (distance between gridlines) for Mindagap.", + "fa_icon": "fas fa-th", + "hidden": true }, - "clahe_skip_pyramid": { - "type": "boolean", - "description": "Should pyramid generation be skipped for CLAHE", + "clahe_pyramid_tile": { + "type": "integer", + "description": "Tile size used for pyramid generation (must be divisible by 16).", "fa_icon": "fas fa-cubes", - "hidden": true + "hidden": true, + "default": 1072 } } }, diff --git a/tests/main.nf.test b/tests/main.nf.test index d44fdcf..e66a5df 100644 --- a/tests/main.nf.test +++ b/tests/main.nf.test @@ -13,7 +13,7 @@ nextflow_pipeline { input = 'https://raw.githubusercontent.com/nf-core/test-datasets/molkart/test_data/samplesheets/samplesheet_nuclear.csv' outdir = "$outputDir" skip_clahe = true - tilesize = 90 + mindagap_tilesize = 90 segmentation_method = "cellpose,mesmer" } } @@ -40,8 +40,8 @@ nextflow_pipeline { params { input = 'https://raw.githubusercontent.com/nf-core/test-datasets/molkart/test_data/samplesheets/samplesheet_membrane.csv' outdir = "$outputDir" - tilesize = 90 - clahe_skip_pyramid = true + mindagap_tilesize = 90 + clahe_pyramid_tile = 368 segmentation_method = "cellpose,mesmer" } } @@ -50,6 +50,7 @@ nextflow_pipeline { assert workflow.success assert snapshot( path("$outputDir/mindagap/mem_only_membrane_gridfilled.tiff"), + path("$outputDir/mindagap/mem_only_nuclear_gridfilled.tiff"), path("$outputDir/mindagap/mem_only_spots_markedDups.txt"), path("$outputDir/segmentation/cellpose/mem_only_cellpose_mask.tif"), path("$outputDir/segmentation/mesmer/mem_only_mesmer_mask.tif"), @@ -59,8 +60,8 @@ nextflow_pipeline { path("$outputDir/molcart_qc/mem_only.cellpose.spot_QC.csv"), path("$outputDir/molcart_qc/mem_only.mesmer.spot_QC.csv"), ).match() - assert file("$outputDir/clahe/mem_only_0.clahe.tiff").exists() - assert file("$outputDir/clahe/mem_only_1.clahe.tiff").exists() + assert file("$outputDir/clahe/mem_only_membrane_gridfilled_clahe.tiff").exists() + assert file("$outputDir/clahe/mem_only_nuclear_gridfilled_clahe.tiff").exists() assert file("$outputDir/multiqc/multiqc_report.html").exists() } } @@ -71,8 +72,8 @@ nextflow_pipeline { params { input = 'https://raw.githubusercontent.com/nf-core/test-datasets/molkart/test_data/samplesheets/samplesheet_nuclear.csv' outdir = "$outputDir" - tilesize = 90 - clahe_skip_pyramid = true + mindagap_tilesize = 90 + clahe_pyramid_tile = 368 create_training_subset = true crop_amount = 2 crop_size_x = 10 @@ -85,13 +86,13 @@ nextflow_pipeline { assert snapshot( path("$outputDir/mindagap/nuc_only_nuclear_gridfilled.tiff"), ).match() - assert file("$outputDir/clahe/nuc_only_0.clahe.tiff").exists() - assert file("$outputDir/training_subset/hdf5/nuc_only_0.clahe_crop0.hdf5").exists() - assert file("$outputDir/training_subset/hdf5/nuc_only_0.clahe_crop1.hdf5").exists() - assert file("$outputDir/training_subset/hdf5/nuc_only_0.clahe_CropSummary.txt").exists() - assert file("$outputDir/training_subset/tiff/nuc_only_0.clahe_crop0.tiff").exists() - assert file("$outputDir/training_subset/tiff/nuc_only_0.clahe_crop1.tiff").exists() - assert file("$outputDir/training_subset/tiff/nuc_only_0.clahe.crop_overview.png").exists() + assert file("$outputDir/clahe/nuc_only_nuclear_gridfilled_clahe.tiff").exists() + assert file("$outputDir/training_subset/hdf5/nuc_only_nuclear_gridfilled_clahe_crop0.hdf5").exists() + assert file("$outputDir/training_subset/hdf5/nuc_only_nuclear_gridfilled_clahe_crop1.hdf5").exists() + assert file("$outputDir/training_subset/hdf5/nuc_only_nuclear_gridfilled_clahe_CropSummary.txt").exists() + assert file("$outputDir/training_subset/tiff/nuc_only_nuclear_gridfilled_clahe_crop0.tiff").exists() + assert file("$outputDir/training_subset/tiff/nuc_only_nuclear_gridfilled_clahe_crop1.tiff").exists() + assert file("$outputDir/training_subset/tiff/nuc_only_nuclear_gridfilled_clahe.crop_overview.png").exists() } } } diff --git a/tests/main.nf.test.snap b/tests/main.nf.test.snap index 2aee6fa..bd86d65 100644 --- a/tests/main.nf.test.snap +++ b/tests/main.nf.test.snap @@ -2,6 +2,7 @@ "Two channels, mesmer and cellpose, with clahe": { "content": [ "mem_only_membrane_gridfilled.tiff:md5,6e24160d758468d2de07ca200dfb62c2", + "mem_only_nuclear_gridfilled.tiff:md5,123763d54f05b2274690b3b84f9690b1", "mem_only_spots_markedDups.txt:md5,4562caad05850d7dd7b6e9235e068a8b", "mem_only_cellpose_mask.tif:md5,590591f541b6d3f17810cd44dd71b252", "mem_only_mesmer_mask.tif:md5,6f8c792ccc4cca97b5696990fb4e3801", @@ -11,7 +12,7 @@ "mem_only.cellpose.spot_QC.csv:md5,4b24962d8eae2579eab419179212fd27", "mem_only.mesmer.spot_QC.csv:md5,d5c302ff76e8ce7a8d212f6d818cedbc" ], - "timestamp": "2023-11-28T21:37:13.813957843" + "timestamp": "2023-11-30T16:46:18.513521201" }, "Nuclear channel, mesmer and cellpose, without clahe": { "content": [ diff --git a/workflows/molkart.nf b/workflows/molkart.nf index 7baba71..6b16564 100644 --- a/workflows/molkart.nf +++ b/workflows/molkart.nf @@ -35,7 +35,7 @@ ch_multiqc_custom_methods_description = params.multiqc_methods_description ? fil include { CREATETRAININGTIFF } from '../modules/local/createtrainingtiff' include { CREATEILASTIKTRAININGSUBSET } from '../modules/local/createilastiktrainingsubset' include { CREATE_STACK } from '../modules/local/create_stack' -include { CLAHE_DASK } from '../modules/local/clahe_dask' +include { CLAHE } from '../modules/local/clahe_dask' include { MINDAGAP_DUPLICATEFINDER } from '../modules/local/mindagap_duplicatefinder' include { SPOT2CELL } from '../modules/local/spot2cell' include { TIFFH5CONVERT } from '../modules/local/tiffh5convert' @@ -107,8 +107,9 @@ workflow MOLKART { // // currently CLAHE is either applied on all channels, or none. if (!params.skip_clahe) { - CLAHE_DASK(MINDAGAP_MINDAGAP.out.tiff) // TODO : Add local module for testing - CLAHE_DASK.out.img_clahe.set{ map_for_stacks } + CLAHE(MINDAGAP_MINDAGAP.out.tiff) + ch_versions = ch_versions.mix(CLAHE.out.versions) + CLAHE.out.img_clahe.set{ map_for_stacks } } else { MINDAGAP_MINDAGAP.out.tiff.set{ map_for_stacks } } // if clahe should be run, use its output for next step, otherwise, use mindagap output From c39ee20c81118ca0fbc187d88281215896f4009c Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Thu, 30 Nov 2023 17:10:29 +0000 Subject: [PATCH 073/149] updated test.config --- conf/test.config | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/conf/test.config b/conf/test.config index ba5ed84..a01d69f 100644 --- a/conf/test.config +++ b/conf/test.config @@ -21,7 +21,7 @@ params { // Input data input = 'https://raw.githubusercontent.com/nf-core/test-datasets/molkart/test_data/samplesheets/samplesheet_membrane.csv' - tilesize = 90 - clahe_skip_pyramid = true + mindagap_tilesize = 90 + clahe_pyramid_tile = 368 segmentation_method = "cellpose,mesmer" } From 3cd81c683a3cfd4dea52c33e729ace5d67f3d9b8 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Thu, 30 Nov 2023 17:12:39 +0000 Subject: [PATCH 074/149] updated usage.md --- docs/usage.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/usage.md b/docs/usage.md index 65364d0..c94e779 100644 --- a/docs/usage.md +++ b/docs/usage.md @@ -95,13 +95,13 @@ mesmer_image_mpp: 0.138 mesmer_compartment: "whole-cell" ilastik_pixel_project: null ilastik_multicut_project: null -tilesize: 2144 +mindagap_tilesize: 2144 skip_clahe: false clahe_cliplimit: 0.01 clahe_nbins: 256 clahe_pixel_size: 0.138 clahe_kernel: 25 -clahe_skip_pyramid: false +clahe_pyramid_tile: 1072 create_training_subset: false crop_amount: 4 crop_nonzero_fraction: 0.4 From 4e63f0f7efbc2a8f9b139b326b905b1fedbecfe7 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Thu, 30 Nov 2023 17:13:20 +0000 Subject: [PATCH 075/149] updated output.md --- docs/output.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/output.md b/docs/output.md index 7c8d592..d468c82 100644 --- a/docs/output.md +++ b/docs/output.md @@ -41,7 +41,7 @@ The pipeline is built using [Nextflow](https://www.nextflow.io/) and processes d Output files - `clahe/` - - `*.clahe.tiff`: Image with contrast-limited adaptive histogram equalization applied. + - `*_clahe.tiff`: Image with contrast-limited adaptive histogram equalization applied.

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s-w=Htf$yLHzn>ugn?>Kpj`D4T>(kY@Y^z>66W>xhtZ^t)$>j3?16zc11ONa4 literal 0 HcmV?d00001 From 241354de59bf3039a44453cce6fe0f52dbb66ae2 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Tue, 14 Nov 2023 10:32:18 +0000 Subject: [PATCH 057/149] Removed workflow TODO --- README.md | 1 - 1 file changed, 1 deletion(-) diff --git a/README.md b/README.md index 46db397..17bf9ac 100644 --- a/README.md +++ b/README.md @@ -15,7 +15,6 @@ **nf-core/molkart** is a pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH). It takes as input a table of FISH spot positions (x,y,z,gene), a corresponding DAPI image (`tiff` format) and optionally a membrane staining image in the `tiff` format. nf-core/molkart performs end-to-end processing of the data including image processing, QC filtering of spots, cell segmentation, spot-to-cell assignment and reports quality metrics such as the spot assignment rate, average spots per cell and segmentation mask size ranges. -

    From 68bd97ab0295b2b383af4413d2bd8ec39beb1c6d Mon Sep 17 00:00:00 2001 From: Florian Wuennemann Date: Sat, 2 Dec 2023 12:34:15 +0000 Subject: [PATCH 076/149] Replaced local mindagap/duplicatefinder with nf-core module. --- CHANGELOG.md | 12 +++++ modules.json | 5 +++ .../mindagap/duplicatefinder/environment.yml | 7 +++ .../mindagap/duplicatefinder/main.nf} | 6 +-- .../nf-core/mindagap/duplicatefinder/meta.yml | 44 +++++++++++++++++++ .../duplicatefinder/tests/main.nf.test | 34 ++++++++++++++ .../duplicatefinder/tests/main.nf.test.snap | 31 +++++++++++++ .../duplicatefinder/tests/nextflow.config | 7 +++ .../mindagap/duplicatefinder/tests/tags.yml | 2 + .../execution_trace_2023-12-02_12-23-56.txt | 1 + workflows/molkart.nf | 2 +- 11 files changed, 147 insertions(+), 4 deletions(-) create mode 100644 modules/nf-core/mindagap/duplicatefinder/environment.yml rename modules/{local/mindagap_duplicatefinder.nf => nf-core/mindagap/duplicatefinder/main.nf} (83%) create mode 100644 modules/nf-core/mindagap/duplicatefinder/meta.yml create mode 100644 modules/nf-core/mindagap/duplicatefinder/tests/main.nf.test create mode 100644 modules/nf-core/mindagap/duplicatefinder/tests/main.nf.test.snap create mode 100644 modules/nf-core/mindagap/duplicatefinder/tests/nextflow.config create mode 100644 modules/nf-core/mindagap/duplicatefinder/tests/tags.yml create mode 100644 null/pipeline_info/execution_trace_2023-12-02_12-23-56.txt diff --git a/CHANGELOG.md b/CHANGELOG.md index fc1de80..7370601 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -3,6 +3,18 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/) and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html). +## v1.0.1dev - [2023.12.02] + +Replaced local module for mindagap/duplicatefinder with nf-core module. + +### `Added` + +- installed mindagap/duplicatefinder via nf-core tools + +### `Removed` + +- removed local mindagap_duplicatefinder.nf in local modules + ## v1.0.1dev - [2023.11.30.] Changes to clahe - more nf-core compliant, script change, versions, updated tests. diff --git a/modules.json b/modules.json index 1bb0a68..fcd0ff1 100644 --- a/modules.json +++ b/modules.json @@ -30,6 +30,11 @@ "git_sha": "516189e968feb4ebdd9921806988b4c12b4ac2dc", "installed_by": ["modules"] }, + "mindagap/duplicatefinder": { + "branch": "master", + "git_sha": "cdc42519bf7d6d2cac9b5f14cb56e0060477c69c", + "installed_by": ["modules"] + }, "mindagap/mindagap": { "branch": "master", "git_sha": "8fc1d24c710ebe1d5de0f2447ec9439fd3d9d66a", diff --git a/modules/nf-core/mindagap/duplicatefinder/environment.yml b/modules/nf-core/mindagap/duplicatefinder/environment.yml new file mode 100644 index 0000000..ad98152 --- /dev/null +++ b/modules/nf-core/mindagap/duplicatefinder/environment.yml @@ -0,0 +1,7 @@ +name: "MINDAGAP_DUPLICATEFINDER" +channels: + - conda-forge + - bioconda + - defaults +dependencies: + - "bioconda::mindagap=0.0.2" diff --git a/modules/local/mindagap_duplicatefinder.nf b/modules/nf-core/mindagap/duplicatefinder/main.nf similarity index 83% rename from modules/local/mindagap_duplicatefinder.nf rename to modules/nf-core/mindagap/duplicatefinder/main.nf index 3a11015..ad7ce5b 100644 --- a/modules/local/mindagap_duplicatefinder.nf +++ b/modules/nf-core/mindagap/duplicatefinder/main.nf @@ -5,20 +5,20 @@ process MINDAGAP_DUPLICATEFINDER { conda "bioconda::mindagap=0.0.2" container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? 'https://depot.galaxyproject.org/singularity/mindagap:0.0.2--pyhdfd78af_1': - 'quay.io/biocontainers/mindagap:0.0.2--pyhdfd78af_1' }" + 'biocontainers/mindagap:0.0.2--pyhdfd78af_1' }" input: tuple val(meta), path(spot_table) output: tuple val(meta), path("*markedDups.txt"), emit: marked_dups_spots - path "versions.yml" , emit: versions + path "versions.yml" , emit: versions when: task.ext.when == null || task.ext.when script: - def args = task.ext.args ?: '' + def args = task.ext.args ?: '' def prefix = task.ext.prefix ?: "${meta.id}" """ duplicate_finder.py \\ diff --git a/modules/nf-core/mindagap/duplicatefinder/meta.yml b/modules/nf-core/mindagap/duplicatefinder/meta.yml new file mode 100644 index 0000000..b92d419 --- /dev/null +++ b/modules/nf-core/mindagap/duplicatefinder/meta.yml @@ -0,0 +1,44 @@ +name: "MINDAGAP_DUPLICATEFINDER" +description: marks duplicate spots along gridline edges. +keywords: + - imaging + - resolve_bioscience + - spatial_transcriptomics +tools: + - "mindagap": + description: "Takes a single panorama image and fills the empty grid lines with neighbour-weighted values." + homepage: "https://github.com/ViriatoII/MindaGap/blob/main/README.md" + documentation: "https://github.com/ViriatoII/MindaGap/blob/main/README.md" + tool_dev_url: "https://github.com/ViriatoII/MindaGap" + licence: ["BSD 3-clause License"] + +input: + - meta: + type: map + description: | + Groovy Map containing sample information + e.g. [ id:'test' ] + - spot_table: + type: file + description: tsv file containing one spot per row with order x,y,z,gene without column header. + pattern: "*.{tsv,txt}" + +output: + - meta: + type: map + description: | + Groovy Map containing sample information + e.g. [ id:'test' ] + - versions: + type: file + description: File containing software versions + pattern: "versions.yml" + - marked_dups_spots: + type: file + description: tsv file containing one spot per row, with duplicated spots labeled with "Duplicated" in their gene column. + pattern: "*.{markedDups.txt}" + +authors: + - "@FloWuenne" +maintainers: + - "@FloWuenne" diff --git a/modules/nf-core/mindagap/duplicatefinder/tests/main.nf.test b/modules/nf-core/mindagap/duplicatefinder/tests/main.nf.test new file mode 100644 index 0000000..d43a7de --- /dev/null +++ b/modules/nf-core/mindagap/duplicatefinder/tests/main.nf.test @@ -0,0 +1,34 @@ +nextflow_process { + + name "Test Process MINDAGAP_DUPLICATEFINDER" + script "../main.nf" + config "./nextflow.config" + process "MINDAGAP_DUPLICATEFINDER" + tag "modules" + tag "modules_nfcore" + tag "mindagap" + tag "mindagap/duplicatefinder" + + test("test_mindagap_duplicatefinder_spots") { + + when { + process { + """ + input[0] = [ + [ id:'test'], // meta map + file('https://raw.githubusercontent.com/nf-core/test-datasets/molkart/test_data/input_data/spots.txt') + ] + """ + } + } + + then { + assertAll( + { assert process.success }, + { assert snapshot(process.out).match() } + ) + } + + } + +} diff --git a/modules/nf-core/mindagap/duplicatefinder/tests/main.nf.test.snap b/modules/nf-core/mindagap/duplicatefinder/tests/main.nf.test.snap new file mode 100644 index 0000000..a1af5c2 --- /dev/null +++ b/modules/nf-core/mindagap/duplicatefinder/tests/main.nf.test.snap @@ -0,0 +1,31 @@ +{ + "test_mindagap_duplicatefinder_spots": { + "content": [ + { + "0": [ + [ + { + "id": "test" + }, + "spots_markedDups.txt:md5,4562caad05850d7dd7b6e9235e068a8b" + ] + ], + "1": [ + "versions.yml:md5,ae112b853ec32ee1c5eecaf421d01003" + ], + "marked_dups_spots": [ + [ + { + "id": "test" + }, + "spots_markedDups.txt:md5,4562caad05850d7dd7b6e9235e068a8b" + ] + ], + "versions": [ + "versions.yml:md5,ae112b853ec32ee1c5eecaf421d01003" + ] + } + ], + "timestamp": "2023-11-30T22:56:20.101101751" + } +} \ No newline at end of file diff --git a/modules/nf-core/mindagap/duplicatefinder/tests/nextflow.config b/modules/nf-core/mindagap/duplicatefinder/tests/nextflow.config new file mode 100644 index 0000000..99963ab --- /dev/null +++ b/modules/nf-core/mindagap/duplicatefinder/tests/nextflow.config @@ -0,0 +1,7 @@ +process { + + withName: "MINDAGAP_DUPLICATEFINDER" { + ext.args = '90' + } + +} diff --git a/modules/nf-core/mindagap/duplicatefinder/tests/tags.yml b/modules/nf-core/mindagap/duplicatefinder/tests/tags.yml new file mode 100644 index 0000000..6f4a474 --- /dev/null +++ b/modules/nf-core/mindagap/duplicatefinder/tests/tags.yml @@ -0,0 +1,2 @@ +mindagap/duplicatefinder: + - modules/nf-core/mindagap/duplicatefinder/** diff --git a/null/pipeline_info/execution_trace_2023-12-02_12-23-56.txt b/null/pipeline_info/execution_trace_2023-12-02_12-23-56.txt new file mode 100644 index 0000000..6b739ac --- /dev/null +++ b/null/pipeline_info/execution_trace_2023-12-02_12-23-56.txt @@ -0,0 +1 @@ +task_id hash native_id name status exit submit duration realtime %cpu peak_rss peak_vmem rchar wchar diff --git a/workflows/molkart.nf b/workflows/molkart.nf index 6b16564..b48cceb 100644 --- a/workflows/molkart.nf +++ b/workflows/molkart.nf @@ -36,7 +36,7 @@ include { CREATETRAININGTIFF } from '../modules/local/createtrainingtif include { CREATEILASTIKTRAININGSUBSET } from '../modules/local/createilastiktrainingsubset' include { CREATE_STACK } from '../modules/local/create_stack' include { CLAHE } from '../modules/local/clahe_dask' -include { MINDAGAP_DUPLICATEFINDER } from '../modules/local/mindagap_duplicatefinder' +include { MINDAGAP_DUPLICATEFINDER } from '../modules/nf-core/mindagap/duplicatefinder/main' include { SPOT2CELL } from '../modules/local/spot2cell' include { TIFFH5CONVERT } from '../modules/local/tiffh5convert' include { MOLCART_QC } from '../modules/local/molcart_qc' From 610b1c83d00a800780633c6efefd21524c0530fd Mon Sep 17 00:00:00 2001 From: Florian Wuennemann Date: Sun, 3 Dec 2023 15:27:09 +0100 Subject: [PATCH 077/149] Delete null/pipeline_info/execution_trace_2023-12-02_12-23-56.txt Removed execution_trace file accidentally left over. --- null/pipeline_info/execution_trace_2023-12-02_12-23-56.txt | 1 - 1 file changed, 1 deletion(-) delete mode 100644 null/pipeline_info/execution_trace_2023-12-02_12-23-56.txt diff --git a/null/pipeline_info/execution_trace_2023-12-02_12-23-56.txt b/null/pipeline_info/execution_trace_2023-12-02_12-23-56.txt deleted file mode 100644 index 6b739ac..0000000 --- a/null/pipeline_info/execution_trace_2023-12-02_12-23-56.txt +++ /dev/null @@ -1 +0,0 @@ -task_id hash native_id name status exit submit duration realtime %cpu peak_rss peak_vmem rchar wchar From cdabd16867773cec5e06acf220fb75b518717678 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= <86408271+kbestak@users.noreply.github.com> Date: Mon, 4 Dec 2023 09:36:04 +0000 Subject: [PATCH 078/149] Moved duplicatefinder to nf-core modules section --- workflows/molkart.nf | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/workflows/molkart.nf b/workflows/molkart.nf index b48cceb..9ff72f4 100644 --- a/workflows/molkart.nf +++ b/workflows/molkart.nf @@ -36,7 +36,6 @@ include { CREATETRAININGTIFF } from '../modules/local/createtrainingtif include { CREATEILASTIKTRAININGSUBSET } from '../modules/local/createilastiktrainingsubset' include { CREATE_STACK } from '../modules/local/create_stack' include { CLAHE } from '../modules/local/clahe_dask' -include { MINDAGAP_DUPLICATEFINDER } from '../modules/nf-core/mindagap/duplicatefinder/main' include { SPOT2CELL } from '../modules/local/spot2cell' include { TIFFH5CONVERT } from '../modules/local/tiffh5convert' include { MOLCART_QC } from '../modules/local/molcart_qc' @@ -56,6 +55,7 @@ include { MOLCART_QC } from '../modules/local/molcart_qc' // include { MULTIQC } from '../modules/nf-core/multiqc/main' include { CUSTOM_DUMPSOFTWAREVERSIONS } from '../modules/nf-core/custom/dumpsoftwareversions/main' +include { MINDAGAP_DUPLICATEFINDER } from '../modules/nf-core/mindagap/duplicatefinder/main' include { MINDAGAP_MINDAGAP } from '../modules/nf-core/mindagap/mindagap/main' include { CELLPOSE } from '../modules/nf-core/cellpose/main' include { DEEPCELL_MESMER } from '../modules/nf-core/deepcell/mesmer/main' From 788c3c6e609111652cfa58c6f752f7243826ea9b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Tue, 5 Dec 2023 17:34:03 +0000 Subject: [PATCH 079/149] maskfilter added, molkartqc update, prefix fix, versions --- CHANGELOG.md | 21 +++ assets/multiqc_config.yml | 9 ++ bin/check_samplesheet.py | 259 ------------------------------ bin/collect_QC.py | 17 +- bin/maskfilter.py | 118 ++++++++++++++ bin/spot2cell.py | 1 + conf/modules.config | 24 ++- docs/output.md | 15 +- modules/local/create_stack.nf | 10 +- modules/local/maskfilter.nf | 47 ++++++ modules/local/molcart_qc.nf | 28 ---- modules/local/molkartqc.nf | 47 ++++++ modules/local/spot2cell.nf | 21 ++- nextflow.config | 2 + nextflow_schema.json | 10 ++ subworkflows/local/input_check.nf | 44 ----- tests/main.nf.test | 14 +- tests/main.nf.test.snap | 22 +-- workflows/molkart.nf | 97 ++++++----- 19 files changed, 401 insertions(+), 405 deletions(-) delete mode 100755 bin/check_samplesheet.py create mode 100755 bin/maskfilter.py create mode 100644 modules/local/maskfilter.nf delete mode 100644 modules/local/molcart_qc.nf create mode 100644 modules/local/molkartqc.nf delete mode 100644 subworkflows/local/input_check.nf diff --git a/CHANGELOG.md b/CHANGELOG.md index 7370601..2a892f2 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -3,6 +3,27 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/) and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html). +## v1.0.1dev - [2023.12.05] + +Added MASKFILTER module. + +### `Added` + +- MASKFILTER module with respective script, parameters, qc measures that are passed to MOLKARTQC and MULTIQC +- renamed molcart_qc to MOLKARTQC +- versions to main local modules (MOLKARTQC, SPOT2CELL) +- CREATE_STACK when clause (so that it does not show in the progress when it doesn't run) +- comments in molkart.nf for clarity + +### `Fixed` + +- collect_QC average area is now rounded +- prefix handling in some modules + +### `Removed` + +- SAMPLESHEETCHECK subworkflow and Python script + ## v1.0.1dev - [2023.12.02] Replaced local module for mindagap/duplicatefinder with nf-core module. diff --git a/assets/multiqc_config.yml b/assets/multiqc_config.yml index 3edf5af..cee82bb 100644 --- a/assets/multiqc_config.yml +++ b/assets/multiqc_config.yml @@ -50,6 +50,15 @@ custom_data: duplicated_total: title: Total number of duplicated spots in the area description: "Total number of duplicated spots" + labels_total: + title: Total number of segmentation labels before filtering + description: "Total number of segmented labels" + labels_below_thresh: + title: Number of removed small labels + description: "Total number of labels below min_area" + labels_above_thresh: + title: Number of removed large labels + description: "Total number of labels above max_area" sp: segmentation_stats: fn: "final_QC.all_samples.csv" diff --git a/bin/check_samplesheet.py b/bin/check_samplesheet.py deleted file mode 100755 index 4a758fe..0000000 --- a/bin/check_samplesheet.py +++ /dev/null @@ -1,259 +0,0 @@ -#!/usr/bin/env python - - -"""Provide a command line tool to validate and transform tabular samplesheets.""" - - -import argparse -import csv -import logging -import sys -from collections import Counter -from pathlib import Path - -logger = logging.getLogger() - - -class RowChecker: - """ - Define a service that can validate and transform each given row. - - Attributes: - modified (list): A list of dicts, where each dict corresponds to a previously - validated and transformed row. The order of rows is maintained. - - """ - - VALID_FORMATS = ( - ".fq.gz", - ".fastq.gz", - ) - - def __init__( - self, - sample_col="sample", - first_col="fastq_1", - second_col="fastq_2", - single_col="single_end", - **kwargs, - ): - """ - Initialize the row checker with the expected column names. - - Args: - sample_col (str): The name of the column that contains the sample name - (default "sample"). - first_col (str): The name of the column that contains the first (or only) - FASTQ file path (default "fastq_1"). - second_col (str): The name of the column that contains the second (if any) - FASTQ file path (default "fastq_2"). - single_col (str): The name of the new column that will be inserted and - records whether the sample contains single- or paired-end sequencing - reads (default "single_end"). - - """ - super().__init__(**kwargs) - self._sample_col = sample_col - self._first_col = first_col - self._second_col = second_col - self._single_col = single_col - self._seen = set() - self.modified = [] - - def validate_and_transform(self, row): - """ - Perform all validations on the given row and insert the read pairing status. - - Args: - row (dict): A mapping from column headers (keys) to elements of that row - (values). - - """ - self._validate_sample(row) - self._validate_first(row) - self._validate_second(row) - self._validate_pair(row) - self._seen.add((row[self._sample_col], row[self._first_col])) - self.modified.append(row) - - def _validate_sample(self, row): - """Assert that the sample name exists and convert spaces to underscores.""" - if len(row[self._sample_col]) <= 0: - raise AssertionError("Sample input is required.") - # Sanitize samples slightly. - row[self._sample_col] = row[self._sample_col].replace(" ", "_") - - def _validate_first(self, row): - """Assert that the first FASTQ entry is non-empty and has the right format.""" - if len(row[self._first_col]) <= 0: - raise AssertionError("At least the first FASTQ file is required.") - self._validate_fastq_format(row[self._first_col]) - - def _validate_second(self, row): - """Assert that the second FASTQ entry has the right format if it exists.""" - if len(row[self._second_col]) > 0: - self._validate_fastq_format(row[self._second_col]) - - def _validate_pair(self, row): - """Assert that read pairs have the same file extension. Report pair status.""" - if row[self._first_col] and row[self._second_col]: - row[self._single_col] = False - first_col_suffix = Path(row[self._first_col]).suffixes[-2:] - second_col_suffix = Path(row[self._second_col]).suffixes[-2:] - if first_col_suffix != second_col_suffix: - raise AssertionError("FASTQ pairs must have the same file extensions.") - else: - row[self._single_col] = True - - def _validate_fastq_format(self, filename): - """Assert that a given filename has one of the expected FASTQ extensions.""" - if not any(filename.endswith(extension) for extension in self.VALID_FORMATS): - raise AssertionError( - f"The FASTQ file has an unrecognized extension: {filename}\n" - f"It should be one of: {', '.join(self.VALID_FORMATS)}" - ) - - def validate_unique_samples(self): - """ - Assert that the combination of sample name and FASTQ filename is unique. - - In addition to the validation, also rename all samples to have a suffix of _T{n}, where n is the - number of times the same sample exist, but with different FASTQ files, e.g., multiple runs per experiment. - - """ - if len(self._seen) != len(self.modified): - raise AssertionError("The pair of sample name and FASTQ must be unique.") - seen = Counter() - for row in self.modified: - sample = row[self._sample_col] - seen[sample] += 1 - row[self._sample_col] = f"{sample}_T{seen[sample]}" - - -def read_head(handle, num_lines=10): - """Read the specified number of lines from the current position in the file.""" - lines = [] - for idx, line in enumerate(handle): - if idx == num_lines: - break - lines.append(line) - return "".join(lines) - - -def sniff_format(handle): - """ - Detect the tabular format. - - Args: - handle (text file): A handle to a `text file`_ object. The read position is - expected to be at the beginning (index 0). - - Returns: - csv.Dialect: The detected tabular format. - - .. _text file: - https://docs.python.org/3/glossary.html#term-text-file - - """ - peek = read_head(handle) - handle.seek(0) - sniffer = csv.Sniffer() - dialect = sniffer.sniff(peek) - return dialect - - -def check_samplesheet(file_in, file_out): - """ - Check that the tabular samplesheet has the structure expected by nf-core pipelines. - - Validate the general shape of the table, expected columns, and each row. Also add - an additional column which records whether one or two FASTQ reads were found. - - Args: - file_in (pathlib.Path): The given tabular samplesheet. The format can be either - CSV, TSV, or any other format automatically recognized by ``csv.Sniffer``. - file_out (pathlib.Path): Where the validated and transformed samplesheet should - be created; always in CSV format. - - Example: - This function checks that the samplesheet follows the following structure, - see also the `viral recon samplesheet`_:: - - sample,fastq_1,fastq_2 - SAMPLE_PE,SAMPLE_PE_RUN1_1.fastq.gz,SAMPLE_PE_RUN1_2.fastq.gz - SAMPLE_PE,SAMPLE_PE_RUN2_1.fastq.gz,SAMPLE_PE_RUN2_2.fastq.gz - SAMPLE_SE,SAMPLE_SE_RUN1_1.fastq.gz, - - .. _viral recon samplesheet: - https://raw.githubusercontent.com/nf-core/test-datasets/viralrecon/samplesheet/samplesheet_test_illumina_amplicon.csv - - """ - required_columns = {"sample", "fastq_1", "fastq_2"} - # See https://docs.python.org/3.9/library/csv.html#id3 to read up on `newline=""`. - with file_in.open(newline="") as in_handle: - reader = csv.DictReader(in_handle, dialect=sniff_format(in_handle)) - # Validate the existence of the expected header columns. - if not required_columns.issubset(reader.fieldnames): - req_cols = ", ".join(required_columns) - logger.critical(f"The sample sheet **must** contain these column headers: {req_cols}.") - sys.exit(1) - # Validate each row. - checker = RowChecker() - for i, row in enumerate(reader): - try: - checker.validate_and_transform(row) - except AssertionError as error: - logger.critical(f"{str(error)} On line {i + 2}.") - sys.exit(1) - checker.validate_unique_samples() - header = list(reader.fieldnames) - header.insert(1, "single_end") - # See https://docs.python.org/3.9/library/csv.html#id3 to read up on `newline=""`. - with file_out.open(mode="w", newline="") as out_handle: - writer = csv.DictWriter(out_handle, header, delimiter=",") - writer.writeheader() - for row in checker.modified: - writer.writerow(row) - - -def parse_args(argv=None): - """Define and immediately parse command line arguments.""" - parser = argparse.ArgumentParser( - description="Validate and transform a tabular samplesheet.", - epilog="Example: python check_samplesheet.py samplesheet.csv samplesheet.valid.csv", - ) - parser.add_argument( - "file_in", - metavar="FILE_IN", - type=Path, - help="Tabular input samplesheet in CSV or TSV format.", - ) - parser.add_argument( - "file_out", - metavar="FILE_OUT", - type=Path, - help="Transformed output samplesheet in CSV format.", - ) - parser.add_argument( - "-l", - "--log-level", - help="The desired log level (default WARNING).", - choices=("CRITICAL", "ERROR", "WARNING", "INFO", "DEBUG"), - default="WARNING", - ) - return parser.parse_args(argv) - - -def main(argv=None): - """Coordinate argument parsing and program execution.""" - args = parse_args(argv) - logging.basicConfig(level=args.log_level, format="[%(levelname)s] %(message)s") - if not args.file_in.is_file(): - logger.error(f"The given input file {args.file_in} was not found!") - sys.exit(2) - args.file_out.parent.mkdir(parents=True, exist_ok=True) - check_samplesheet(args.file_in, args.file_out) - - -if __name__ == "__main__": - sys.exit(main()) diff --git a/bin/collect_QC.py b/bin/collect_QC.py index 09dffce..923cbcf 100755 --- a/bin/collect_QC.py +++ b/bin/collect_QC.py @@ -25,7 +25,7 @@ def summarize_segmasks(cellxgene_table, spots_summary): total_cells = cellxgene_table.shape[0] ## Calculate the average segmentation area from column Area in cellxgene_table - avg_area = cellxgene_table["Area"].mean() + avg_area = round(cellxgene_table["Area"].mean(), 2) ## Calculate the % of spots assigned ## Subset cellxgene_table for all columns with _intensity_sum in the column name and sum the column values @@ -48,6 +48,8 @@ def summarize_segmasks(cellxgene_table, spots_summary): parser.add_argument("-o", "--outdir", help="Output directory.") parser.add_argument("-d", "--sample_id", help="Sample ID.") parser.add_argument("-g", "--segmentation_method", help="Segmentation method used.") + parser.add_argument("--filterqc", required=False, help="QC from mask filter step") + parser.add_argument("--version", action="version", version="0.1.0") args = parser.parse_args() @@ -59,6 +61,13 @@ def summarize_segmasks(cellxgene_table, spots_summary): duplicated = sum(spots.gene.str.contains("Duplicated")) spots = spots[~spots.gene.str.contains("Duplicated")] + ## Pass on filterqc values + filterqc = pd.read_csv( + args.filterqc, + names=["below_min_area", "below_percentage", "above_max_area", "above_percentage", "total_labels"], + header=None, + ) + ## Summarize spots table summary_spots = summarize_spots(spots) summary_segmentation = summarize_segmasks(cellxgene_table, summary_spots) @@ -75,6 +84,9 @@ def summarize_segmasks(cellxgene_table, spots_summary): "spot_assign_total", "spot_assign_percent", "duplicated_total", + "labels_total", + "labels_below_thresh", + "labels_above_thresh", ] ) summary_df.loc[0] = [ @@ -88,6 +100,9 @@ def summarize_segmasks(cellxgene_table, spots_summary): summary_segmentation[3], summary_segmentation[4], duplicated, + filterqc.total_labels[1], + filterqc.below_min_area[1], + filterqc.above_max_area[1], ] print(args.sample_id) # Write summary_df to a csv file diff --git a/bin/maskfilter.py b/bin/maskfilter.py new file mode 100755 index 0000000..51d70f5 --- /dev/null +++ b/bin/maskfilter.py @@ -0,0 +1,118 @@ +#!/usr/bin/env python +import time +import argparse +from argparse import ArgumentParser as AP +from os.path import abspath +import argparse +import numpy as np +from skimage.measure import label, regionprops +from skimage.io import imread, imsave +from os.path import abspath +from argparse import ArgumentParser as AP +import time +import pandas as pd + + +def get_args(): + # Script description + description = """Segmentation mask filtering""" + + # Add parser + parser = AP(description=description, formatter_class=argparse.RawDescriptionHelpFormatter) + + # Sections + inputs = parser.add_argument_group(title="Required Input", description="Path to required input file") + inputs.add_argument("-r", "--input", dest="input", action="store", required=True, help="File path to input image.") + inputs.add_argument("-o", "--output", dest="output", action="store", required=True, help="Path to output image.") + inputs.add_argument( + "--output_qc", dest="output_qc", action="store", required=False, help="Path to output qc csv file." + ) + inputs.add_argument( + "--min_area", + dest="min_area", + action="store", + type=int, + default=None, + help="Lower area (in px) threshold for cell removal", + ) + inputs.add_argument( + "--max_area", + dest="max_area", + action="store", + type=int, + default=None, + help="Upper area (in px) threshold for cell removal", + ) + inputs.add_argument("--version", action="version", version="0.1.0") + arg = parser.parse_args() + + # Standardize paths + arg.input = abspath(arg.input) + arg.output = abspath(arg.output) + if arg.output_qc is None: + arg.output_qc = abspath(arg.output.replace(".tif", ".csv")) + return arg + + +def filter_areas(mask, min_area=None, max_area=None): + labeled_mask = label(mask, background=0) # Start labeling from 1 + measure_tmp = regionprops(labeled_mask) + num_cells = len(measure_tmp) + if min_area: + small_labels = len([prop for prop in measure_tmp if prop.area < min_area]) + else: + small_labels = 0 + min_area = 0 + if max_area: + large_labels = len([prop for prop in measure_tmp if prop.area > max_area]) + else: + max_area = mask.shape[0] * mask.shape[1] + large_labels = 0 + # Create an array to store the filtered mask + filtered_mask = np.zeros_like(labeled_mask) + counter = 1 + for prop in measure_tmp: + if (min_area <= prop.area <= max_area) and (min_area <= prop.area <= max_area): + filtered_mask[labeled_mask == prop.label] = counter + counter += 1 + + return filtered_mask, small_labels, large_labels, num_cells + + +def main(args): + print(f"Head directory = {args.input}") + + # Example usage + in_path = args.input + output = args.output + min_area = args.min_area + max_area = args.max_area + + mask = imread(in_path) + mask, small, big, total = filter_areas(mask, min_area=min_area, max_area=max_area) + imsave(output, mask.astype("int32"), check_contrast=False) + print(f"Filtered mask saved to {output}") + + qc_df = pd.DataFrame( + { + "below_min_area": [small], + "below_percentage": [small / total], + "above_max_area": [big], + "above_percentage": [big / total], + "total_labels": [total], + }, + index=None, + ) + qc_df.to_csv(output.replace(".tif", ".csv"), index=False) + print() + + +if __name__ == "__main__": + # Read in arguments + args = get_args() + + # Run script + st = time.time() + main(args) + rt = time.time() - st + print(f"Script finished in {rt // 60:.0f}m {rt % 60:.0f}s") diff --git a/bin/spot2cell.py b/bin/spot2cell.py index 0f786d8..10e97b5 100755 --- a/bin/spot2cell.py +++ b/bin/spot2cell.py @@ -113,6 +113,7 @@ def assign_spots2cell(spot_table, cell_mask): parser.add_argument("-c", "--cell_mask", help="Sample ID.") parser.add_argument("--tag", type=str, help="Additional tag to append to filename") parser.add_argument("--output", type=str, help="Output path") + parser.add_argument("--version", action="version", version="0.1.0") args = parser.parse_args() diff --git a/conf/modules.config b/conf/modules.config index f50e74e..f192bf2 100644 --- a/conf/modules.config +++ b/conf/modules.config @@ -35,20 +35,39 @@ process { ] } - withName: 'MOLCART_QC' { + withName: 'MOLKARTQC' { publishDir = [ - path: { "${params.outdir}/molcart_qc" }, + path: { "${params.outdir}/molkartqc" }, pattern: "*.csv" ] } withName: 'CREATE_STACK' { + ext.when = { + (params.segmentation_method.split(',').contains('cellpose') || + params.segmentation_method.split(',').contains('ilastik') || + params.create_training_subset) && + (image.size() == 2 ) } + ext.prefix = { "${meta.id}_stack" } publishDir = [ path: { "${params.outdir}/stack" }, pattern: "*.{ome.tif}" ] } + withName: "MASKFILTER" { + ext.prefix = { "${meta.id}_${meta.segmentation}_mask" } + ext.args = [ "", + params.segmentation_min_area ? "--min_area ${params.segmentation_min_area}" : "", + params.segmentation_max_area ? "--min_area ${params.segmentation_max_area}" : "" + ].join(" ").trim() + publishDir = [ + path: { "${params.outdir}/segmentation/filtered_masks" }, + pattern: "*.{tiff,tif}", + saveAs: { filename -> "$filename" } + ] + } + withName: "MINDAGAP_MINDAGAP" { ext.args = [ "", params.mindagap_tilesize ? "-xt ${params.mindagap_tilesize}" : "" @@ -72,6 +91,7 @@ process { } withName: "SPOT2CELL" { + ext.prefix = { "${meta.id}_${tag}"} publishDir = [ path: { "${params.outdir}/spot2cell" }, pattern: "*.csv", diff --git a/docs/output.md b/docs/output.md index d468c82..d528612 100644 --- a/docs/output.md +++ b/docs/output.md @@ -16,7 +16,7 @@ The pipeline is built using [Nextflow](https://www.nextflow.io/) and processes d - [segmentation](#segmentation) - Segment single cells from provided image using segmentation method of choice (Cellpose, Mesmer, ilastik). - [Mindagap_duplicatefinder](#Mindagap) - Take a spot table and search for duplicates along grid lines. - [Spot2cell](#spot2cell) - Assign non-duplicated spots to segmented cells based on segmentation mask and extract cell shape information. -- [molkartqc](#molkartqc) - Produce QC metrics specific to this pipeline. +- [MolkartQC](#molkartqc) - Produce QC metrics specific to this pipeline. - [MultiQC](#multiqc) - Aggregate report describing results and QC from the whole pipeline. - [Pipeline information](#pipeline-information) - Report metrics generated during the workflow execution. @@ -72,8 +72,8 @@ Create stack is a local module used to merge images into a stack as preparation - `*_ilastik_mask.tif`: Segmentation masks created by ilastik's Boundary prediction with Multicut workflow. - `mesmer/`: - `*_mesmer_mask.tif`: Segmentation masks created by Mesmer. - - + - `filtered_masks/` - `*_method_mask.tif`: Segmentation masks filtered based on provided area limits. + [Cellpose](https://www.cellpose.org) is a segmentation tool that provides pretrained models as well as additional human-in-the loop training. If additional training is performed, the envisioned way of doing it is creating the training subset (`tiff`), and training the model in the [Cellpose GUI](https://cellpose.readthedocs.io/en/latest/gui.html) on the subset, then giving the trained model as an argument within the pipeline to complete the pipeline run. @@ -99,13 +99,7 @@ Spot2cell is a local module that assigns spots (without Duplicates) to cells via Output files - `molkartqc/` - - `*.spot_QC.csv`: ### Spot2cell - -
    -Output files - -- `molkartqc/` - - `*.cellxgene.csv`: Sheet containing useful quality-control metrics specific to spot-based image processing methods. + - `*.spot_QC.csv`: Sheet containing useful quality-control metrics specific to spot-based image processing methods.
    @@ -117,6 +111,7 @@ MolkartQC is a local module used for gathering useful quality-control metrics fo Output files - `multiqc/` + - `final_QC.all_samples.csv`: all molkartqc outputs concatenated to one `csv` file. - `multiqc_report.html`: a standalone HTML file that can be viewed in your web browser. - `multiqc_data/`: directory containing parsed statistics from the different tools used in the pipeline. - `multiqc_plots/`: directory containing static images from the report in various formats. diff --git a/modules/local/create_stack.nf b/modules/local/create_stack.nf index 45dc867..8571e2f 100644 --- a/modules/local/create_stack.nf +++ b/modules/local/create_stack.nf @@ -1,6 +1,6 @@ process CREATE_STACK { - tag "Stacking channels for $meta.id" - label 'process_medium' + tag "$meta.id" + label 'process_low' container 'ghcr.io/schapirolabor/background_subtraction:v0.3.3' @@ -16,10 +16,12 @@ process CREATE_STACK { script: def args = task.ext.args ?: '' def prefix = task.ext.prefix ?: "${meta.id}" + """ create_stack.py \\ --input ${image} \\ - --output ${meta.id}.stack.ome.tif \\ - --num-channels 2 + --output ${prefix}.ome.tif \\ + --num-channels 2 \\ + $args """ } diff --git a/modules/local/maskfilter.nf b/modules/local/maskfilter.nf new file mode 100644 index 0000000..0ad1125 --- /dev/null +++ b/modules/local/maskfilter.nf @@ -0,0 +1,47 @@ +process MASKFILTER { + tag "$meta.id" + label 'process_single' + + container 'ghcr.io/schapirolabor/background_subtraction:v0.4.1' + + input: + tuple val(meta), path(mask) + + output: + tuple val(meta), path("*.tif"), emit: filtered_mask + tuple val(meta), path("*.csv"), emit: filtered_qc + path "versions.yml", emit: versions + + when: + task.ext.when == null || task.ext.when + + script: + def args = task.ext.args ?: '' + def prefix = task.ext.prefix ?: "${meta.id}" + + """ + maskfilter.py \\ + --input ${mask} \\ + --output ${prefix}.tif \\ + --output_qc ${prefix}.csv \\ + $args + + cat <<-END_VERSIONS > versions.yml + "${task.process}": + molkart_maskfilter: \$(maskfilter.py --version) + END_VERSIONS + """ + + stub: + def args = task.ext.args ?: '' + def prefix = task.ext.prefix ?: "${meta.id}" + + """ + touch ${prefix}.tif + + cat <<-END_VERSIONS > versions.yml + "${task.process}": + molkart_maskfilter: \$(maskfilter.py --version) + END_VERSIONS + """ +} diff --git a/modules/local/molcart_qc.nf b/modules/local/molcart_qc.nf deleted file mode 100644 index 54b40c3..0000000 --- a/modules/local/molcart_qc.nf +++ /dev/null @@ -1,28 +0,0 @@ -process MOLCART_QC{ - tag "${meta.id}" - container 'docker.io/wuennemannflorian/project_spots:latest' - label 'process_single' - - input: - tuple val(meta), path(cellxgene_table) - tuple val(meta2), path(spot_table) - tuple val(meta3), val(segmethod) - - output: - tuple val(meta), path("*.csv"), emit: qc - - when: - task.ext.when == null || task.ext.when - - script: - def args = task.ext.args ?: '' - def sample_id = "${meta.id}" - """ - collect_QC.py \ - --cellxgene $cellxgene_table \ - --spots $spot_table \ - --sample_id $sample_id \ - --segmentation_method $segmethod \ - --outdir . - """ -} diff --git a/modules/local/molkartqc.nf b/modules/local/molkartqc.nf new file mode 100644 index 0000000..25781d2 --- /dev/null +++ b/modules/local/molkartqc.nf @@ -0,0 +1,47 @@ +process MOLKARTQC{ + tag "${meta.id}" + container 'docker.io/wuennemannflorian/project_spots:latest' + label 'process_single' + + input: + tuple val(meta), path(spot_table), path(cellxgene_table), val(segmethod), path(filterqc) + + output: + tuple val(meta), path("*.csv"), emit: qc + path "versions.yml" , emit: versions + + when: + task.ext.when == null || task.ext.when + + script: + def args = task.ext.args ?: '' + def prefix = task.ext.prefix ?: "${meta.id}" + """ + collect_QC.py \\ + --cellxgene $cellxgene_table \\ + --spots $spot_table \\ + --sample_id $prefix \\ + --segmentation_method $segmethod \\ + --filterqc $filterqc \\ + --outdir . \\ + $args + + cat <<-END_VERSIONS > versions.yml + "${task.process}": + molkartqc: \$(collect_QC.py --version) + END_VERSIONS + """ + + stub: + def args = task.ext.args ?: '' + def prefix = task.ext.prefix ?: "${meta.id}" + + """ + touch ${prefix}.csv + + cat <<-END_VERSIONS > versions.yml + "${task.process}": + molkartqc: \$(collect_QC.py --version) + END_VERSIONS + """ +} diff --git a/modules/local/spot2cell.nf b/modules/local/spot2cell.nf index b1a65cb..32a3439 100644 --- a/modules/local/spot2cell.nf +++ b/modules/local/spot2cell.nf @@ -1,6 +1,6 @@ process SPOT2CELL{ debug true - tag "Assigning spots to cells for $meta.id" + tag "$meta.id" label 'process_single' container 'ghcr.io/schapirolabor/background_subtraction:v0.3.3' @@ -12,19 +12,26 @@ process SPOT2CELL{ output: tuple val(meta), path("*.csv"), emit: cellxgene_table + path "versions.yml" , emit: versions when: task.ext.when == null || task.ext.when script: def args = task.ext.args ?: '' - def prefix = task.ext.prefix ?: tag ? "${meta.id}_${tag}" : "${meta.id}" + def prefix = task.ext.prefix ?: "${meta.id}" """ - spot2cell.py \ - --spot_table ${spot_table} \ - --cell_mask ${cell_mask} \ - --tag ${tag} \ - --output ${prefix}.csv + spot2cell.py \\ + --spot_table ${spot_table} \\ + --cell_mask ${cell_mask} \\ + --tag ${tag} \\ + --output ${prefix}.csv \\ + $args + + cat <<-END_VERSIONS > versions.yml + "${task.process}": + molkart_spot2cell: \$(spot2cell.py --version) + END_VERSIONS """ } diff --git a/nextflow.config b/nextflow.config index e4c8dec..3452417 100644 --- a/nextflow.config +++ b/nextflow.config @@ -14,6 +14,8 @@ params { // Segmentation command line flags segmentation_method = 'mesmer' + segmentation_min_area = null + segmentation_max_area = null cellpose_save_flows = false cellpose_diameter = 30 cellpose_chan = 0 diff --git a/nextflow_schema.json b/nextflow_schema.json index 170259d..23b8cdc 100644 --- a/nextflow_schema.json +++ b/nextflow_schema.json @@ -17,6 +17,16 @@ "default": "mesmer", "fa_icon": "fas fa-border-all" }, + "segmentation_min_area": { + "type": "integer", + "description": "Minimum area size (in pixels) for segmentation masks.", + "fa_icon": "fas fa-chart-area" + }, + "segmentation_max_area": { + "type": "integer", + "description": "Maximum area size (in pixels) for segmenation masks.", + "fa_icon": "fas fa-chart-area" + }, "cellpose_diameter": { "type": "integer", "default": 30, diff --git a/subworkflows/local/input_check.nf b/subworkflows/local/input_check.nf deleted file mode 100644 index 0aecf87..0000000 --- a/subworkflows/local/input_check.nf +++ /dev/null @@ -1,44 +0,0 @@ -// -// Check input samplesheet and get read channels -// - -include { SAMPLESHEET_CHECK } from '../../modules/local/samplesheet_check' - -workflow INPUT_CHECK { - take: - samplesheet // file: /path/to/samplesheet.csv - - main: - SAMPLESHEET_CHECK ( samplesheet ) - .csv - .splitCsv ( header:true, sep:',' ) - .map { create_fastq_channel(it) } - .set { reads } - - emit: - reads // channel: [ val(meta), [ reads ] ] - versions = SAMPLESHEET_CHECK.out.versions // channel: [ versions.yml ] -} - -// Function to get list of [ meta, [ fastq_1, fastq_2 ] ] -def create_fastq_channel(LinkedHashMap row) { - // create meta map - def meta = [:] - meta.id = row.sample - meta.single_end = row.single_end.toBoolean() - - // add path(s) of the fastq file(s) to the meta map - def fastq_meta = [] - if (!file(row.fastq_1).exists()) { - exit 1, "ERROR: Please check input samplesheet -> Read 1 FastQ file does not exist!\n${row.fastq_1}" - } - if (meta.single_end) { - fastq_meta = [ meta, [ file(row.fastq_1) ] ] - } else { - if (!file(row.fastq_2).exists()) { - exit 1, "ERROR: Please check input samplesheet -> Read 2 FastQ file does not exist!\n${row.fastq_2}" - } - fastq_meta = [ meta, [ file(row.fastq_1), file(row.fastq_2) ] ] - } - return fastq_meta -} diff --git a/tests/main.nf.test b/tests/main.nf.test index e66a5df..81597d8 100644 --- a/tests/main.nf.test +++ b/tests/main.nf.test @@ -25,10 +25,12 @@ nextflow_pipeline { path("$outputDir/mindagap/nuc_only_spots_markedDups.txt"), path("$outputDir/segmentation/cellpose/nuc_only_cellpose_mask.tif"), path("$outputDir/segmentation/mesmer/nuc_only_mesmer_mask.tif"), + path("$outputDir/segmentation/filtered_masks/nuc_only_mesmer_mask.tif"), + path("$outputDir/segmentation/filtered_masks/nuc_only_cellpose_mask.tif"), path("$outputDir/spot2cell/cellxgene_nuc_only_cellpose.csv"), path("$outputDir/spot2cell/cellxgene_nuc_only_mesmer.csv"), - path("$outputDir/molcart_qc/nuc_only.cellpose.spot_QC.csv"), - path("$outputDir/molcart_qc/nuc_only.mesmer.spot_QC.csv") + path("$outputDir/molkartqc/nuc_only.cellpose.spot_QC.csv"), + path("$outputDir/molkartqc/nuc_only.mesmer.spot_QC.csv") ).match() assert file("$outputDir/multiqc/multiqc_report.html").exists() } @@ -54,11 +56,13 @@ nextflow_pipeline { path("$outputDir/mindagap/mem_only_spots_markedDups.txt"), path("$outputDir/segmentation/cellpose/mem_only_cellpose_mask.tif"), path("$outputDir/segmentation/mesmer/mem_only_mesmer_mask.tif"), + path("$outputDir/segmentation/filtered_masks/mem_only_mesmer_mask.tif"), + path("$outputDir/segmentation/filtered_masks/mem_only_cellpose_mask.tif"), path("$outputDir/spot2cell/cellxgene_mem_only_cellpose.csv"), path("$outputDir/spot2cell/cellxgene_mem_only_mesmer.csv"), - path("$outputDir/stack/mem_only.stack.ome.tif"), - path("$outputDir/molcart_qc/mem_only.cellpose.spot_QC.csv"), - path("$outputDir/molcart_qc/mem_only.mesmer.spot_QC.csv"), + path("$outputDir/stack/mem_only_stack.ome.tif"), + path("$outputDir/molkartqc/mem_only.cellpose.spot_QC.csv"), + path("$outputDir/molkartqc/mem_only.mesmer.spot_QC.csv"), ).match() assert file("$outputDir/clahe/mem_only_membrane_gridfilled_clahe.tiff").exists() assert file("$outputDir/clahe/mem_only_nuclear_gridfilled_clahe.tiff").exists() diff --git a/tests/main.nf.test.snap b/tests/main.nf.test.snap index bd86d65..9357bf5 100644 --- a/tests/main.nf.test.snap +++ b/tests/main.nf.test.snap @@ -6,13 +6,15 @@ "mem_only_spots_markedDups.txt:md5,4562caad05850d7dd7b6e9235e068a8b", "mem_only_cellpose_mask.tif:md5,590591f541b6d3f17810cd44dd71b252", "mem_only_mesmer_mask.tif:md5,6f8c792ccc4cca97b5696990fb4e3801", + "mem_only_mesmer_mask.tif:md5,5751b2e39393a9c8221396f5ef592035", + "mem_only_cellpose_mask.tif:md5,590591f541b6d3f17810cd44dd71b252", "cellxgene_mem_only_cellpose.csv:md5,f063c1ce5e93e1e73431af36c6bc1e79", - "cellxgene_mem_only_mesmer.csv:md5,f54f2af6ce874e96f7973504bddd9bc9", - "mem_only.stack.ome.tif:md5,d8659ad7bf017fecc795b855785b74be", - "mem_only.cellpose.spot_QC.csv:md5,4b24962d8eae2579eab419179212fd27", - "mem_only.mesmer.spot_QC.csv:md5,d5c302ff76e8ce7a8d212f6d818cedbc" + "cellxgene_mem_only_mesmer.csv:md5,198b187d5f151077437aa591f5991b22", + "mem_only_stack.ome.tif:md5,d8659ad7bf017fecc795b855785b74be", + "mem_only.cellpose.spot_QC.csv:md5,df312175498f7942bffc33f2c2d8d1c9", + "mem_only.mesmer.spot_QC.csv:md5,3273bd6fecf93a3d240614d1b38831c9" ], - "timestamp": "2023-11-30T16:46:18.513521201" + "timestamp": "2023-12-05T17:06:31.14616363" }, "Nuclear channel, mesmer and cellpose, without clahe": { "content": [ @@ -20,12 +22,14 @@ "nuc_only_spots_markedDups.txt:md5,4562caad05850d7dd7b6e9235e068a8b", "nuc_only_cellpose_mask.tif:md5,2784d8c6683ad80c24d8df4121e1128f", "nuc_only_mesmer_mask.tif:md5,e9719f53651b4bf76a37e9374db7f4e4", + "nuc_only_mesmer_mask.tif:md5,5a6761c80ea65d41ce00d06d3414c96b", + "nuc_only_cellpose_mask.tif:md5,2784d8c6683ad80c24d8df4121e1128f", "cellxgene_nuc_only_cellpose.csv:md5,0610a8713457c28acf1bc4c298bee8e3", - "cellxgene_nuc_only_mesmer.csv:md5,13d8f4fb05a400c94866404fc424a8e8", - "nuc_only.cellpose.spot_QC.csv:md5,3fa7f7d1f87d37428907a77236893330", - "nuc_only.mesmer.spot_QC.csv:md5,9779af541ceae4a0fe0ae20d75db2bee" + "cellxgene_nuc_only_mesmer.csv:md5,425cfb90a60b564e4bfff09ac5ea94c7", + "nuc_only.cellpose.spot_QC.csv:md5,e77b5973e0997170d0fde5c5901ad551", + "nuc_only.mesmer.spot_QC.csv:md5,f8f4eb85bb8269341ac072ac78962ed4" ], - "timestamp": "2023-11-28T21:36:07.153599523" + "timestamp": "2023-12-05T17:05:20.326350602" }, "Create training subset": { "content": [ diff --git a/workflows/molkart.nf b/workflows/molkart.nf index 9ff72f4..39cf64e 100644 --- a/workflows/molkart.nf +++ b/workflows/molkart.nf @@ -36,9 +36,10 @@ include { CREATETRAININGTIFF } from '../modules/local/createtrainingtif include { CREATEILASTIKTRAININGSUBSET } from '../modules/local/createilastiktrainingsubset' include { CREATE_STACK } from '../modules/local/create_stack' include { CLAHE } from '../modules/local/clahe_dask' +include { MASKFILTER } from '../modules/local/maskfilter' +include { MOLKARTQC } from '../modules/local/molkartqc' include { SPOT2CELL } from '../modules/local/spot2cell' include { TIFFH5CONVERT } from '../modules/local/tiffh5convert' -include { MOLCART_QC } from '../modules/local/molcart_qc' // // SUBWORKFLOW: Consisting of a mix of local and nf-core/modules @@ -53,14 +54,14 @@ include { MOLCART_QC } from '../modules/local/molcart_qc' // // MODULE: Installed directly from nf-core/modules // -include { MULTIQC } from '../modules/nf-core/multiqc/main' -include { CUSTOM_DUMPSOFTWAREVERSIONS } from '../modules/nf-core/custom/dumpsoftwareversions/main' -include { MINDAGAP_DUPLICATEFINDER } from '../modules/nf-core/mindagap/duplicatefinder/main' -include { MINDAGAP_MINDAGAP } from '../modules/nf-core/mindagap/mindagap/main' include { CELLPOSE } from '../modules/nf-core/cellpose/main' +include { CUSTOM_DUMPSOFTWAREVERSIONS } from '../modules/nf-core/custom/dumpsoftwareversions/main' include { DEEPCELL_MESMER } from '../modules/nf-core/deepcell/mesmer/main' -include { ILASTIK_PIXELCLASSIFICATION } from '../modules/nf-core/ilastik/pixelclassification/main' include { ILASTIK_MULTICUT } from '../modules/nf-core/ilastik/multicut/main' +include { ILASTIK_PIXELCLASSIFICATION } from '../modules/nf-core/ilastik/pixelclassification/main' +include { MINDAGAP_DUPLICATEFINDER } from '../modules/nf-core/mindagap/duplicatefinder/main' +include { MINDAGAP_MINDAGAP } from '../modules/nf-core/mindagap/mindagap/main' +include { MULTIQC } from '../modules/nf-core/multiqc/main' /* ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ @@ -82,44 +83,46 @@ workflow MOLKART { ch_from_samplesheet = Channel.fromSamplesheet("input") + // stain: "1" denotes membrane, stain: "0" denotes nuclear image + // this is used to preserve the order later ch_from_samplesheet .map { it[3] != [] ? tuple([id:it[0],stain:"1"], it[3]) : null - }.set { membrane_tuple } + }.set { membrane_tuple } // if a membrane image is provided, return membrane image channel tuple (meta, path) ch_from_samplesheet .map { it -> tuple([id:it[0],stain:"0"], it[1]) } - .set { image_tuple } + .set { image_tuple } // creates nuclear image channel tuple (meta, path) ch_from_samplesheet .map { it -> tuple([id:it[0]], it[2]) } - .set { spot_tuple } + .set { spot_tuple } // creates spot table channel tuple (meta, path) // // MODULE: Run Mindagap_mindagap // - mindagap_in = membrane_tuple.mix(image_tuple) - MINDAGAP_MINDAGAP(mindagap_in, 7, 100) + mindagap_in = membrane_tuple.mix(image_tuple) // mindagap input contains both membrane and nuclear images + MINDAGAP_MINDAGAP(mindagap_in, 7, 100) // runs MINDAGAP_MINDAGAP, hardcoded boxsize and loopnumber parameters; TODO: make mindagap_mindagap more compliant with nf-core guidelines ch_versions = ch_versions.mix(MINDAGAP_MINDAGAP.out.versions) // //MODULE: Apply Contrast-limited adaptive histogram equalization (CLAHE) // - // currently CLAHE is either applied on all channels, or none. + // CLAHE is either applied to all images, or none. if (!params.skip_clahe) { CLAHE(MINDAGAP_MINDAGAP.out.tiff) ch_versions = ch_versions.mix(CLAHE.out.versions) - CLAHE.out.img_clahe.set{ map_for_stacks } + CLAHE.out.img_clahe.set{ map_for_stacks } // if CLAHE is run, use CLAHE output for next steps } else { - MINDAGAP_MINDAGAP.out.tiff.set{ map_for_stacks } - } // if clahe should be run, use its output for next step, otherwise, use mindagap output + MINDAGAP_MINDAGAP.out.tiff.set{ map_for_stacks } // if CLAHE is not run, use MINDAGAP output for next steps + } map_for_stacks .map { - meta, tiff -> [meta.subMap("id"), tiff, meta.stain] - }.groupTuple() + meta, tiff -> [meta.subMap("id"), tiff, meta.stain] // creates a channel containing only the sample id in meta, path to preprocessed image and the stain value ("0" or "1") + }.groupTuple() // combines based on meta .map{ - meta, paths, stains -> [meta, [paths[0], stains[0]], [paths[1], stains[1]]] + meta, paths, stains -> [meta, [paths[0], stains[0]], [paths[1], stains[1]]] // reorganizes to match path and stain }.map{ meta, stain1, stain2 -> [meta, [stain1, stain2].sort{ it[1] }] // sort by stain index (0 for nuclear, 1 for other) }.map{ @@ -128,20 +131,20 @@ workflow MOLKART { it[1][0] != null ? [it[0],it[1][0],it[2][0]] : [it[0],it[2][0]] // if null, only return the valid nuclear path value, otherwise return both nuclear and membrane paths }.set { grouped_map_stack } - grouped_map_stack.filter{ + grouped_map_stack.filter{ // for rows without a present membrane image, set channel to no_stack it[2] == null }.set{ no_stack } - grouped_map_stack.filter{ + grouped_map_stack.filter{ // for rows where the membrane image is present, make it compliant with STACK inputs it[2] != null }.map{ [it[0],tuple(it[1],it[2])] }.set{ create_stack_in } // - // MODULE: Stack channels if membrane image provided for segmentation + // MODULE: Stack channels if membrane image provided for segmentation (Mesmer does not require it, Cellpose and ilastik do) // if (params.segmentation_method.split(',').contains('cellpose') || - params.segmentation_method.split(',').contains('ilastik') || + params.segmentation_method.split(',').contains('ilastik') || params.create_training_subset){ CREATE_STACK(create_stack_in) stack_mix = CREATE_STACK.out.stack.mix(no_stack) @@ -239,10 +242,28 @@ workflow MOLKART { .mix(ILASTIK_MULTICUT.out.out_tiff .combine(Channel.of('ilastik'))) } + segmentation_masks.map{ + meta, mask, segmentation -> + new_meta = meta.clone() + new_meta.segmentation = segmentation + [new_meta, mask] + }.set { matched_segmasks } - // Assigning of spots to mask + // + // MODULE: filter segmentation masks + // + MASKFILTER(matched_segmasks) + ch_versions = ch_versions.mix(MASKFILTER.out.versions) + MASKFILTER.out.filtered_mask.map{ + meta, mask -> + tuple(meta.subMap("id"), mask, meta.segmentation) + }.set { filtered_masks } + + // + // MODULE: assign spots to segmentation mask + // qc_spots - .combine(segmentation_masks, by: 0) + .combine(filtered_masks, by: 0) .map { meta, spots_table, mask, segmethod -> new_meta = meta.clone() @@ -256,29 +277,33 @@ workflow MOLKART { dedup_spots.map(it -> tuple(it[0],it[2])), dedup_spots.map(it -> it[0].segmentation) ) + ch_versions = ch_versions.mix(SPOT2CELL.out.versions) // - // MODULE: MOLCART_QC + // MODULE: MOLKARTQC // - SPOT2CELL.out.cellxgene_table - .map { - meta, quant -> - [meta.subMap("id"), quant, meta.segmentation] + SPOT2CELL.out.cellxgene_table.combine( + MASKFILTER.out.filtered_qc, by: 0 + ).map{ + meta, quant, filterqc -> + [meta.subMap("id"), quant, meta.segmentation, filterqc] }.set { spot2cell_out } qc_spots .combine(spot2cell_out, by: 0) - .set{ molcart_qc } + .set{ molkartqc } - MOLCART_QC( - molcart_qc.map{it -> tuple(it[0],it[2])}, - molcart_qc.map{it -> tuple(it[0],it[1])}, - molcart_qc.map{it -> tuple(it[0],it[3])} - ) + MOLKARTQC(molkartqc) + ch_versions = ch_versions.mix(MOLKARTQC.out.versions) + + // + // MODULE: CUSTOM_DUMPSOFTWAREVERSIONS + // CUSTOM_DUMPSOFTWAREVERSIONS ( ch_versions.unique().collectFile(name: 'collated_versions.yml') ) + // // MODULE: MultiQC // @@ -288,7 +313,7 @@ workflow MOLKART { ch_methods_description = Channel.value(methods_description) ch_multiqc_files = Channel.empty() - ch_multiqc_files = ch_multiqc_files.mix(MOLCART_QC.out.qc.map{it[1]}.collectFile(name: 'final_QC.all_samples.csv', keepHeader: true, storeDir: "$params.outdir")) + ch_multiqc_files = ch_multiqc_files.mix(MOLKARTQC.out.qc.map{it[1]}.collectFile(name: 'final_QC.all_samples.csv', keepHeader: true, storeDir: "${params.outdir}/multiqc")) ch_multiqc_files = ch_multiqc_files.mix(ch_workflow_summary.collectFile(name: 'workflow_summary_mqc.yaml')) ch_multiqc_files = ch_multiqc_files.mix(ch_methods_description.collectFile(name: 'methods_description_mqc.yaml')) ch_multiqc_files = ch_multiqc_files.mix(CUSTOM_DUMPSOFTWAREVERSIONS.out.mqc_yml.collect()) From 1e779bce8fea43fd45a5396650d15bc0239705e6 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Tue, 5 Dec 2023 19:13:06 +0000 Subject: [PATCH 080/149] Updated documentation --- CITATIONS.md | 4 ++-- README.md | 23 +++++++++++++++-------- docs/images/molkart_workflow.png | Bin 588219 -> 588106 bytes docs/output.md | 2 +- docs/usage.md | 4 +++- 5 files changed, 21 insertions(+), 12 deletions(-) diff --git a/CITATIONS.md b/CITATIONS.md index 6b93761..6b28ae6 100644 --- a/CITATIONS.md +++ b/CITATIONS.md @@ -17,11 +17,11 @@ - [ilastik](https://www.ilastik.org/) -> Berg, S., Kutra, D., Kroeger, T. et al. ilastik: interactive machine learning for (bio)image analysis. Nat Methods 16, 1226–1232 (2019). https://doi.org/10.1038/s41592-019-0582-9 + > Berg, S., Kutra, D., Kroeger, T. et al. ilastik: interactive machine learning for (bio)image analysis. Nat Methods 16, 1226–1232 (2019). https://doi.org/10.1038/s41592-019-0582-9 - [Mesmer](https://deepcell.readthedocs.io/en/master/API/deepcell.applications.html) -> Greenwald NF, Miller G, Moen E, Kong A, Kagel A, Dougherty T, Fullaway CC, McIntosh BJ, Leow KX, Schwartz MS, Pavelchek C, Cui S, Camplisson I, Bar-Tal O, Singh J, Fong M, Chaudhry G, Abraham Z, Moseley J, Warshawsky S, Soon E, Greenbaum S, Risom T, Hollmann T, Bendall SC, Keren L, Graf W, Angelo M, Van Valen D. Whole-cell segmentation of tissue images with human-level performance using large-scale data annotation and deep learning. Nat Biotechnol. 2022 Apr;40(4):555-565. doi: 10.1038/s41587-021-01094-0. Epub 2021 Nov 18. PMID: 34795433; PMCID: PMC9010346. + > Greenwald NF, Miller G, Moen E, Kong A, Kagel A, Dougherty T, Fullaway CC, McIntosh BJ, Leow KX, Schwartz MS, Pavelchek C, Cui S, Camplisson I, Bar-Tal O, Singh J, Fong M, Chaudhry G, Abraham Z, Moseley J, Warshawsky S, Soon E, Greenbaum S, Risom T, Hollmann T, Bendall SC, Keren L, Graf W, Angelo M, Van Valen D. Whole-cell segmentation of tissue images with human-level performance using large-scale data annotation and deep learning. Nat Biotechnol. 2022 Apr;40(4):555-565. doi: 10.1038/s41587-021-01094-0. Epub 2021 Nov 18. PMID: 34795433; PMCID: PMC9010346. - [Mindagap](https://github.com/ViriatoII/MindaGap) diff --git a/README.md b/README.md index 17bf9ac..90c6f38 100644 --- a/README.md +++ b/README.md @@ -4,7 +4,6 @@ [![GitHub Actions Linting Status](https://github.com/nf-core/molkart/workflows/nf-core%20linting/badge.svg)](https://github.com/nf-core/molkart/actions?query=workflow%3A%22nf-core+linting%22)[![AWS CI](https://img.shields.io/badge/CI%20tests-full%20size-FF9900?labelColor=000000&logo=Amazon%20AWS)](https://nf-co.re/molkart/results)[![Cite with Zenodo](http://img.shields.io/badge/DOI-10.5281/zenodo.XXXXXXX-1073c8?labelColor=000000)](https://doi.org/10.5281/zenodo.XXXXXXX) [![Nextflow](https://img.shields.io/badge/nextflow%20DSL2-%E2%89%A523.04.0-23aa62.svg)](https://www.nextflow.io/) -[![run with conda](http://img.shields.io/badge/run%20with-conda-3EB049?labelColor=000000&logo=anaconda)](https://docs.conda.io/en/latest/) [![run with docker](https://img.shields.io/badge/run%20with-docker-0db7ed?labelColor=000000&logo=docker)](https://www.docker.com/) [![run with singularity](https://img.shields.io/badge/run%20with-singularity-1d355c.svg?labelColor=000000)](https://sylabs.io/docs/) [![Launch on Nextflow Tower](https://img.shields.io/badge/Launch%20%F0%9F%9A%80-Nextflow%20Tower-%234256e7)](https://tower.nf/launch?pipeline=https://github.com/nf-core/molkart) @@ -16,20 +15,27 @@ **nf-core/molkart** is a pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH). It takes as input a table of FISH spot positions (x,y,z,gene), a corresponding DAPI image (`tiff` format) and optionally a membrane staining image in the `tiff` format. nf-core/molkart performs end-to-end processing of the data including image processing, QC filtering of spots, cell segmentation, spot-to-cell assignment and reports quality metrics such as the spot assignment rate, average spots per cell and segmentation mask size ranges.

    - +

    Image preprocessing - Fill the grid pattern in provided images ([`Mindagap`](https://github.com/ViriatoII/MindaGap)) - Optionally apply contrast-limited adaptive histogram equalization -- If a second (membrane) image is present, combine images into a multichannel stack - Cell segmentation -- Apply cell segmentation based on provided images, available options are: - [`Cellpose`](https://www.cellpose.org/) - [`Mesmer `](https://deepcell.readthedocs.io/en/master/API/deepcell.applications.html#mesmer) - [`ilastik`](https://www.ilastik.org/) - Spot processing +- If a second (membrane) image is present, combine images into a multichannel stack (if required for segmentation) + +Cell segmentation + +- Apply cell segmentation based on provided images, available options are: - [`Cellpose`](https://www.cellpose.org/) - [`Mesmer`](https://deepcell.readthedocs.io/en/master/API/deepcell.applications.html#mesmer) - [`ilastik`](https://www.ilastik.org/) +- Filter cells based on cell size to remove artifacts + +Spot processing + - Find duplicated spots near grid lines ([`Mindagap`](https://github.com/ViriatoII/MindaGap)) - Assign spots to segmented cells - Quality control + +Quality control + - Create quality-control metrics specific to this pipeline - provide them to ([`MultiQC`](http://multiqc.info/)) to create a report @@ -47,7 +53,7 @@ First, prepare a samplesheet with your input data that looks as follows: ```csv sample,nuclear_image,spot_locations,membrane_image -sample0,sample0_DAPI.tiff,sample0_spots.txt, sample0_WGA.tiff +sample0,sample0_DAPI.tiff,sample0_spots.txt,sample0_WGA.tiff ``` Each row represents an FOV (field-of-view). Columns represent the sample ID (all must be unique), the path to the respective nuclear image, the spot table, and optionally the path to the respective membrane image (or any second image). @@ -71,6 +77,7 @@ For more details and further functionality, please refer to the [usage documenta ## Pipeline output +The pipeline outputs a matched cell-by-transcript table based on deduplicated spots and segmented cells, as well as preprocessing and segmentation intermediaries. To see the results of an example test run with a full size dataset refer to the [results](https://nf-co.re/molkart/results) tab on the nf-core website pipeline page. 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+ diff --git a/assets/multiqc_config.yml b/assets/multiqc_config.yml index 5c4e4ef..b5b575a 100644 --- a/assets/multiqc_config.yml +++ b/assets/multiqc_config.yml @@ -1,5 +1,5 @@ report_comment: > - This report has been generated by the nf-core/molkart + This report has been generated by the nf-core/molkart analysis pipeline. For information about how to interpret these results, please see the documentation. report_section_order: diff --git a/assets/slackreport.json b/assets/slackreport.json index 26e267b..5c8bbab 100644 --- a/assets/slackreport.json +++ b/assets/slackreport.json @@ -3,7 +3,7 @@ { "fallback": "Plain-text summary of the attachment.", "color": "<% if (success) { %>good<% } else { %>danger<%} %>", - "author_name": "nf-core/molkart v${version} - ${runName}", + "author_name": "nf-core/molkart ${version} - ${runName}", "author_icon": "https://www.nextflow.io/docs/latest/_static/favicon.ico", "text": "<% if (success) { %>Pipeline completed successfully!<% } else { %>Pipeline completed with errors<% } %>", "fields": [ diff --git a/conf/modules.config b/conf/modules.config index 39e8138..d91c6ab 100644 --- a/conf/modules.config +++ b/conf/modules.config @@ -39,7 +39,7 @@ process { } withName: 'MULTIQC' { - ext.args = params.multiqc_title ? "--title \"$params.multiqc_title\"" : '' + ext.args = { params.multiqc_title ? "--title \"$params.multiqc_title\"" : '' } publishDir = [ path: { "${params.outdir}/multiqc" }, mode: params.publish_dir_mode, diff --git a/docs/usage.md b/docs/usage.md index f4a48c0..921ab6e 100644 --- a/docs/usage.md +++ b/docs/usage.md @@ -20,7 +20,7 @@ You will need to create a samplesheet with information about the samples you wou The `sample` identifiers have to be the same when you have re-sequenced the same sample more than once e.g. to increase sequencing depth. The pipeline will concatenate the raw reads before performing any downstream analysis. Below is an example for the same sample sequenced across 3 lanes: -```console +```csv title="samplesheet.csv" sample,fastq_1,fastq_2 CONTROL_REP1,AEG588A1_S1_L002_R1_001.fastq.gz,AEG588A1_S1_L002_R2_001.fastq.gz CONTROL_REP1,AEG588A1_S1_L003_R1_001.fastq.gz,AEG588A1_S1_L003_R2_001.fastq.gz @@ -33,7 +33,7 @@ The pipeline will auto-detect whether a sample is single- or paired-end using th A final samplesheet file consisting of both single- and paired-end data may look something like the one below. This is for 6 samples, where `TREATMENT_REP3` has been sequenced twice. -```console +```csv title="samplesheet.csv" sample,fastq_1,fastq_2 CONTROL_REP1,AEG588A1_S1_L002_R1_001.fastq.gz,AEG588A1_S1_L002_R2_001.fastq.gz CONTROL_REP2,AEG588A2_S2_L002_R1_001.fastq.gz,AEG588A2_S2_L002_R2_001.fastq.gz diff --git a/lib/NfcoreTemplate.groovy b/lib/NfcoreTemplate.groovy index 01b8653..e248e4c 100755 --- a/lib/NfcoreTemplate.groovy +++ b/lib/NfcoreTemplate.groovy @@ -4,6 +4,7 @@ import org.yaml.snakeyaml.Yaml import groovy.json.JsonOutput +import nextflow.extension.FilesEx class NfcoreTemplate { @@ -141,12 +142,14 @@ class NfcoreTemplate { try { if (params.plaintext_email) { throw GroovyException('Send plaintext e-mail, not HTML') } // Try to send HTML e-mail using sendmail + def sendmail_tf = new File(workflow.launchDir.toString(), ".sendmail_tmp.html") + sendmail_tf.withWriter { w -> w << sendmail_html } [ 'sendmail', '-t' ].execute() << sendmail_html log.info "-${colors.purple}[$workflow.manifest.name]${colors.green} Sent summary e-mail to $email_address (sendmail)-" } catch (all) { // Catch failures and try with plaintext def mail_cmd = [ 'mail', '-s', subject, '--content-type=text/html', email_address ] - if ( mqc_report.size() <= max_multiqc_email_size.toBytes() ) { + if ( mqc_report != null && mqc_report.size() <= max_multiqc_email_size.toBytes() ) { mail_cmd += [ '-A', mqc_report ] } mail_cmd.execute() << email_html @@ -155,14 +158,16 @@ class NfcoreTemplate { } // Write summary e-mail HTML to a file - def output_d = new File("${params.outdir}/pipeline_info/") - if (!output_d.exists()) { - output_d.mkdirs() - } - def output_hf = new File(output_d, "pipeline_report.html") + def output_hf = new File(workflow.launchDir.toString(), ".pipeline_report.html") output_hf.withWriter { w -> w << email_html } - def output_tf = new File(output_d, "pipeline_report.txt") + FilesEx.copyTo(output_hf.toPath(), "${params.outdir}/pipeline_info/pipeline_report.html"); + output_hf.delete() + + // Write summary e-mail TXT to a file + def output_tf = new File(workflow.launchDir.toString(), ".pipeline_report.txt") output_tf.withWriter { w -> w << email_txt } + FilesEx.copyTo(output_tf.toPath(), "${params.outdir}/pipeline_info/pipeline_report.txt"); + output_tf.delete() } // @@ -227,15 +232,14 @@ class NfcoreTemplate { // Dump pipeline parameters in a json file // public static void dump_parameters(workflow, params) { - def output_d = new File("${params.outdir}/pipeline_info/") - if (!output_d.exists()) { - output_d.mkdirs() - } - def timestamp = new java.util.Date().format( 'yyyy-MM-dd_HH-mm-ss') - def output_pf = new File(output_d, "params_${timestamp}.json") + def filename = "params_${timestamp}.json" + def temp_pf = new File(workflow.launchDir.toString(), ".${filename}") def jsonStr = JsonOutput.toJson(params) - output_pf.text = JsonOutput.prettyPrint(jsonStr) + temp_pf.text = JsonOutput.prettyPrint(jsonStr) + + FilesEx.copyTo(temp_pf.toPath(), "${params.outdir}/pipeline_info/params_${timestamp}.json") + temp_pf.delete() } // diff --git a/modules.json b/modules.json index 6537423..8701cbf 100644 --- a/modules.json +++ b/modules.json @@ -7,17 +7,17 @@ "nf-core": { "custom/dumpsoftwareversions": { "branch": "master", - "git_sha": "911696ea0b62df80e900ef244d7867d177971f73", + "git_sha": "bba7e362e4afead70653f84d8700588ea28d0f9e", "installed_by": ["modules"] }, "fastqc": { "branch": "master", - "git_sha": "bd8092b67b5103bdd52e300f75889442275c3117", + "git_sha": "65ad3e0b9a4099592e1102e92e10455dc661cf53", "installed_by": ["modules"] }, "multiqc": { "branch": "master", - "git_sha": "911696ea0b62df80e900ef244d7867d177971f73", + "git_sha": "4ab13872435962dadc239979554d13709e20bf29", "installed_by": ["modules"] } } diff --git a/modules/nf-core/custom/dumpsoftwareversions/environment.yml b/modules/nf-core/custom/dumpsoftwareversions/environment.yml new file mode 100644 index 0000000..f0c63f6 --- /dev/null +++ b/modules/nf-core/custom/dumpsoftwareversions/environment.yml @@ -0,0 +1,7 @@ +name: custom_dumpsoftwareversions +channels: + - conda-forge + - bioconda + - defaults +dependencies: + - bioconda::multiqc=1.17 diff --git a/modules/nf-core/custom/dumpsoftwareversions/main.nf b/modules/nf-core/custom/dumpsoftwareversions/main.nf index ebc8727..7685b33 100644 --- a/modules/nf-core/custom/dumpsoftwareversions/main.nf +++ b/modules/nf-core/custom/dumpsoftwareversions/main.nf @@ -2,10 +2,10 @@ process CUSTOM_DUMPSOFTWAREVERSIONS { label 'process_single' // Requires `pyyaml` which does not have a dedicated container but is in the MultiQC container - conda "bioconda::multiqc=1.14" + conda "${moduleDir}/environment.yml" container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? - 'https://depot.galaxyproject.org/singularity/multiqc:1.14--pyhdfd78af_0' : - 'biocontainers/multiqc:1.14--pyhdfd78af_0' }" + 'https://depot.galaxyproject.org/singularity/multiqc:1.17--pyhdfd78af_0' : + 'biocontainers/multiqc:1.17--pyhdfd78af_0' }" input: path versions diff --git a/modules/nf-core/custom/dumpsoftwareversions/meta.yml b/modules/nf-core/custom/dumpsoftwareversions/meta.yml index c32657d..5f15a5f 100644 --- a/modules/nf-core/custom/dumpsoftwareversions/meta.yml +++ b/modules/nf-core/custom/dumpsoftwareversions/meta.yml @@ -1,4 +1,4 @@ -# yaml-language-server: $schema=https://raw.githubusercontent.com/nf-core/modules/master/modules/yaml-schema.json +# yaml-language-server: $schema=https://raw.githubusercontent.com/nf-core/modules/master/modules/meta-schema.json name: custom_dumpsoftwareversions description: Custom module used to dump software versions within the nf-core pipeline template keywords: @@ -16,7 +16,6 @@ input: type: file description: YML file containing software versions pattern: "*.yml" - output: - yml: type: file @@ -30,7 +29,9 @@ output: type: file description: File containing software versions pattern: "versions.yml" - authors: - "@drpatelh" - "@grst" +maintainers: + - "@drpatelh" + - "@grst" diff --git a/modules/nf-core/custom/dumpsoftwareversions/tests/main.nf.test b/modules/nf-core/custom/dumpsoftwareversions/tests/main.nf.test new file mode 100644 index 0000000..eec1db1 --- /dev/null +++ b/modules/nf-core/custom/dumpsoftwareversions/tests/main.nf.test @@ -0,0 +1,38 @@ +nextflow_process { + + name "Test Process CUSTOM_DUMPSOFTWAREVERSIONS" + script "../main.nf" + process "CUSTOM_DUMPSOFTWAREVERSIONS" + tag "modules" + tag "modules_nfcore" + tag "custom" + tag "dumpsoftwareversions" + tag "custom/dumpsoftwareversions" + + test("Should run without failures") { + when { + process { + """ + def tool1_version = ''' + TOOL1: + tool1: 0.11.9 + '''.stripIndent() + + def tool2_version = ''' + TOOL2: + tool2: 1.9 + '''.stripIndent() + + input[0] = Channel.of(tool1_version, tool2_version).collectFile() + """ + } + } + + then { + assertAll( + { assert process.success }, + { assert snapshot(process.out).match() } + ) + } + } +} diff --git a/modules/nf-core/custom/dumpsoftwareversions/tests/main.nf.test.snap b/modules/nf-core/custom/dumpsoftwareversions/tests/main.nf.test.snap new file mode 100644 index 0000000..4274ed5 --- /dev/null +++ b/modules/nf-core/custom/dumpsoftwareversions/tests/main.nf.test.snap @@ -0,0 +1,27 @@ +{ + "Should run without failures": { + "content": [ + { + "0": [ + "software_versions.yml:md5,1c851188476409cda5752ce971b20b58" + ], + "1": [ + "software_versions_mqc.yml:md5,2570f4ba271ad08357b0d3d32a9cf84d" + ], + "2": [ + "versions.yml:md5,3843ac526e762117eedf8825b40683df" + ], + "mqc_yml": [ + "software_versions_mqc.yml:md5,2570f4ba271ad08357b0d3d32a9cf84d" + ], + "versions": [ + "versions.yml:md5,3843ac526e762117eedf8825b40683df" + ], + "yml": [ + "software_versions.yml:md5,1c851188476409cda5752ce971b20b58" + ] + } + ], + "timestamp": "2023-11-03T14:43:22.157011" + } +} diff --git a/modules/nf-core/custom/dumpsoftwareversions/tests/tags.yml b/modules/nf-core/custom/dumpsoftwareversions/tests/tags.yml new file mode 100644 index 0000000..405aa24 --- /dev/null +++ b/modules/nf-core/custom/dumpsoftwareversions/tests/tags.yml @@ -0,0 +1,2 @@ +custom/dumpsoftwareversions: + - modules/nf-core/custom/dumpsoftwareversions/** diff --git a/modules/nf-core/fastqc/environment.yml b/modules/nf-core/fastqc/environment.yml new file mode 100644 index 0000000..1787b38 --- /dev/null +++ b/modules/nf-core/fastqc/environment.yml @@ -0,0 +1,7 @@ +name: fastqc +channels: + - conda-forge + - bioconda + - defaults +dependencies: + - bioconda::fastqc=0.12.1 diff --git a/modules/nf-core/fastqc/main.nf b/modules/nf-core/fastqc/main.nf index 249f906..9e19a74 100644 --- a/modules/nf-core/fastqc/main.nf +++ b/modules/nf-core/fastqc/main.nf @@ -2,10 +2,10 @@ process FASTQC { tag "$meta.id" label 'process_medium' - conda "bioconda::fastqc=0.11.9" + conda "${moduleDir}/environment.yml" container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? - 'https://depot.galaxyproject.org/singularity/fastqc:0.11.9--0' : - 'biocontainers/fastqc:0.11.9--0' }" + 'https://depot.galaxyproject.org/singularity/fastqc:0.12.1--hdfd78af_0' : + 'biocontainers/fastqc:0.12.1--hdfd78af_0' }" input: tuple val(meta), path(reads) @@ -37,7 +37,7 @@ process FASTQC { cat <<-END_VERSIONS > versions.yml "${task.process}": - fastqc: \$( fastqc --version | sed -e "s/FastQC v//g" ) + fastqc: \$( fastqc --version | sed '/FastQC v/!d; s/.*v//' ) END_VERSIONS """ @@ -49,7 +49,7 @@ process FASTQC { cat <<-END_VERSIONS > versions.yml "${task.process}": - fastqc: \$( fastqc --version | sed -e "s/FastQC v//g" ) + fastqc: \$( fastqc --version | sed '/FastQC v/!d; s/.*v//' ) END_VERSIONS """ } diff --git a/modules/nf-core/fastqc/meta.yml b/modules/nf-core/fastqc/meta.yml index 4da5bb5..ee5507e 100644 --- a/modules/nf-core/fastqc/meta.yml +++ b/modules/nf-core/fastqc/meta.yml @@ -50,3 +50,8 @@ authors: - "@grst" - "@ewels" - "@FelixKrueger" +maintainers: + - "@drpatelh" + - "@grst" + - "@ewels" + - "@FelixKrueger" diff --git a/modules/nf-core/fastqc/tests/main.nf.test b/modules/nf-core/fastqc/tests/main.nf.test new file mode 100644 index 0000000..b9e8f92 --- /dev/null +++ b/modules/nf-core/fastqc/tests/main.nf.test @@ -0,0 +1,109 @@ +nextflow_process { + + name "Test Process FASTQC" + script "../main.nf" + process "FASTQC" + tag "modules" + tag "modules_nfcore" + tag "fastqc" + + test("Single-Read") { + + when { + params { + outdir = "$outputDir" + } + process { + """ + input[0] = [ + [ id: 'test', single_end:true ], + [ + file(params.test_data['sarscov2']['illumina']['test_1_fastq_gz'], checkIfExists: true) + ] + ] + """ + } + } + + then { + assertAll ( + { assert process.success }, + // NOTE The report contains the date inside it, which means that the md5sum is stable per day, but not longer than that. So you can't md5sum it. + // looks like this:
    Mon 2 Oct 2023
    test.gz
    + // https://github.com/nf-core/modules/pull/3903#issuecomment-1743620039 + { assert process.out.html.get(0).get(1) ==~ ".*/test_fastqc.html" }, + { assert path(process.out.html.get(0).get(1)).getText().contains("File typeConventional base calls") }, + { assert snapshot(process.out.versions).match("versions") }, + { assert process.out.zip.get(0).get(1) ==~ ".*/test_fastqc.zip" } + ) + } + } +// TODO +// // +// // Test with paired-end data +// // +// workflow test_fastqc_paired_end { +// input = [ +// [id: 'test', single_end: false], // meta map +// [ +// file(params.test_data['sarscov2']['illumina']['test_1_fastq_gz'], checkIfExists: true), +// file(params.test_data['sarscov2']['illumina']['test_2_fastq_gz'], checkIfExists: true) +// ] +// ] + +// FASTQC ( input ) +// } + +// // +// // Test with interleaved data +// // +// workflow test_fastqc_interleaved { +// input = [ +// [id: 'test', single_end: false], // meta map +// file(params.test_data['sarscov2']['illumina']['test_interleaved_fastq_gz'], checkIfExists: true) +// ] + +// FASTQC ( input ) +// } + +// // +// // Test with bam data +// // +// workflow test_fastqc_bam { +// input = [ +// [id: 'test', single_end: false], // meta map +// file(params.test_data['sarscov2']['illumina']['test_paired_end_sorted_bam'], checkIfExists: true) +// ] + +// FASTQC ( input ) +// } + +// // +// // Test with multiple samples +// // +// workflow test_fastqc_multiple { +// input = [ +// [id: 'test', single_end: false], // meta map +// [ +// file(params.test_data['sarscov2']['illumina']['test_1_fastq_gz'], checkIfExists: true), +// file(params.test_data['sarscov2']['illumina']['test_2_fastq_gz'], checkIfExists: true), +// file(params.test_data['sarscov2']['illumina']['test2_1_fastq_gz'], checkIfExists: true), +// file(params.test_data['sarscov2']['illumina']['test2_2_fastq_gz'], checkIfExists: true) +// ] +// ] + +// FASTQC ( input ) +// } + +// // +// // Test with custom prefix +// // +// workflow test_fastqc_custom_prefix { +// input = [ +// [ id:'mysample', single_end:true ], // meta map +// file(params.test_data['sarscov2']['illumina']['test_1_fastq_gz'], checkIfExists: true) +// ] + +// FASTQC ( input ) +// } +} diff --git a/modules/nf-core/fastqc/tests/main.nf.test.snap b/modules/nf-core/fastqc/tests/main.nf.test.snap new file mode 100644 index 0000000..636a32c --- /dev/null +++ b/modules/nf-core/fastqc/tests/main.nf.test.snap @@ -0,0 +1,10 @@ +{ + "versions": { + "content": [ + [ + "versions.yml:md5,e1cc25ca8af856014824abd842e93978" + ] + ], + "timestamp": "2023-10-09T23:40:54+0000" + } +} \ No newline at end of file diff --git a/modules/nf-core/fastqc/tests/tags.yml b/modules/nf-core/fastqc/tests/tags.yml new file mode 100644 index 0000000..7834294 --- /dev/null +++ b/modules/nf-core/fastqc/tests/tags.yml @@ -0,0 +1,2 @@ +fastqc: + - modules/nf-core/fastqc/** diff --git a/modules/nf-core/multiqc/environment.yml b/modules/nf-core/multiqc/environment.yml new file mode 100644 index 0000000..bc0bdb5 --- /dev/null +++ b/modules/nf-core/multiqc/environment.yml @@ -0,0 +1,7 @@ +name: multiqc +channels: + - conda-forge + - bioconda + - defaults +dependencies: + - bioconda::multiqc=1.18 diff --git a/modules/nf-core/multiqc/main.nf b/modules/nf-core/multiqc/main.nf index 1fc387b..00cc48d 100644 --- a/modules/nf-core/multiqc/main.nf +++ b/modules/nf-core/multiqc/main.nf @@ -1,10 +1,10 @@ process MULTIQC { label 'process_single' - conda "bioconda::multiqc=1.14" + conda "${moduleDir}/environment.yml" container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? - 'https://depot.galaxyproject.org/singularity/multiqc:1.14--pyhdfd78af_0' : - 'biocontainers/multiqc:1.14--pyhdfd78af_0' }" + 'https://depot.galaxyproject.org/singularity/multiqc:1.18--pyhdfd78af_0' : + 'biocontainers/multiqc:1.18--pyhdfd78af_0' }" input: path multiqc_files, stageAs: "?/*" @@ -25,12 +25,14 @@ process MULTIQC { def args = task.ext.args ?: '' def config = multiqc_config ? "--config $multiqc_config" : '' def extra_config = extra_multiqc_config ? "--config $extra_multiqc_config" : '' + def logo = multiqc_logo ? /--cl-config 'custom_logo: "${multiqc_logo}"'/ : '' """ multiqc \\ --force \\ $args \\ $config \\ $extra_config \\ + $logo \\ . cat <<-END_VERSIONS > versions.yml diff --git a/modules/nf-core/multiqc/meta.yml b/modules/nf-core/multiqc/meta.yml index f93b5ee..f1aa660 100644 --- a/modules/nf-core/multiqc/meta.yml +++ b/modules/nf-core/multiqc/meta.yml @@ -1,5 +1,5 @@ -# yaml-language-server: $schema=https://raw.githubusercontent.com/nf-core/modules/master/modules/yaml-schema.json -name: MultiQC +# yaml-language-server: $schema=https://raw.githubusercontent.com/nf-core/modules/master/modules/meta-schema.json +name: multiqc description: Aggregate results from bioinformatics analyses across many samples into a single report keywords: - QC @@ -13,7 +13,6 @@ tools: homepage: https://multiqc.info/ documentation: https://multiqc.info/docs/ licence: ["GPL-3.0-or-later"] - input: - multiqc_files: type: file @@ -31,7 +30,6 @@ input: type: file description: Optional logo file for MultiQC pattern: "*.{png}" - output: - report: type: file @@ -54,3 +52,8 @@ authors: - "@bunop" - "@drpatelh" - "@jfy133" +maintainers: + - "@abhi18av" + - "@bunop" + - "@drpatelh" + - "@jfy133" diff --git a/modules/nf-core/multiqc/tests/main.nf.test b/modules/nf-core/multiqc/tests/main.nf.test new file mode 100644 index 0000000..c2dad21 --- /dev/null +++ b/modules/nf-core/multiqc/tests/main.nf.test @@ -0,0 +1,63 @@ +nextflow_process { + + name "Test Process MULTIQC" + script "../main.nf" + process "MULTIQC" + tag "modules" + tag "modules_nfcore" + tag "multiqc" + + test("MULTIQC: FASTQC") { + + when { + params { + outdir = "$outputDir" + } + process { + """ + input[0] = Channel.of([file(params.test_data['sarscov2']['illumina']['test_1_fastq_gz_fastqc_zip'], checkIfExists: true)]) + input[1] = [] + input[2] = [] + input[3] = [] + """ + } + } + + then { + assertAll( + { assert process.success }, + { assert path(process.out.report.get(0)).exists() }, + { assert path(process.out.data.get(0)).exists() }, + { assert path(process.out.versions.get(0)).getText().contains("multiqc") } + ) + } + + } + + test("MULTIQC: FASTQC and a config file") { + + when { + params { + outdir = "$outputDir" + } + process { + """ + input[0] = Channel.of([file(params.test_data['sarscov2']['illumina']['test_1_fastq_gz_fastqc_zip'], checkIfExists: true)]) + input[1] = Channel.of(file("https://github.com/nf-core/tools/raw/dev/nf_core/pipeline-template/assets/multiqc_config.yml", checkIfExists: true)) + input[2] = [] + input[3] = [] + """ + } + } + + then { + assertAll( + { assert process.success }, + { assert path(process.out.report.get(0)).exists() }, + { assert path(process.out.data.get(0)).exists() }, + { assert path(process.out.versions.get(0)).getText().contains("multiqc") } + ) + } + + } +} diff --git a/modules/nf-core/multiqc/tests/tags.yml b/modules/nf-core/multiqc/tests/tags.yml new file mode 100644 index 0000000..bea6c0d --- /dev/null +++ b/modules/nf-core/multiqc/tests/tags.yml @@ -0,0 +1,2 @@ +multiqc: + - modules/nf-core/multiqc/** diff --git a/nextflow.config b/nextflow.config index 0540a11..419b27b 100644 --- a/nextflow.config +++ b/nextflow.config @@ -14,7 +14,7 @@ params { input = null // References genome = null - igenomes_base = 's3://ngi-igenomes/igenomes' + igenomes_base = 's3://ngi-igenomes/igenomes/' igenomes_ignore = false @@ -82,6 +82,7 @@ profiles { dumpHashes = true process.beforeScript = 'echo $HOSTNAME' cleanup = false + nextflow.enable.configProcessNamesValidation = true } conda { conda.enabled = true @@ -104,13 +105,13 @@ profiles { } docker { docker.enabled = true - docker.userEmulation = true conda.enabled = false singularity.enabled = false podman.enabled = false shifter.enabled = false charliecloud.enabled = false apptainer.enabled = false + runOptions = '-u $(id -u):$(id -g)' } arm { docker.runOptions = '-u $(id -u):$(id -g) --platform=linux/amd64' @@ -181,7 +182,7 @@ singularity.registry = 'quay.io' // Nextflow plugins plugins { - id 'nf-validation' // Validation of pipeline parameters and creation of an input channel from a sample sheet + id 'nf-validation@1.1.3' // Validation of pipeline parameters and creation of an input channel from a sample sheet } // Load igenomes.config if required @@ -204,6 +205,9 @@ env { // Capture exit codes from upstream processes when piping process.shell = ['/bin/bash', '-euo', 'pipefail'] +// Disable process selector warnings by default. Use debug profile to enable warnings. +nextflow.enable.configProcessNamesValidation = false + def trace_timestamp = new java.util.Date().format( 'yyyy-MM-dd_HH-mm-ss') timeline { enabled = true @@ -224,7 +228,7 @@ dag { manifest { name = 'nf-core/molkart' - author = """@FloWuenne""" + author = """@kbestak, @FloWuenne""" homePage = 'https://github.com/nf-core/molkart' description = """An analysis pipeline for Molecular Cartography data from Resolve Biosciences.""" mainScript = 'main.nf' From 45a4ca9bc655a3f781488dde6472a96eded76f47 Mon Sep 17 00:00:00 2001 From: nf-core-bot Date: Wed, 20 Dec 2023 15:57:13 +0000 Subject: [PATCH 115/149] Template update for nf-core/tools version 2.11.1 --- .../{release-announcments.yml => release-announcements.yml} | 0 nextflow.config | 4 ++-- 2 files changed, 2 insertions(+), 2 deletions(-) rename .github/workflows/{release-announcments.yml => release-announcements.yml} (100%) diff --git a/.github/workflows/release-announcments.yml b/.github/workflows/release-announcements.yml similarity index 100% rename from .github/workflows/release-announcments.yml rename to .github/workflows/release-announcements.yml diff --git a/nextflow.config b/nextflow.config index 419b27b..8bcaf43 100644 --- a/nextflow.config +++ b/nextflow.config @@ -111,10 +111,10 @@ profiles { shifter.enabled = false charliecloud.enabled = false apptainer.enabled = false - runOptions = '-u $(id -u):$(id -g)' + docker.runOptions = '-u $(id -u):$(id -g)' } arm { - docker.runOptions = '-u $(id -u):$(id -g) --platform=linux/amd64' + docker.runOptions = '-u $(id -u):$(id -g) --platform=linux/amd64' } singularity { singularity.enabled = true From 6223d0d317b43c8c196b5e03fa6d1944fc20d313 Mon Sep 17 00:00:00 2001 From: Florian Wuennemann Date: Thu, 4 Jan 2024 14:49:13 +0000 Subject: [PATCH 116/149] Added createanndata process after spot2cell. --- bin/create_anndata.py | 0 modules/local/createanndata.nf | 4 ++-- workflows/molkart.nf | 9 +++++++++ 3 files changed, 11 insertions(+), 2 deletions(-) mode change 100644 => 100755 bin/create_anndata.py diff --git a/bin/create_anndata.py b/bin/create_anndata.py old mode 100644 new mode 100755 diff --git a/modules/local/createanndata.nf b/modules/local/createanndata.nf index b84e0e4..45a56bf 100644 --- a/modules/local/createanndata.nf +++ b/modules/local/createanndata.nf @@ -8,7 +8,7 @@ process CREATE_ANNDATA { tuple val(meta), path(spot2cell) output: - tuple val(meta), path("*.adata"), emit: stack + tuple val(meta), path("*.adata") , emit: stack path "versions.yml" , emit: versions when: @@ -23,7 +23,7 @@ process CREATE_ANNDATA { --input ${spot2cell} \\ --spatial_cols X_centroid Y_centroid \\ --exclude_cols CellID Area MajorAxisLength MinorAxisLength Eccentricity Solidity Extent Orientation \\ - --output test.adata + --output ${prefix}.adata $args cat <<-END_VERSIONS > versions.yml diff --git a/workflows/molkart.nf b/workflows/molkart.nf index 2614123..54d3763 100644 --- a/workflows/molkart.nf +++ b/workflows/molkart.nf @@ -41,6 +41,7 @@ include { MOLKARTQC } from '../modules/local/molkartqc' include { MOLKARTQCPNG } from '../modules/local/molkartqcpng' include { SPOT2CELL } from '../modules/local/spot2cell' include { TIFFH5CONVERT } from '../modules/local/tiffh5convert' +include { CREATE_ANNDATA } from '../modules/local/createanndata' // // SUBWORKFLOW: Consisting of a mix of local and nf-core/modules @@ -288,6 +289,14 @@ workflow MOLKART { ) ch_versions = ch_versions.mix(SPOT2CELL.out.versions) + // + // MODULE: create anndata squidpy object from spot2cell table + // + CREATE_ANNDATA( + SPOT2CELL.out.cellxgene_table + ) + ch_versions = ch_versions.mix(CREATE_ANNDATA.out.versions) + // // MODULE: MOLKARTQC // From ce431c666e80ff4a0cdb5c5ee5998cc318d385cc Mon Sep 17 00:00:00 2001 From: Florian Wuennemann Date: Thu, 4 Jan 2024 14:52:33 +0000 Subject: [PATCH 117/149] Updated molkart-local version to v0.0.3 for all local modules. --- modules/local/clahe.nf | 2 +- modules/local/createstack.nf | 2 +- modules/local/crophdf5.nf | 2 +- modules/local/croptiff.nf | 2 +- modules/local/maskfilter.nf | 2 +- modules/local/molkartqc.nf | 2 +- modules/local/molkartqcpng.nf | 2 +- modules/local/spot2cell.nf | 2 +- modules/local/tiffh5convert.nf | 2 +- 9 files changed, 9 insertions(+), 9 deletions(-) diff --git a/modules/local/clahe.nf b/modules/local/clahe.nf index 701eda7..718faf4 100644 --- a/modules/local/clahe.nf +++ b/modules/local/clahe.nf @@ -2,7 +2,7 @@ process CLAHE{ tag "$meta.id" label 'process_medium' - container 'ghcr.io/schapirolabor/molkart-local:v0.0.1' + container 'ghcr.io/schapirolabor/molkart-local:v0.0.3' input: tuple val(meta), path(image) diff --git a/modules/local/createstack.nf b/modules/local/createstack.nf index fd74205..e40df17 100644 --- a/modules/local/createstack.nf +++ b/modules/local/createstack.nf @@ -2,7 +2,7 @@ process CREATE_STACK { tag "$meta.id" label 'process_low' - container 'ghcr.io/schapirolabor/molkart-local:v0.0.1' + container 'ghcr.io/schapirolabor/molkart-local:v0.0.3' input: tuple val(meta), path(image) diff --git a/modules/local/crophdf5.nf b/modules/local/crophdf5.nf index a845dd4..c763878 100644 --- a/modules/local/crophdf5.nf +++ b/modules/local/crophdf5.nf @@ -2,7 +2,7 @@ process CROPHDF5 { tag "$meta.id" label 'process_single' - container 'ghcr.io/schapirolabor/molkart-local:v0.0.1' + container 'ghcr.io/schapirolabor/molkart-local:v0.0.3' input: tuple val(meta), path(image_stack), val(num_channels) diff --git a/modules/local/croptiff.nf b/modules/local/croptiff.nf index 93b936d..e9f3421 100644 --- a/modules/local/croptiff.nf +++ b/modules/local/croptiff.nf @@ -2,7 +2,7 @@ process CROPTIFF { tag "$meta.id" label 'process_single' - container 'ghcr.io/schapirolabor/molkart-local:v0.0.1' + container 'ghcr.io/schapirolabor/molkart-local:v0.0.3' input: tuple val(meta), path(image_stack) diff --git a/modules/local/maskfilter.nf b/modules/local/maskfilter.nf index 23cbc67..8a6f6a2 100644 --- a/modules/local/maskfilter.nf +++ b/modules/local/maskfilter.nf @@ -2,7 +2,7 @@ process MASKFILTER { tag "$meta.id" label 'process_medium' - container 'ghcr.io/schapirolabor/molkart-local:v0.0.1' + container 'ghcr.io/schapirolabor/molkart-local:v0.0.3' input: tuple val(meta), path(mask) diff --git a/modules/local/molkartqc.nf b/modules/local/molkartqc.nf index 6ac7346..cbcc5ef 100644 --- a/modules/local/molkartqc.nf +++ b/modules/local/molkartqc.nf @@ -2,7 +2,7 @@ process MOLKARTQC{ tag "$meta.id" label 'process_single' - container 'ghcr.io/schapirolabor/molkart-local:v0.0.1' + container 'ghcr.io/schapirolabor/molkart-local:v0.0.3' input: tuple val(meta), path(spot_table), path(cellxgene_table), val(segmethod), path(filterqc) diff --git a/modules/local/molkartqcpng.nf b/modules/local/molkartqcpng.nf index 9ab4f64..e920ea8 100644 --- a/modules/local/molkartqcpng.nf +++ b/modules/local/molkartqcpng.nf @@ -1,7 +1,7 @@ process MOLKARTQCPNG { label 'process_single' - container 'ghcr.io/schapirolabor/molkart-local:v0.0.1' + container 'ghcr.io/schapirolabor/molkart-local:v0.0.3' input: path(png) diff --git a/modules/local/spot2cell.nf b/modules/local/spot2cell.nf index 8048b6a..97ed638 100644 --- a/modules/local/spot2cell.nf +++ b/modules/local/spot2cell.nf @@ -3,7 +3,7 @@ process SPOT2CELL{ tag "$meta.id" label 'process_single' - container 'ghcr.io/schapirolabor/molkart-local:v0.0.1' + container 'ghcr.io/schapirolabor/molkart-local:v0.0.3' input: tuple val(meta) , path(spot_table) diff --git a/modules/local/tiffh5convert.nf b/modules/local/tiffh5convert.nf index ffec3b8..c3d1158 100644 --- a/modules/local/tiffh5convert.nf +++ b/modules/local/tiffh5convert.nf @@ -2,7 +2,7 @@ process TIFFH5CONVERT { tag "$meta.id" label 'process_single' - container "ghcr.io/schapirolabor/molkart-local:v0.0.1" + container "ghcr.io/schapirolabor/molkart-local:v0.0.3" input: tuple val(meta), path(image), val(num_channels) From a2444c372372d90422a4b00d4415d43a207be7a1 Mon Sep 17 00:00:00 2001 From: Florian Wuennemann Date: Thu, 4 Jan 2024 15:32:53 +0000 Subject: [PATCH 118/149] Modified create anndata code to add regionprops to adata.obs. --- bin/create_anndata.py | 18 ++++++++++++++---- conf/modules.config | 8 ++++++++ modules/local/createanndata.nf | 3 +-- 3 files changed, 23 insertions(+), 6 deletions(-) diff --git a/bin/create_anndata.py b/bin/create_anndata.py index 5c7491a..b649c9b 100755 --- a/bin/create_anndata.py +++ b/bin/create_anndata.py @@ -20,7 +20,6 @@ def get_args(): inputs = parser.add_argument_group(title="Required Input", description="Path to required input file") inputs.add_argument("-i", "--input", type=str, help="Path to the spot2cell csv file.") inputs.add_argument("-s", "--spatial_cols", nargs="+", help="Column names for location data.") - inputs.add_argument("-e", "--exclude_cols", nargs="+", help="Column names to exclude from count table.") inputs.add_argument( "-o", "--output", dest="output", action="store", required=True, help="Path to output anndata object." ) @@ -31,16 +30,27 @@ def get_args(): return arg -def create_spatial_anndata(input, spatial_cols, exclude_cols): +def create_spatial_anndata(input, spatial_cols): df = pd.read_csv(input) spatial_coords = np.array(df[args.spatial_cols].values.tolist()) - count_table = csr_matrix(df.drop(spatial_cols + exclude_cols, axis=1).values.tolist()) + # Find the index of 'Y_centroid' column + y_centroid_index = df.columns.get_loc('X_centroid') + # Create a list of all columns from 'Y_centroid' to the end + metadata_cols = df.columns[y_centroid_index:] + # Extract the excluded columns as metadata + metadata = df[metadata_cols] + + count_table = csr_matrix(df.drop(list(metadata_cols), axis=1).values.tolist()) adata = AnnData(count_table, obsm={"spatial": spatial_coords}) + # Add the metadata to adata.obs + for col in metadata.columns: + adata.obs[col] = metadata[col].values + adata.obs_names = [f"Cell_{i:d}" for i in range(adata.n_obs)] return adata def main(args): - adata = create_spatial_anndata(args.input, args.spatial_cols, args.exclude_cols) + adata = create_spatial_anndata(args.input, args.spatial_cols) adata.write(args.output) diff --git a/conf/modules.config b/conf/modules.config index e248d3f..1417976 100644 --- a/conf/modules.config +++ b/conf/modules.config @@ -211,4 +211,12 @@ process { saveAs: { filename -> "${meta.id}_cellpose_mask.tif" } ] } + + withName: "CREATE_ANNDATA" { + publishDir = [ + path: "${params.outdir}/anndata", + mode: params.publish_dir_mode, + pattern: "*.{adata}" + ] + } } diff --git a/modules/local/createanndata.nf b/modules/local/createanndata.nf index 45a56bf..09592ff 100644 --- a/modules/local/createanndata.nf +++ b/modules/local/createanndata.nf @@ -22,8 +22,7 @@ process CREATE_ANNDATA { create_anndata.py \\ --input ${spot2cell} \\ --spatial_cols X_centroid Y_centroid \\ - --exclude_cols CellID Area MajorAxisLength MinorAxisLength Eccentricity Solidity Extent Orientation \\ - --output ${prefix}.adata + --output ${prefix}.adata \\ $args cat <<-END_VERSIONS > versions.yml From 0f6bc16f14f6329c3d09bd17e8cef9212fb17b72 Mon Sep 17 00:00:00 2001 From: Florian Wuennemann Date: Thu, 4 Jan 2024 15:34:02 +0000 Subject: [PATCH 119/149] Prettier fix. --- bin/create_anndata.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/bin/create_anndata.py b/bin/create_anndata.py index b649c9b..5725397 100755 --- a/bin/create_anndata.py +++ b/bin/create_anndata.py @@ -34,7 +34,7 @@ def create_spatial_anndata(input, spatial_cols): df = pd.read_csv(input) spatial_coords = np.array(df[args.spatial_cols].values.tolist()) # Find the index of 'Y_centroid' column - y_centroid_index = df.columns.get_loc('X_centroid') + y_centroid_index = df.columns.get_loc("X_centroid") # Create a list of all columns from 'Y_centroid' to the end metadata_cols = df.columns[y_centroid_index:] # Extract the excluded columns as metadata From b2db2eb0c0acece21b6da3d13fcb04a924677d6c Mon Sep 17 00:00:00 2001 From: Florian Wuennemann Date: Thu, 4 Jan 2024 15:37:15 +0000 Subject: [PATCH 120/149] Changelog update. --- CHANGELOG.md | 10 ++++++++++ 1 file changed, 10 insertions(+) diff --git a/CHANGELOG.md b/CHANGELOG.md index fe8bcc1..82283b2 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -3,6 +3,16 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/) and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html). +## v1.0.1dev - [2024.01.04] + +### `Added` + +- Added createanndata process to workflow. This process will generate a spatial anndata object from the spot2cell output. The anndata object will be written to /anndata in the output folder. + +### `Fixed` + +- Updated version numbers for all local modules using the molkart-local container to v0.0.3 + ## v1.0.1dev - [2023.12.19] ### `Fixed` From 9f2c81fd4a7fc65cbed9fbaab7e826547a8262ec Mon Sep 17 00:00:00 2001 From: Florian Wuennemann Date: Thu, 4 Jan 2024 15:44:45 +0000 Subject: [PATCH 121/149] Added anndata to output.md --- docs/output.md | 13 +++++++++++++ 1 file changed, 13 insertions(+) diff --git a/docs/output.md b/docs/output.md index 00786ab..4a35e8c 100644 --- a/docs/output.md +++ b/docs/output.md @@ -16,6 +16,7 @@ The pipeline is built using [Nextflow](https://www.nextflow.io/) and processes d - [segmentation](#segmentation) - Segment single cells from provided image using segmentation method of choice (Cellpose, Mesmer, ilastik) and filter them by size. - [Mindagap_duplicatefinder](#Mindagap) - Take a spot table and search for duplicates along grid lines. - [Spot2cell](#spot2cell) - Assign non-duplicated spots to segmented cells based on segmentation mask and extract cell shape information. +- [Create_anndata](#anndata) - Creates a spatial AnnData object as described in the [Squidpy tutorial](https://squidpy.readthedocs.io/en/stable/notebooks/tutorials/tutorial_read_spatial.html). - [MolkartQC](#molkartqc) - Produce QC metrics specific to this pipeline. - [MultiQC](#multiqc) - Aggregate report describing results and QC from the whole pipeline. - [Pipeline information](#pipeline-information) - Report metrics generated during the workflow execution. @@ -93,6 +94,18 @@ Create stack is a local module used to merge images into a stack as preparation Spot2cell is a local module that assigns spots (without Duplicates) to cells via a spot table and segmentation mask. +### Create_anndata + +
    +Output files + +- `anndata/` + - `*.adata`: Anndata object containing the spot count table, spatial locations of cells in `adata.obsm` and metadata like 'Area', 'MajorAxisLength', 'MinorAxisLength', 'Eccentricity', 'Solidity', 'Extent', 'Orientation' in `adata.obs` + +
    + +CREATE_ANNDATA is a local module that generates an [AnnData object](https://anndata.readthedocs.io/en/latest/) storing expression, metadadata and spatial locations of cells. + ### MolkartQC
    From 01ff5c92368379f2dfb756198f37ad492771faa4 Mon Sep 17 00:00:00 2001 From: Florian Wuennemann Date: Thu, 4 Jan 2024 15:47:51 +0000 Subject: [PATCH 122/149] Added anndata to CITATIONS.md --- CITATIONS.md | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/CITATIONS.md b/CITATIONS.md index 6b28ae6..0248a6d 100644 --- a/CITATIONS.md +++ b/CITATIONS.md @@ -10,6 +10,10 @@ ## Pipeline tools +- [anndata](https://anndata.readthedocs.io/en/latest/) + + > Isaac Virshup, Sergei Rybakov, Fabian J. Theis, Philipp Angerer, F. Alexander Wolf anndata: Annotated data > bioRxiv 2021.12.16.473007; doi: https://doi.org/10.1101/2021.12.16.473007 + - [Cellpose](https://www.cellpose.org/) > Stringer, C., Wang, T., Michaelos, M. et al. Cellpose: a generalist algorithm for cellular segmentation. Nat Methods 18, 100–106 (2021). https://doi.org/10.1038/s41592-020-01018-x From e095a690a09219c866b2d60dca9f7d73701e7fa2 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Fri, 5 Jan 2024 11:43:32 +0000 Subject: [PATCH 123/149] minor_fixes --- CHANGELOG.md | 4 ++++ bin/spot2cell.py | 10 +--------- conf/modules.config | 3 ++- docs/output.md | 28 ++++++++++++++-------------- modules/local/clahe.nf | 2 +- modules/local/createanndata.nf | 6 +++--- modules/local/createstack.nf | 6 +++--- modules/local/croptiff.nf | 2 +- modules/local/maskfilter.nf | 2 +- modules/local/molkartqc.nf | 2 +- modules/local/spot2cell.nf | 4 +--- modules/local/tiffh5convert.nf | 2 +- tests/main.nf.test | 4 ++++ tests/main.nf.test.snap | 8 ++++++-- workflows/molkart.nf | 21 ++++++++++----------- 15 files changed, 53 insertions(+), 51 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 82283b2..983422e 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -8,10 +8,14 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 ### `Added` - Added createanndata process to workflow. This process will generate a spatial anndata object from the spot2cell output. The anndata object will be written to /anndata in the output folder. +- added tests for createanndata ### `Fixed` - Updated version numbers for all local modules using the molkart-local container to v0.0.3 +- spot2cell - removed tag, output name now required, output name defined in modules.config +- output documentation for create training subset +- formatting in local modules ## v1.0.1dev - [2023.12.19] diff --git a/bin/spot2cell.py b/bin/spot2cell.py index 10e97b5..1e5e5a3 100755 --- a/bin/spot2cell.py +++ b/bin/spot2cell.py @@ -111,7 +111,6 @@ def assign_spots2cell(spot_table, cell_mask): parser = argparse.ArgumentParser() parser.add_argument("-s", "--spot_table", help="Spot table to project.") parser.add_argument("-c", "--cell_mask", help="Sample ID.") - parser.add_argument("--tag", type=str, help="Additional tag to append to filename") parser.add_argument("--output", type=str, help="Output path") parser.add_argument("--version", action="version", version="0.1.0") @@ -126,11 +125,4 @@ def assign_spots2cell(spot_table, cell_mask): gene_counts_df, background = assign_spots2cell(spot_data, cell_mask) - if args.output: - outpath = args.output - - else: - basename = os.path.basename(args.spot_table) - basename = os.path.splitext(basename)[0] - outpath = f"{basename}.{args.tag}.cellxgene.csv" - gene_counts_df.to_csv(outpath, sep=",", header=True, index=False) + gene_counts_df.to_csv(args.output, sep=",", header=True, index=False) diff --git a/conf/modules.config b/conf/modules.config index 1417976..85f3174 100644 --- a/conf/modules.config +++ b/conf/modules.config @@ -101,7 +101,7 @@ process { } withName: "SPOT2CELL" { - ext.prefix = { "${meta.id}_${tag}"} + ext.prefix = { "${meta.id}_${meta.segmentation}"} publishDir = [ path: { "${params.outdir}/spot2cell" }, pattern: "*.csv", @@ -213,6 +213,7 @@ process { } withName: "CREATE_ANNDATA" { + ext.prefix = { "${meta.id}_${meta.segmentation}"} publishDir = [ path: "${params.outdir}/anndata", mode: params.publish_dir_mode, diff --git a/docs/output.md b/docs/output.md index 4a35e8c..2dd3cc0 100644 --- a/docs/output.md +++ b/docs/output.md @@ -16,7 +16,7 @@ The pipeline is built using [Nextflow](https://www.nextflow.io/) and processes d - [segmentation](#segmentation) - Segment single cells from provided image using segmentation method of choice (Cellpose, Mesmer, ilastik) and filter them by size. - [Mindagap_duplicatefinder](#Mindagap) - Take a spot table and search for duplicates along grid lines. - [Spot2cell](#spot2cell) - Assign non-duplicated spots to segmented cells based on segmentation mask and extract cell shape information. -- [Create_anndata](#anndata) - Creates a spatial AnnData object as described in the [Squidpy tutorial](https://squidpy.readthedocs.io/en/stable/notebooks/tutorials/tutorial_read_spatial.html). +- [Create AnnData](#anndata) - Creates a spatial AnnData object as described in the [Squidpy tutorial](https://squidpy.readthedocs.io/en/stable/notebooks/tutorials/tutorial_read_spatial.html). - [MolkartQC](#molkartqc) - Produce QC metrics specific to this pipeline. - [MultiQC](#multiqc) - Aggregate report describing results and QC from the whole pipeline. - [Pipeline information](#pipeline-information) - Report metrics generated during the workflow execution. @@ -104,7 +104,7 @@ Spot2cell is a local module that assigns spots (without Duplicates) to cells via
    -CREATE_ANNDATA is a local module that generates an [AnnData object](https://anndata.readthedocs.io/en/latest/) storing expression, metadadata and spatial locations of cells. +CREATE_ANNDATA is a local module that generates an [AnnData object](https://anndata.readthedocs.io/en/latest/) storing expression, metadata and spatial locations of cells. ### MolkartQC @@ -136,17 +136,6 @@ MolkartQC is a local module used for gathering useful quality-control metrics fo Results generated by MultiQC collate pipeline QC from supported tools e.g. FastQC. The pipeline has special steps which also allow the software versions to be reported in the MultiQC output for future traceability. For more information about how to use MultiQC reports, see . -### Pipeline information - -
    -Output files - -- `pipeline_info/` - - Reports generated by Nextflow: `execution_report.html`, `execution_timeline.html`, `execution_trace.txt` and `pipeline_dag.dot`/`pipeline_dag.svg`. - - Reports generated by the pipeline: `pipeline_report.html`, `pipeline_report.txt` and `software_versions.yml`. The `pipeline_report*` files will only be present if the `--email` / `--email_on_fail` parameters are used when running the pipeline. - - Reformatted samplesheet files used as input to the pipeline: `samplesheet.valid.csv`. - - Parameters used by the pipeline run: `params.json`. - ### create-training-subset
    @@ -160,7 +149,18 @@ Results generated by MultiQC collate pipeline QC from supported tools e.g. FastQ
    -Spot2cell is a local module that assigns spots (without Duplicates) to cells via a spot table and segmentation mask. +Create training subset is an optional group of modules that create crops in `hdf5` and `tiff` formats, as well as provide the crop overview for reusability. + +### Pipeline information + +
    +Output files + +- `pipeline_info/` + - Reports generated by Nextflow: `execution_report.html`, `execution_timeline.html`, `execution_trace.txt` and `pipeline_dag.dot`/`pipeline_dag.svg`. + - Reports generated by the pipeline: `pipeline_report.html`, `pipeline_report.txt` and `software_versions.yml`. The `pipeline_report*` files will only be present if the `--email` / `--email_on_fail` parameters are used when running the pipeline. + - Reformatted samplesheet files used as input to the pipeline: `samplesheet.valid.csv`. + - Parameters used by the pipeline run: `params.json`.
    diff --git a/modules/local/clahe.nf b/modules/local/clahe.nf index 718faf4..5585eba 100644 --- a/modules/local/clahe.nf +++ b/modules/local/clahe.nf @@ -15,7 +15,7 @@ process CLAHE{ task.ext.when == null || task.ext.when script: - def args = task.ext.args ?: '' + def args = task.ext.args ?: '' def prefix = task.ext.prefix ?: "${meta.id}" """ apply_clahe.dask.py \\ diff --git a/modules/local/createanndata.nf b/modules/local/createanndata.nf index 09592ff..244df8d 100644 --- a/modules/local/createanndata.nf +++ b/modules/local/createanndata.nf @@ -8,14 +8,14 @@ process CREATE_ANNDATA { tuple val(meta), path(spot2cell) output: - tuple val(meta), path("*.adata") , emit: stack - path "versions.yml" , emit: versions + tuple val(meta), path("*.adata") , emit: stack + path "versions.yml" , emit: versions when: task.ext.when == null || task.ext.when script: - def args = task.ext.args ?: '' + def args = task.ext.args ?: '' def prefix = task.ext.prefix ?: "${meta.id}" """ diff --git a/modules/local/createstack.nf b/modules/local/createstack.nf index e40df17..08e9031 100644 --- a/modules/local/createstack.nf +++ b/modules/local/createstack.nf @@ -8,14 +8,14 @@ process CREATE_STACK { tuple val(meta), path(image) output: - tuple val(meta), path("*.ome.tif"), emit: stack - path "versions.yml" , emit: versions + tuple val(meta), path("*.ome.tif") , emit: stack + path "versions.yml" , emit: versions when: task.ext.when == null || task.ext.when script: - def args = task.ext.args ?: '' + def args = task.ext.args ?: '' def prefix = task.ext.prefix ?: "${meta.id}" """ diff --git a/modules/local/croptiff.nf b/modules/local/croptiff.nf index e9f3421..3ac77f4 100644 --- a/modules/local/croptiff.nf +++ b/modules/local/croptiff.nf @@ -17,7 +17,7 @@ process CROPTIFF { task.ext.when == null || task.ext.when script: - def args = task.ext.args ?: '' + def args = task.ext.args ?: '' def prefix = task.ext.prefix ?: "${meta.id}" """ diff --git a/modules/local/maskfilter.nf b/modules/local/maskfilter.nf index 8a6f6a2..3a4f84d 100644 --- a/modules/local/maskfilter.nf +++ b/modules/local/maskfilter.nf @@ -16,7 +16,7 @@ process MASKFILTER { task.ext.when == null || task.ext.when script: - def args = task.ext.args ?: '' + def args = task.ext.args ?: '' def prefix = task.ext.prefix ?: "${meta.id}" """ diff --git a/modules/local/molkartqc.nf b/modules/local/molkartqc.nf index cbcc5ef..a0af1ec 100644 --- a/modules/local/molkartqc.nf +++ b/modules/local/molkartqc.nf @@ -15,7 +15,7 @@ process MOLKARTQC{ task.ext.when == null || task.ext.when script: - def args = task.ext.args ?: '' + def args = task.ext.args ?: '' def prefix = task.ext.prefix ?: "${meta.id}" """ diff --git a/modules/local/spot2cell.nf b/modules/local/spot2cell.nf index 97ed638..a8259cf 100644 --- a/modules/local/spot2cell.nf +++ b/modules/local/spot2cell.nf @@ -8,7 +8,6 @@ process SPOT2CELL{ input: tuple val(meta) , path(spot_table) tuple val(meta2), path(cell_mask) - val(tag) output: tuple val(meta), path("*.csv"), emit: cellxgene_table @@ -18,14 +17,13 @@ process SPOT2CELL{ task.ext.when == null || task.ext.when script: - def args = task.ext.args ?: '' + def args = task.ext.args ?: '' def prefix = task.ext.prefix ?: "${meta.id}" """ spot2cell.py \\ --spot_table ${spot_table} \\ --cell_mask ${cell_mask} \\ - --tag ${tag} \\ --output ${prefix}.csv \\ $args diff --git a/modules/local/tiffh5convert.nf b/modules/local/tiffh5convert.nf index c3d1158..a283b33 100644 --- a/modules/local/tiffh5convert.nf +++ b/modules/local/tiffh5convert.nf @@ -15,7 +15,7 @@ process TIFFH5CONVERT { task.ext.when == null || task.ext.when script: - def args = task.ext.args ?: '' + def args = task.ext.args ?: '' def prefix = task.ext.prefix ?: "${meta.id}" """ diff --git a/tests/main.nf.test b/tests/main.nf.test index 490ee28..0080994 100644 --- a/tests/main.nf.test +++ b/tests/main.nf.test @@ -29,6 +29,8 @@ nextflow_pipeline { path("$outputDir/segmentation/filtered_masks/nuc_only_cellpose_filtered.tif"), path("$outputDir/spot2cell/cellxgene_nuc_only_cellpose.csv"), path("$outputDir/spot2cell/cellxgene_nuc_only_mesmer.csv"), + path("$outputDir/anndata/nuc_only_cellpose.adata"), + path("$outputDir/anndata/nuc_only_mesmer.adata"), path("$outputDir/molkartqc/nuc_only.cellpose.spot_QC.csv"), path("$outputDir/molkartqc/nuc_only.mesmer.spot_QC.csv") ).match() @@ -60,6 +62,8 @@ nextflow_pipeline { path("$outputDir/segmentation/filtered_masks/mem_only_cellpose_filtered.tif"), path("$outputDir/spot2cell/cellxgene_mem_only_cellpose.csv"), path("$outputDir/spot2cell/cellxgene_mem_only_mesmer.csv"), + path("$outputDir/anndata/mem_only_cellpose.adata"), + path("$outputDir/anndata/mem_only_mesmer.adata"), path("$outputDir/molkartqc/mem_only.cellpose.spot_QC.csv"), path("$outputDir/molkartqc/mem_only.mesmer.spot_QC.csv"), ).match() diff --git a/tests/main.nf.test.snap b/tests/main.nf.test.snap index fc71229..58e4a17 100644 --- a/tests/main.nf.test.snap +++ b/tests/main.nf.test.snap @@ -10,10 +10,12 @@ "mem_only_cellpose_filtered.tif:md5,590591f541b6d3f17810cd44dd71b252", "cellxgene_mem_only_cellpose.csv:md5,f063c1ce5e93e1e73431af36c6bc1e79", "cellxgene_mem_only_mesmer.csv:md5,198b187d5f151077437aa591f5991b22", + "mem_only_cellpose.adata:md5,b47ea63ffea0947e43511f17b6920cd8", + "mem_only_mesmer.adata:md5,530649647a3466316ea52dde9dede4ab", "mem_only.cellpose.spot_QC.csv:md5,df312175498f7942bffc33f2c2d8d1c9", "mem_only.mesmer.spot_QC.csv:md5,3273bd6fecf93a3d240614d1b38831c9" ], - "timestamp": "2023-12-07T15:13:30.564809013" + "timestamp": "2024-01-05T11:19:49.882138591" }, "Nuclear channel, mesmer and cellpose, without clahe": { "content": [ @@ -25,10 +27,12 @@ "nuc_only_cellpose_filtered.tif:md5,2784d8c6683ad80c24d8df4121e1128f", "cellxgene_nuc_only_cellpose.csv:md5,0610a8713457c28acf1bc4c298bee8e3", "cellxgene_nuc_only_mesmer.csv:md5,425cfb90a60b564e4bfff09ac5ea94c7", + "nuc_only_cellpose.adata:md5,fd52e62711465d754fd36a433761cb3b", + "nuc_only_mesmer.adata:md5,cd20ab6db5274bb85c960ea3bd8d2619", "nuc_only.cellpose.spot_QC.csv:md5,e77b5973e0997170d0fde5c5901ad551", "nuc_only.mesmer.spot_QC.csv:md5,f8f4eb85bb8269341ac072ac78962ed4" ], - "timestamp": "2023-12-07T15:07:51.353007277" + "timestamp": "2024-01-05T11:18:48.214995389" }, "Create training subset": { "content": [ diff --git a/workflows/molkart.nf b/workflows/molkart.nf index 54d3763..2e6a86e 100644 --- a/workflows/molkart.nf +++ b/workflows/molkart.nf @@ -32,16 +32,16 @@ ch_multiqc_custom_methods_description = params.multiqc_methods_description ? fil ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ */ -include { CROPTIFF } from '../modules/local/croptiff' -include { CROPHDF5 } from '../modules/local/crophdf5' -include { CREATE_STACK } from '../modules/local/createstack' -include { CLAHE } from '../modules/local/clahe' -include { MASKFILTER } from '../modules/local/maskfilter' -include { MOLKARTQC } from '../modules/local/molkartqc' -include { MOLKARTQCPNG } from '../modules/local/molkartqcpng' -include { SPOT2CELL } from '../modules/local/spot2cell' -include { TIFFH5CONVERT } from '../modules/local/tiffh5convert' +include { CROPTIFF } from '../modules/local/croptiff' +include { CROPHDF5 } from '../modules/local/crophdf5' include { CREATE_ANNDATA } from '../modules/local/createanndata' +include { CREATE_STACK } from '../modules/local/createstack' +include { CLAHE } from '../modules/local/clahe' +include { MASKFILTER } from '../modules/local/maskfilter' +include { MOLKARTQC } from '../modules/local/molkartqc' +include { MOLKARTQCPNG } from '../modules/local/molkartqcpng' +include { SPOT2CELL } from '../modules/local/spot2cell' +include { TIFFH5CONVERT } from '../modules/local/tiffh5convert' // // SUBWORKFLOW: Consisting of a mix of local and nf-core/modules @@ -284,8 +284,7 @@ workflow MOLKART { SPOT2CELL( dedup_spots.map(it -> tuple(it[0],it[1])), - dedup_spots.map(it -> tuple(it[0],it[2])), - dedup_spots.map(it -> it[0].segmentation) + dedup_spots.map(it -> tuple(it[0],it[2])) ) ch_versions = ch_versions.mix(SPOT2CELL.out.versions) From d245f99d9e73d44106c1947cec5f7e0cafcc6cdc Mon Sep 17 00:00:00 2001 From: Florian Wuennemann Date: Fri, 5 Jan 2024 15:24:44 +0000 Subject: [PATCH 124/149] Updated molkart-local container version. --- modules/local/clahe.nf | 2 +- modules/local/createanndata.nf | 2 +- modules/local/createstack.nf | 2 +- modules/local/crophdf5.nf | 2 +- modules/local/croptiff.nf | 2 +- modules/local/maskfilter.nf | 2 +- modules/local/molkartqc.nf | 2 +- modules/local/molkartqcpng.nf | 2 +- modules/local/spot2cell.nf | 2 +- modules/local/tiffh5convert.nf | 2 +- 10 files changed, 10 insertions(+), 10 deletions(-) diff --git a/modules/local/clahe.nf b/modules/local/clahe.nf index 5585eba..b4caf08 100644 --- a/modules/local/clahe.nf +++ b/modules/local/clahe.nf @@ -2,7 +2,7 @@ process CLAHE{ tag "$meta.id" label 'process_medium' - container 'ghcr.io/schapirolabor/molkart-local:v0.0.3' + container 'ghcr.io/schapirolabor/molkart-local:v0.0.4' input: tuple val(meta), path(image) diff --git a/modules/local/createanndata.nf b/modules/local/createanndata.nf index 244df8d..a11e3d7 100644 --- a/modules/local/createanndata.nf +++ b/modules/local/createanndata.nf @@ -2,7 +2,7 @@ process CREATE_ANNDATA { tag "$meta.id" label 'process_low' - container 'ghcr.io/schapirolabor/molkart-local:v0.0.3' + container 'ghcr.io/schapirolabor/molkart-local:v0.0.4' input: tuple val(meta), path(spot2cell) diff --git a/modules/local/createstack.nf b/modules/local/createstack.nf index 08e9031..993c5a4 100644 --- a/modules/local/createstack.nf +++ b/modules/local/createstack.nf @@ -2,7 +2,7 @@ process CREATE_STACK { tag "$meta.id" label 'process_low' - container 'ghcr.io/schapirolabor/molkart-local:v0.0.3' + container 'ghcr.io/schapirolabor/molkart-local:v0.0.4' input: tuple val(meta), path(image) diff --git a/modules/local/crophdf5.nf b/modules/local/crophdf5.nf index c763878..6d5229a 100644 --- a/modules/local/crophdf5.nf +++ b/modules/local/crophdf5.nf @@ -2,7 +2,7 @@ process CROPHDF5 { tag "$meta.id" label 'process_single' - container 'ghcr.io/schapirolabor/molkart-local:v0.0.3' + container 'ghcr.io/schapirolabor/molkart-local:v0.0.4' input: tuple val(meta), path(image_stack), val(num_channels) diff --git a/modules/local/croptiff.nf b/modules/local/croptiff.nf index 3ac77f4..7e3ca43 100644 --- a/modules/local/croptiff.nf +++ b/modules/local/croptiff.nf @@ -2,7 +2,7 @@ process CROPTIFF { tag "$meta.id" label 'process_single' - container 'ghcr.io/schapirolabor/molkart-local:v0.0.3' + container 'ghcr.io/schapirolabor/molkart-local:v0.0.4' input: tuple val(meta), path(image_stack) diff --git a/modules/local/maskfilter.nf b/modules/local/maskfilter.nf index 3a4f84d..97e73c3 100644 --- a/modules/local/maskfilter.nf +++ b/modules/local/maskfilter.nf @@ -2,7 +2,7 @@ process MASKFILTER { tag "$meta.id" label 'process_medium' - container 'ghcr.io/schapirolabor/molkart-local:v0.0.3' + container 'ghcr.io/schapirolabor/molkart-local:v0.0.4' input: tuple val(meta), path(mask) diff --git a/modules/local/molkartqc.nf b/modules/local/molkartqc.nf index a0af1ec..57fe8d4 100644 --- a/modules/local/molkartqc.nf +++ b/modules/local/molkartqc.nf @@ -2,7 +2,7 @@ process MOLKARTQC{ tag "$meta.id" label 'process_single' - container 'ghcr.io/schapirolabor/molkart-local:v0.0.3' + container 'ghcr.io/schapirolabor/molkart-local:v0.0.4' input: tuple val(meta), path(spot_table), path(cellxgene_table), val(segmethod), path(filterqc) diff --git a/modules/local/molkartqcpng.nf b/modules/local/molkartqcpng.nf index e920ea8..f5a44df 100644 --- a/modules/local/molkartqcpng.nf +++ b/modules/local/molkartqcpng.nf @@ -1,7 +1,7 @@ process MOLKARTQCPNG { label 'process_single' - container 'ghcr.io/schapirolabor/molkart-local:v0.0.3' + container 'ghcr.io/schapirolabor/molkart-local:v0.0.4' input: path(png) diff --git a/modules/local/spot2cell.nf b/modules/local/spot2cell.nf index a8259cf..4eab5ba 100644 --- a/modules/local/spot2cell.nf +++ b/modules/local/spot2cell.nf @@ -3,7 +3,7 @@ process SPOT2CELL{ tag "$meta.id" label 'process_single' - container 'ghcr.io/schapirolabor/molkart-local:v0.0.3' + container 'ghcr.io/schapirolabor/molkart-local:v0.0.4' input: tuple val(meta) , path(spot_table) diff --git a/modules/local/tiffh5convert.nf b/modules/local/tiffh5convert.nf index a283b33..f3d38ab 100644 --- a/modules/local/tiffh5convert.nf +++ b/modules/local/tiffh5convert.nf @@ -2,7 +2,7 @@ process TIFFH5CONVERT { tag "$meta.id" label 'process_single' - container "ghcr.io/schapirolabor/molkart-local:v0.0.3" + container "ghcr.io/schapirolabor/molkart-local:v0.0.4" input: tuple val(meta), path(image), val(num_channels) From f5abf0d2ce71bd9d6a4319c6f564759ec6c6a278 Mon Sep 17 00:00:00 2001 From: Florian Wuennemann Date: Sat, 6 Jan 2024 16:42:18 +0000 Subject: [PATCH 125/149] Added changes to changelog. --- CHANGELOG.md | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/CHANGELOG.md b/CHANGELOG.md index 983422e..9743e58 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -3,6 +3,12 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/) and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html). +## v1.0.1dev - [2024.01.06] + +### `Fixed` + +- Updated version numbers for all local modules to molkart-local container v0.0.4 due to a bug in version v0.0.3 that prevented the modules to be properly run with singularity. + ## v1.0.1dev - [2024.01.04] ### `Added` From 6ab6e27504cfc5e83315f3f2138fd8de84ee9952 Mon Sep 17 00:00:00 2001 From: Florian Wuennemann Date: Mon, 8 Jan 2024 13:03:42 +0000 Subject: [PATCH 126/149] Fixed maskfilter bug. --- CHANGELOG.md | 7 +++++++ assets/multiqc_config.yml | 6 +++--- bin/maskfilter.py | 8 ++++---- 3 files changed, 14 insertions(+), 7 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 9743e58..f432161 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -3,6 +3,13 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/) and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html). +## v1.0.1dev - [2024.01.08 + +### `Fixed` + +- Fixed a bug in maskfilter for calculating the number of filtered objects. +- Changed values in multiqc table for filtered object + ## v1.0.1dev - [2024.01.06] ### `Fixed` diff --git a/assets/multiqc_config.yml b/assets/multiqc_config.yml index f88672e..820f824 100644 --- a/assets/multiqc_config.yml +++ b/assets/multiqc_config.yml @@ -51,13 +51,13 @@ custom_data: title: Total number of duplicated spots in the area description: "Total number of duplicated spots" labels_total: - title: Total number of segmentation labels before filtering + title: Total number of cells before filtering description: "Total number of segmented labels" labels_below_thresh: - title: Number of removed small labels + title: Number of removed small cells description: "Total number of labels below min_area" labels_above_thresh: - title: Number of removed large labels + title: Number of removed large cells description: "Total number of labels above max_area" sp: segmentation_stats: diff --git a/bin/maskfilter.py b/bin/maskfilter.py index de4f87b..c47d7b3 100755 --- a/bin/maskfilter.py +++ b/bin/maskfilter.py @@ -66,19 +66,19 @@ def filter_areas(mask, min_area=None, max_area=None): large_valid_labels = np.array([label for label, area in label_area_map.items() if area <= max_area]) valid_labels = np.intersect1d(small_valid_labels, large_valid_labels) retained_masks = np.isin(labeled_mask, valid_labels) * labeled_mask - small_labels = len(labeled_mask) - len(small_valid_labels) - large_labels = len(labeled_mask) - len(large_valid_labels) + small_labels = num_cells - len(small_valid_labels) + large_labels = num_cells - len(large_valid_labels) relabeled_mask = label(retained_masks, background=0) elif min_area: valid_labels = np.array([label for label, area in label_area_map.items() if area >= min_area]) retained_masks = np.isin(labeled_mask, valid_labels) * labeled_mask large_labels = 0 - small_labels = len(labeled_mask) - len(valid_labels) + small_labels = num_cells - len(valid_labels) relabeled_mask = label(retained_masks, background=0) elif max_area: valid_labels = np.array([label for label, area in label_area_map.items() if area <= max_area]) retained_masks = np.isin(labeled_mask, valid_labels) * labeled_mask - large_labels = len(labeled_mask) - len(valid_labels) + large_labels = num_cells - len(valid_labels) small_labels = 0 relabeled_mask = label(retained_masks, background=0) else: From c0a4b4322964c6ab2a66b37ddf3cfe03ee6a18b2 Mon Sep 17 00:00:00 2001 From: Florian Wuennemann Date: Mon, 8 Jan 2024 13:11:52 +0000 Subject: [PATCH 127/149] Fixed Changelog typo. --- CHANGELOG.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index f432161..bfcbc71 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -8,7 +8,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 ### `Fixed` - Fixed a bug in maskfilter for calculating the number of filtered objects. -- Changed values in multiqc table for filtered object +- Changed naming of columns in multiqc table for filtered cells ## v1.0.1dev - [2024.01.06] From a535b3048848e120c333685a1af6baf1d5c1f503 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Tue, 16 Jan 2024 10:13:57 +0000 Subject: [PATCH 128/149] updated modules --- .../dumpsoftwareversions/environment.yml | 2 +- .../custom/dumpsoftwareversions/main.nf | 4 +- .../dumpsoftwareversions/tests/main.nf.test | 7 ++- .../tests/main.nf.test.snap | 50 +++++++++++-------- modules/nf-core/mindagap/mindagap/main.nf | 23 ++++----- modules/nf-core/mindagap/mindagap/meta.yml | 12 ++--- .../mindagap/mindagap/tests/main.nf.test | 36 +++++++++++++ .../mindagap/mindagap/tests/main.nf.test.snap | 23 +++++++++ .../mindagap/mindagap/tests/nextflow.config | 6 +++ .../nf-core/mindagap/mindagap/tests/tags.yml | 2 + modules/nf-core/multiqc/environment.yml | 2 +- modules/nf-core/multiqc/main.nf | 6 +-- modules/nf-core/multiqc/meta.yml | 1 - modules/nf-core/multiqc/tests/main.nf.test | 48 ++++++++++++------ .../nf-core/multiqc/tests/main.nf.test.snap | 21 ++++++++ 15 files changed, 175 insertions(+), 68 deletions(-) create mode 100644 modules/nf-core/mindagap/mindagap/tests/main.nf.test create mode 100644 modules/nf-core/mindagap/mindagap/tests/main.nf.test.snap create mode 100644 modules/nf-core/mindagap/mindagap/tests/nextflow.config create mode 100644 modules/nf-core/mindagap/mindagap/tests/tags.yml create mode 100644 modules/nf-core/multiqc/tests/main.nf.test.snap diff --git a/modules/nf-core/custom/dumpsoftwareversions/environment.yml b/modules/nf-core/custom/dumpsoftwareversions/environment.yml index f0c63f6..9b3272b 100644 --- a/modules/nf-core/custom/dumpsoftwareversions/environment.yml +++ b/modules/nf-core/custom/dumpsoftwareversions/environment.yml @@ -4,4 +4,4 @@ channels: - bioconda - defaults dependencies: - - bioconda::multiqc=1.17 + - bioconda::multiqc=1.19 diff --git a/modules/nf-core/custom/dumpsoftwareversions/main.nf b/modules/nf-core/custom/dumpsoftwareversions/main.nf index 7685b33..f218761 100644 --- a/modules/nf-core/custom/dumpsoftwareversions/main.nf +++ b/modules/nf-core/custom/dumpsoftwareversions/main.nf @@ -4,8 +4,8 @@ process CUSTOM_DUMPSOFTWAREVERSIONS { // Requires `pyyaml` which does not have a dedicated container but is in the MultiQC container conda "${moduleDir}/environment.yml" container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? - 'https://depot.galaxyproject.org/singularity/multiqc:1.17--pyhdfd78af_0' : - 'biocontainers/multiqc:1.17--pyhdfd78af_0' }" + 'https://depot.galaxyproject.org/singularity/multiqc:1.19--pyhdfd78af_0' : + 'biocontainers/multiqc:1.19--pyhdfd78af_0' }" input: path versions diff --git a/modules/nf-core/custom/dumpsoftwareversions/tests/main.nf.test b/modules/nf-core/custom/dumpsoftwareversions/tests/main.nf.test index eec1db1..b1e1630 100644 --- a/modules/nf-core/custom/dumpsoftwareversions/tests/main.nf.test +++ b/modules/nf-core/custom/dumpsoftwareversions/tests/main.nf.test @@ -31,7 +31,12 @@ nextflow_process { then { assertAll( { assert process.success }, - { assert snapshot(process.out).match() } + { assert snapshot( + process.out.versions, + file(process.out.mqc_yml[0]).readLines()[0..10], + file(process.out.yml[0]).readLines()[0..7] + ).match() + } ) } } diff --git a/modules/nf-core/custom/dumpsoftwareversions/tests/main.nf.test.snap b/modules/nf-core/custom/dumpsoftwareversions/tests/main.nf.test.snap index 4274ed5..5f59a93 100644 --- a/modules/nf-core/custom/dumpsoftwareversions/tests/main.nf.test.snap +++ b/modules/nf-core/custom/dumpsoftwareversions/tests/main.nf.test.snap @@ -1,27 +1,33 @@ { "Should run without failures": { "content": [ - { - "0": [ - "software_versions.yml:md5,1c851188476409cda5752ce971b20b58" - ], - "1": [ - "software_versions_mqc.yml:md5,2570f4ba271ad08357b0d3d32a9cf84d" - ], - "2": [ - "versions.yml:md5,3843ac526e762117eedf8825b40683df" - ], - "mqc_yml": [ - "software_versions_mqc.yml:md5,2570f4ba271ad08357b0d3d32a9cf84d" - ], - "versions": [ - "versions.yml:md5,3843ac526e762117eedf8825b40683df" - ], - "yml": [ - "software_versions.yml:md5,1c851188476409cda5752ce971b20b58" - ] - } + [ + "versions.yml:md5,76d454d92244589d32455833f7c1ba6d" + ], + [ + "data: \"\\n\\n \\n \\n \\n \\n \\n \\n \\n\\", + " \\n\\n\\n \\n \\n\\", + " \\ \\n\\n\\n\\n \\n \\", + " \\ \\n \\n\\n\\n\\n\\", + " \\n\\n \\n \\n\\", + " \\ \\n\\n\\n\\n\\n\\n \\n\\", + " \\ \\n \\n\\n\\n\\n\\", + " \\n\\n \\n \\n\\" + ], + [ + "CUSTOM_DUMPSOFTWAREVERSIONS:", + " python: 3.11.7", + " yaml: 5.4.1", + "TOOL1:", + " tool1: 0.11.9", + "TOOL2:", + " tool2: '1.9'", + "Workflow:" + ] ], - "timestamp": "2023-11-03T14:43:22.157011" + "timestamp": "2024-01-09T23:01:18.710682" } -} +} \ No newline at end of file diff --git a/modules/nf-core/mindagap/mindagap/main.nf b/modules/nf-core/mindagap/mindagap/main.nf index 5d59a66..3f06996 100644 --- a/modules/nf-core/mindagap/mindagap/main.nf +++ b/modules/nf-core/mindagap/mindagap/main.nf @@ -4,31 +4,26 @@ process MINDAGAP_MINDAGAP { conda "${moduleDir}/environment.yml" container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? - 'https://depot.galaxyproject.org/singularity/mindagap:0.0.2--pyhdfd78af_0' : - 'biocontainers/mindagap:0.0.2--pyhdfd78af_0' }" + 'https://depot.galaxyproject.org/singularity/mindagap:0.0.2--pyhdfd78af_1' : + 'biocontainers/mindagap:0.0.2--pyhdfd78af_1' }" input: - tuple val(meta), path(tiff) - val(boxsize) - val(loopnum) + tuple val(meta), path(panorama) output: - tuple val(meta), path("*gridfilled.tiff"), emit: tiff - path "versions.yml" , emit: versions + tuple val(meta), path("*.{tif,tiff}"), emit: tiff + path "versions.yml" , emit: versions when: task.ext.when == null || task.ext.when script: - def args = task.ext.args ?: '' - def args2 = task.ext.args2 ?: '' + def args = task.ext.args ?: '' def prefix = task.ext.prefix ?: "${meta.id}" """ mindagap.py \\ - $args \\ - $tiff \\ - $boxsize \\ - $loopnum + $panorama \\ + $args cat <<-END_VERSIONS > versions.yml "${task.process}": @@ -39,7 +34,7 @@ process MINDAGAP_MINDAGAP { stub: def prefix = task.ext.prefix ?: "${meta.id}" """ - touch ${prefix}.gridfilled.tiff + touch ${panorama.baseName}_gridfilled.tiff cat <<-END_VERSIONS > versions.yml "${task.process}": diff --git a/modules/nf-core/mindagap/mindagap/meta.yml b/modules/nf-core/mindagap/mindagap/meta.yml index 5bd562a..efd0000 100644 --- a/modules/nf-core/mindagap/mindagap/meta.yml +++ b/modules/nf-core/mindagap/mindagap/meta.yml @@ -10,23 +10,17 @@ tools: homepage: "https://github.com/ViriatoII/MindaGap" documentation: "https://github.com/ViriatoII/MindaGap/blob/main/README.md" tool_dev_url: "https://github.com/ViriatoII/MindaGap" - licence: "BSD-3-Clause license" + licence: ["BSD-3-Clause license"] input: - meta: type: map description: | Groovy Map containing sample information e.g. [ id:'test', single_end:false ] - - tiff: + - panorama: type: file description: A tiff file containing gridlines as produced by Molecular Cartography imaging. - pattern: "*.{tiff}" - - boxsize: - type: integer - description: A larger number allows to overcome large gaps, but makes looses fine details in new filled grid. - - loopnum: - type: integer - description: The number of times gaussian blur is run consecutively on the gridlines. A smaller number is faster, but the result is less good. + pattern: "*.{tif,tiff}" output: - meta: type: map diff --git a/modules/nf-core/mindagap/mindagap/tests/main.nf.test b/modules/nf-core/mindagap/mindagap/tests/main.nf.test new file mode 100644 index 0000000..dbad491 --- /dev/null +++ b/modules/nf-core/mindagap/mindagap/tests/main.nf.test @@ -0,0 +1,36 @@ +nextflow_process { + + name "Test Process MINDAGAP_MINDAGAP" + script "../main.nf" + config "./nextflow.config" + process "MINDAGAP_MINDAGAP" + + tag "modules" + tag "modules_nfcore" + tag "mindagap" + tag "mindagap/mindagap" + + test("mindgap - tiff") { + + when { + process { + """ + input[0] = [ + [ id:'test' ], + file(params.test_data['imaging']['tiff']['mouse_heart_wga'], checkIfExists: true) + ] + """ + } + } + + then { + assertAll( + { assert process.success }, + { assert snapshot(process.out.tiff).match("tiff") }, + { assert snapshot(process.out.versions).match("versions") } + ) + } + + } + +} diff --git a/modules/nf-core/mindagap/mindagap/tests/main.nf.test.snap b/modules/nf-core/mindagap/mindagap/tests/main.nf.test.snap new file mode 100644 index 0000000..f799a14 --- /dev/null +++ b/modules/nf-core/mindagap/mindagap/tests/main.nf.test.snap @@ -0,0 +1,23 @@ +{ + "tiff": { + "content": [ + [ + [ + { + "id": "test" + }, + "mindagap.mouse_heart.wga_gridfilled.tiff:md5,310cf0017baa54af32176b43a5b0adfd" + ] + ] + ], + "timestamp": "2023-12-15T11:01:20.825556802" + }, + "versions": { + "content": [ + [ + "versions.yml:md5,937acaba2cb90efc2705b71839e6cefc" + ] + ], + "timestamp": "2023-12-15T11:01:20.840211732" + } +} \ No newline at end of file diff --git a/modules/nf-core/mindagap/mindagap/tests/nextflow.config b/modules/nf-core/mindagap/mindagap/tests/nextflow.config new file mode 100644 index 0000000..0991d4f --- /dev/null +++ b/modules/nf-core/mindagap/mindagap/tests/nextflow.config @@ -0,0 +1,6 @@ +process { + + withName: "MINDAGAP_MINDAGAP" { + ext.args = "3 40 --Xtilesize 2144" + } +} diff --git a/modules/nf-core/mindagap/mindagap/tests/tags.yml b/modules/nf-core/mindagap/mindagap/tests/tags.yml new file mode 100644 index 0000000..6f1837d --- /dev/null +++ b/modules/nf-core/mindagap/mindagap/tests/tags.yml @@ -0,0 +1,2 @@ +mindagap/mindagap: + - "modules/nf-core/mindagap/mindagap/**" diff --git a/modules/nf-core/multiqc/environment.yml b/modules/nf-core/multiqc/environment.yml index bc0bdb5..7625b75 100644 --- a/modules/nf-core/multiqc/environment.yml +++ b/modules/nf-core/multiqc/environment.yml @@ -4,4 +4,4 @@ channels: - bioconda - defaults dependencies: - - bioconda::multiqc=1.18 + - bioconda::multiqc=1.19 diff --git a/modules/nf-core/multiqc/main.nf b/modules/nf-core/multiqc/main.nf index 00cc48d..1b9f7c4 100644 --- a/modules/nf-core/multiqc/main.nf +++ b/modules/nf-core/multiqc/main.nf @@ -3,8 +3,8 @@ process MULTIQC { conda "${moduleDir}/environment.yml" container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? - 'https://depot.galaxyproject.org/singularity/multiqc:1.18--pyhdfd78af_0' : - 'biocontainers/multiqc:1.18--pyhdfd78af_0' }" + 'https://depot.galaxyproject.org/singularity/multiqc:1.19--pyhdfd78af_0' : + 'biocontainers/multiqc:1.19--pyhdfd78af_0' }" input: path multiqc_files, stageAs: "?/*" @@ -43,7 +43,7 @@ process MULTIQC { stub: """ - touch multiqc_data + mkdir multiqc_data touch multiqc_plots touch multiqc_report.html diff --git a/modules/nf-core/multiqc/meta.yml b/modules/nf-core/multiqc/meta.yml index f1aa660..45a9bc3 100644 --- a/modules/nf-core/multiqc/meta.yml +++ b/modules/nf-core/multiqc/meta.yml @@ -1,4 +1,3 @@ -# yaml-language-server: $schema=https://raw.githubusercontent.com/nf-core/modules/master/modules/meta-schema.json name: multiqc description: Aggregate results from bioinformatics analyses across many samples into a single report keywords: diff --git a/modules/nf-core/multiqc/tests/main.nf.test b/modules/nf-core/multiqc/tests/main.nf.test index c2dad21..d0438ed 100644 --- a/modules/nf-core/multiqc/tests/main.nf.test +++ b/modules/nf-core/multiqc/tests/main.nf.test @@ -7,12 +7,9 @@ nextflow_process { tag "modules_nfcore" tag "multiqc" - test("MULTIQC: FASTQC") { + test("sarscov2 single-end [fastqc]") { when { - params { - outdir = "$outputDir" - } process { """ input[0] = Channel.of([file(params.test_data['sarscov2']['illumina']['test_1_fastq_gz_fastqc_zip'], checkIfExists: true)]) @@ -26,20 +23,17 @@ nextflow_process { then { assertAll( { assert process.success }, - { assert path(process.out.report.get(0)).exists() }, - { assert path(process.out.data.get(0)).exists() }, - { assert path(process.out.versions.get(0)).getText().contains("multiqc") } + { assert process.out.report[0] ==~ ".*/multiqc_report.html" }, + { assert process.out.data[0] ==~ ".*/multiqc_data" }, + { assert snapshot(process.out.versions).match("versions") } ) } } - test("MULTIQC: FASTQC and a config file") { + test("sarscov2 single-end [fastqc] [config]") { when { - params { - outdir = "$outputDir" - } process { """ input[0] = Channel.of([file(params.test_data['sarscov2']['illumina']['test_1_fastq_gz_fastqc_zip'], checkIfExists: true)]) @@ -53,9 +47,35 @@ nextflow_process { then { assertAll( { assert process.success }, - { assert path(process.out.report.get(0)).exists() }, - { assert path(process.out.data.get(0)).exists() }, - { assert path(process.out.versions.get(0)).getText().contains("multiqc") } + { assert process.out.report[0] ==~ ".*/multiqc_report.html" }, + { assert process.out.data[0] ==~ ".*/multiqc_data" }, + { assert snapshot(process.out.versions).match("versions") } + ) + } + } + + test("sarscov2 single-end [fastqc] - stub") { + + options "-stub" + + when { + process { + """ + input[0] = Channel.of([file(params.test_data['sarscov2']['illumina']['test_1_fastq_gz_fastqc_zip'], checkIfExists: true)]) + input[1] = [] + input[2] = [] + input[3] = [] + """ + } + } + + then { + assertAll( + { assert process.success }, + { assert snapshot(process.out.report.collect { file(it).getName() } + + process.out.data.collect { file(it).getName() } + + process.out.plots.collect { file(it).getName() } + + process.out.versions ).match() } ) } diff --git a/modules/nf-core/multiqc/tests/main.nf.test.snap b/modules/nf-core/multiqc/tests/main.nf.test.snap new file mode 100644 index 0000000..d37e730 --- /dev/null +++ b/modules/nf-core/multiqc/tests/main.nf.test.snap @@ -0,0 +1,21 @@ +{ + "versions": { + "content": [ + [ + "versions.yml:md5,14e9a2661241abd828f4f06a7b5c222d" + ] + ], + "timestamp": "2024-01-09T23:02:49.911994" + }, + "sarscov2 single-end [fastqc] - stub": { + "content": [ + [ + "multiqc_report.html", + "multiqc_data", + "multiqc_plots", + "versions.yml:md5,14e9a2661241abd828f4f06a7b5c222d" + ] + ], + "timestamp": "2024-01-09T23:03:14.524346" + } +} \ No newline at end of file From 0660f031a9b52a966ec37a9bbdde3a9215fbaf62 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Tue, 16 Jan 2024 10:15:01 +0000 Subject: [PATCH 129/149] Adapted pipeline to new mindagap version --- conf/modules.config | 2 ++ conf/test.config | 4 +++- conf/test_full.config | 2 ++ modules.json | 6 +++--- nextflow.config | 3 +++ nextflow_schema.json | 20 +++++++++++++++++++- tests/main.nf.test | 6 ++++++ workflows/molkart.nf | 2 +- 8 files changed, 39 insertions(+), 6 deletions(-) diff --git a/conf/modules.config b/conf/modules.config index 85f3174..93c1b0e 100644 --- a/conf/modules.config +++ b/conf/modules.config @@ -79,6 +79,8 @@ process { withName: "MINDAGAP_MINDAGAP" { ext.args = [ "", + params.mindagap_boxsize ? "${params.mindagap_boxsize}" : "", + params.mindagap_loopnum ? "${params.mindagap_loopnum}" : "", params.mindagap_tilesize ? "-xt ${params.mindagap_tilesize}" : "" ].join(" ").trim() publishDir = [ diff --git a/conf/test.config b/conf/test.config index a01d69f..8b3f0fb 100644 --- a/conf/test.config +++ b/conf/test.config @@ -22,6 +22,8 @@ params { // Input data input = 'https://raw.githubusercontent.com/nf-core/test-datasets/molkart/test_data/samplesheets/samplesheet_membrane.csv' mindagap_tilesize = 90 + mindagap_boxsize = 7 + mindagap_loopnum = 100 clahe_pyramid_tile = 368 - segmentation_method = "cellpose,mesmer" + segmentation_method = ["cellpose", "mesmer"] } diff --git a/conf/test_full.config b/conf/test_full.config index a911dc3..586de22 100644 --- a/conf/test_full.config +++ b/conf/test_full.config @@ -17,5 +17,7 @@ params { input = 'https://raw.githubusercontent.com/nf-core/test-datasets/molkart/test_data/samplesheets/samplesheet_full_test.csv' segmentation_method = "mesmer,cellpose" + mindagap_boxsize = 7 + mindagap_loopnum = 100 cellpose_pretrained_model = "nuclei" } diff --git a/modules.json b/modules.json index 62db811..4b26013 100644 --- a/modules.json +++ b/modules.json @@ -12,7 +12,7 @@ }, "custom/dumpsoftwareversions": { "branch": "master", - "git_sha": "bba7e362e4afead70653f84d8700588ea28d0f9e", + "git_sha": "8ec825f465b9c17f9d83000022995b4f7de6fe93", "installed_by": ["modules"] }, "deepcell/mesmer": { @@ -37,12 +37,12 @@ }, "mindagap/mindagap": { "branch": "master", - "git_sha": "3f5420aa22e00bd030a2556dfdffc9e164ec0ec5", + "git_sha": "97dbec551f491ee562721008cdecd1e7a9a56b14", "installed_by": ["modules"] }, "multiqc": { "branch": "master", - "git_sha": "4ab13872435962dadc239979554d13709e20bf29", + "git_sha": "8ec825f465b9c17f9d83000022995b4f7de6fe93", "installed_by": ["modules"] } } diff --git a/nextflow.config b/nextflow.config index 2d57adc..7afc0d3 100644 --- a/nextflow.config +++ b/nextflow.config @@ -31,6 +31,9 @@ params { // Preprocessing command line flags mindagap_tilesize = 2144 + mindagap_boxsize = 3 + mindagap_loopnum = 40 + mindagap_edges = false skip_clahe = false clahe_cliplimit = 0.01 clahe_nbins = 256 diff --git a/nextflow_schema.json b/nextflow_schema.json index 23b8cdc..0d94107 100644 --- a/nextflow_schema.json +++ b/nextflow_schema.json @@ -13,7 +13,7 @@ "properties": { "segmentation_method": { "type": "string", - "description": "List of segmentation tools to apply to the image", + "description": "List of segmentation tools to apply to the image written as a comma separated string: mesmer,cellpose,ilastik would run all three options.", "default": "mesmer", "fa_icon": "fas fa-border-all" }, @@ -108,6 +108,18 @@ "default": "", "fa_icon": "fas fa-adjust", "properties": { + "mindagap_boxsize": { + "type": "integer", + "default": 3, + "description": "Box size used by Mindagap to overcome gaps, a larger number allows to overcome large gaps, but results in less fine details in the filled grid.", + "fa_icon": "fab fa-dropbox" + }, + "mindagap_loopnum": { + "type": "integer", + "default": 40, + "description": "Loop number performed by Mindagap. Lower values are faster, but the result is less good.", + "fa_icon": "fas fa-circle-notch" + }, "clahe_cliplimit": { "type": "number", "default": 0.01, @@ -144,6 +156,12 @@ "fa_icon": "fas fa-th", "hidden": true }, + "mindagap_edges": { + "type": "boolean", + "description": "Should Mindagap blur area around grid for smoother transitions between tiles with different exposures.", + "fa_icon": "fas fa-th-large", + "hidden": true + }, "clahe_pyramid_tile": { "type": "integer", "description": "Tile size used for pyramid generation (must be divisible by 16).", diff --git a/tests/main.nf.test b/tests/main.nf.test index 0080994..48d5546 100644 --- a/tests/main.nf.test +++ b/tests/main.nf.test @@ -14,6 +14,8 @@ nextflow_pipeline { outdir = "$outputDir" skip_clahe = true mindagap_tilesize = 90 + mindagap_boxsize = 7 + mindagap_loopnum = 100 segmentation_method = "cellpose,mesmer" } } @@ -45,6 +47,8 @@ nextflow_pipeline { input = 'https://raw.githubusercontent.com/nf-core/test-datasets/molkart/test_data/samplesheets/samplesheet_membrane.csv' outdir = "$outputDir" mindagap_tilesize = 90 + mindagap_boxsize = 7 + mindagap_loopnum = 100 clahe_pyramid_tile = 368 segmentation_method = "cellpose,mesmer" } @@ -81,6 +85,8 @@ nextflow_pipeline { input = 'https://raw.githubusercontent.com/nf-core/test-datasets/molkart/test_data/samplesheets/samplesheet_nuclear.csv' outdir = "$outputDir" mindagap_tilesize = 90 + mindagap_boxsize = 7 + mindagap_loopnum = 100 clahe_pyramid_tile = 368 create_training_subset = true crop_amount = 2 diff --git a/workflows/molkart.nf b/workflows/molkart.nf index 2e6a86e..d3892fe 100644 --- a/workflows/molkart.nf +++ b/workflows/molkart.nf @@ -104,7 +104,7 @@ workflow MOLKART { // MODULE: Run Mindagap_mindagap // mindagap_in = membrane_tuple.mix(image_tuple) // mindagap input contains both membrane and nuclear images - MINDAGAP_MINDAGAP(mindagap_in, 7, 100) // runs MINDAGAP_MINDAGAP, hardcoded boxsize and loopnumber parameters; TODO: make mindagap_mindagap more compliant with nf-core guidelines + MINDAGAP_MINDAGAP(mindagap_in) // runs MINDAGAP_MINDAGAP, hardcoded boxsize and loopnumber parameters; TODO: make mindagap_mindagap more compliant with nf-core guidelines ch_versions = ch_versions.mix(MINDAGAP_MINDAGAP.out.versions) // From 2de50b493c82f9bc2a18cf1ca021644bc45f8cbe Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Tue, 16 Jan 2024 10:29:15 +0000 Subject: [PATCH 130/149] removed mindagap todo --- workflows/molkart.nf | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/workflows/molkart.nf b/workflows/molkart.nf index d3892fe..99b8fb8 100644 --- a/workflows/molkart.nf +++ b/workflows/molkart.nf @@ -104,12 +104,11 @@ workflow MOLKART { // MODULE: Run Mindagap_mindagap // mindagap_in = membrane_tuple.mix(image_tuple) // mindagap input contains both membrane and nuclear images - MINDAGAP_MINDAGAP(mindagap_in) // runs MINDAGAP_MINDAGAP, hardcoded boxsize and loopnumber parameters; TODO: make mindagap_mindagap more compliant with nf-core guidelines + MINDAGAP_MINDAGAP(mindagap_in) ch_versions = ch_versions.mix(MINDAGAP_MINDAGAP.out.versions) // - //MODULE: Apply Contrast-limited adaptive histogram equalization (CLAHE) - // + // MODULE: Apply Contrast-limited adaptive histogram equalization (CLAHE) // CLAHE is either applied to all images, or none. // CLAHE(MINDAGAP_MINDAGAP.out.tiff) @@ -147,7 +146,6 @@ workflow MOLKART { CREATE_STACK(create_stack_in) ch_versions = ch_versions.mix(CREATE_STACK.out.versions) stack_mix = no_stack.mix(CREATE_STACK.out.stack) - //stack_mix = create_stack_in ? CREATE_STACK.out.stack.mix(no_stack) : no_stack if ( params.create_training_subset ) { // Create subsets of the image for training an ilastik model From a6fcde622bcb5c61a481d5cee1bcf67679aaf367 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Tue, 16 Jan 2024 12:43:42 +0000 Subject: [PATCH 131/149] updated changelog --- .github/workflows/awsfulltest.yml | 3 --- CHANGELOG.md | 9 ++++++++- 2 files changed, 8 insertions(+), 4 deletions(-) diff --git a/.github/workflows/awsfulltest.yml b/.github/workflows/awsfulltest.yml index 1ba5bcf..176bdb5 100644 --- a/.github/workflows/awsfulltest.yml +++ b/.github/workflows/awsfulltest.yml @@ -15,9 +15,6 @@ jobs: steps: - name: Launch workflow via tower uses: seqeralabs/action-tower-launch@v2 - # TODO nf-core: You can customise AWS full pipeline tests as required - # Add full size test data (but still relatively small datasets for few samples) - # on the `test_full.config` test runs with only one set of parameters with: workspace_id: ${{ secrets.TOWER_WORKSPACE_ID }} access_token: ${{ secrets.TOWER_ACCESS_TOKEN }} diff --git a/CHANGELOG.md b/CHANGELOG.md index bfcbc71..78205fb 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -3,7 +3,14 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/) and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html). -## v1.0.1dev - [2024.01.08 +## v1.0.1dev - [2024.01.16] + +### `Added` + +- mindagap_boxsize, mindagap_loopnum, mindagap_edges parameters +- updated mindagap version and adapted molkart.nf and modules.config to match updated mindagap module version + +## v1.0.1dev - [2024.01.08] ### `Fixed` From 8307d1fe1fde5fd2a2b0081a3d1edf0096db65e4 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Tue, 16 Jan 2024 13:01:20 +0000 Subject: [PATCH 132/149] fixed test.config --- conf/test.config | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/conf/test.config b/conf/test.config index 8b3f0fb..f30779e 100644 --- a/conf/test.config +++ b/conf/test.config @@ -25,5 +25,5 @@ params { mindagap_boxsize = 7 mindagap_loopnum = 100 clahe_pyramid_tile = 368 - segmentation_method = ["cellpose", "mesmer"] + segmentation_method = "mesmer,cellpose" } From 829503b48968c5936ed9576df21219c9d06eca82 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Tue, 16 Jan 2024 13:03:45 +0000 Subject: [PATCH 133/149] updated usage --- docs/usage.md | 3 +++ 1 file changed, 3 insertions(+) diff --git a/docs/usage.md b/docs/usage.md index 945d27b..ed37e42 100644 --- a/docs/usage.md +++ b/docs/usage.md @@ -98,6 +98,9 @@ mesmer_compartment: "whole-cell" ilastik_pixel_project: null ilastik_multicut_project: null mindagap_tilesize: 2144 +mindagap_boxsize: 3 +mindagap_loopnum: 40 +mindagap_edges: false skip_clahe: false clahe_cliplimit: 0.01 clahe_nbins: 256 From 155d9c27693e3867f25e709d0aa64ac7d3e4f7d9 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Tue, 16 Jan 2024 13:20:31 +0000 Subject: [PATCH 134/149] update ci.yml --- .github/workflows/ci.yml | 146 +++++++++++++++++++++++++++++++++++---- 1 file changed, 133 insertions(+), 13 deletions(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 169aba6..1e66f51 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -10,34 +10,154 @@ on: env: NXF_ANSI_LOG: false + NFTEST_VER: "0.8.2" concurrency: group: "${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}" cancel-in-progress: true jobs: - test: - name: Run pipeline with test data - # Only run on push if this is the nf-core dev branch (merged PRs) - if: "${{ github.event_name != 'push' || (github.event_name == 'push' && github.repository == 'nf-core/molkart') }}" + nftest-changes: + name: Check for changes (nf-test) runs-on: ubuntu-latest + outputs: + tags: ${{ steps.filter.outputs.changes }} + + steps: + - uses: actions/checkout@v3 + + - name: Combine all tags.yml files + id: get_tags + run: find . -name "tags.yml" -not -path "./.github/*" -exec cat {} + > .github/tags.yml + + - name: debug + run: cat .github/tags.yml + + - uses: frouioui/paths-filter@main + id: filter + with: + filters: ".github/tags.yml" + token: "" + nftest: + name: ${{ matrix.tags }} ${{ matrix.profile }} NF ${{ matrix.NXF_VER }} + runs-on: ubuntu-latest + needs: nftest-changes + if: needs.nftest-changes.outputs.tags != '[]' strategy: + fail-fast: false matrix: + tags: ["${{ fromJson(needs.nftest-changes.outputs.tags) }}"] + profile: ["docker", "singularity"] + TEST_DATA_BASE: + - "test-datasets/data" NXF_VER: - "23.04.0" - "latest-everything" + exclude: + - tags: "custom/dumpsoftwareversions" + env: + NXF_ANSI_LOG: false + TEST_DATA_BASE: "${{ github.workspace }}/test-datasets" + SENTIEON_LICENSE_BASE64: ${{ secrets.SENTIEON_LICENSE_BASE64 }} + steps: - - name: Check out pipeline code - uses: actions/checkout@v4 + - uses: actions/checkout@v3 - - name: Install Nextflow + - uses: actions/setup-java@v3 + with: + distribution: "temurin" + java-version: "17" + - name: Setup Nextflow uses: nf-core/setup-nextflow@v1 + + - name: Cache nf-test installation + id: cache-software + uses: actions/cache@v3 with: - version: "${{ matrix.NXF_VER }}" + path: | + /usr/local/bin/nf-test + /home/runner/.nf-test/nf-test.jar + key: ${{ runner.os }}-${{ env.NFTEST_VER }}-nftest + + - name: Install nf-test + if: steps.cache-software.outputs.cache-hit != 'true' + run: | + wget -qO- https://code.askimed.com/install/nf-test | bash + sudo mv nf-test /usr/local/bin/ + + - name: Setup apptainer + if: matrix.profile == 'singularity' + uses: eWaterCycle/setup-apptainer@main - - name: Run pipeline with test data - # TODO nf-core: You can customise CI pipeline run tests as required - # For example: adding multiple test runs with different parameters - # Remember that you can parallelise this by using strategy.matrix + - name: Set up Singularity + if: matrix.profile == 'singularity' run: | - nextflow run ${GITHUB_WORKSPACE} -profile test,docker --outdir ./results + mkdir -p $NXF_SINGULARITY_CACHEDIR + mkdir -p $NXF_SINGULARITY_LIBRARYDIR + + # Set up secrets + - name: Set up nextflow secrets + if: env.SENTIEON_LICENSE_BASE64 != null + run: | + nextflow secrets set SENTIEON_LICENSE_BASE64 ${{ secrets.SENTIEON_LICENSE_BASE64 }} + nextflow secrets set SENTIEON_AUTH_MECH_BASE64 ${{ secrets.SENTIEON_AUTH_MECH_BASE64 }} + SENTIEON_ENCRYPTION_KEY=$(echo -n "${{ secrets.ENCRYPTION_KEY_BASE64 }}" | base64 -d) + SENTIEON_LICENSE_MESSAGE=$(echo -n "${{ secrets.LICENSE_MESSAGE_BASE64 }}" | base64 -d) + SENTIEON_AUTH_DATA=$(python3 bin/license_message.py encrypt --key "$SENTIEON_ENCRYPTION_KEY" --message "$SENTIEON_LICENSE_MESSAGE") + SENTIEON_AUTH_DATA_BASE64=$(echo -n "$SENTIEON_AUTH_DATA" | base64 -w 0) + nextflow secrets set SENTIEON_AUTH_DATA_BASE64 $SENTIEON_AUTH_DATA_BASE64 + + # Test the module + - name: Run nf-test + run: | + nf-test test \ + --profile=${{ matrix.profile }} \ + --tag ${{ matrix.tags }} \ + --tap=test.tap \ + --verbose + + confirm-pass: + runs-on: ubuntu-latest + needs: + - pytest + - nftest + if: always() + steps: + - name: All tests ok + if: ${{ success() || !contains(needs.*.result, 'failure') }} + run: exit 0 + - name: One or more tests failed + if: ${{ contains(needs.*.result, 'failure') }} + run: exit 1 + + - name: debug-print + if: always() + run: | + echo "toJSON(needs) = ${{ toJSON(needs) }}" + echo "toJSON(needs.*.result) = ${{ toJSON(needs.*.result) }}" + +## nftest: +# name: Run pipeline with test data +# Only run on push if this is the nf-core dev branch (merged PRs) +# if: "${{ github.event_name != 'push' || (github.event_name == 'push' && github.repository == 'nf-core/molkart') }}" +# runs-on: ubuntu-latest +# strategy: +# matrix: +# NXF_VER: +# - "23.04.0" +# - "latest-everything" +# steps: +# - name: Check out pipeline code +# uses: actions/checkout@v4 + +# - name: Install Nextflow +# uses: nf-core/setup-nextflow@v1 +# with: +# version: "${{ matrix.NXF_VER }}"# + +# - name: Run pipeline with test data +# TODO nf-core: You can customise CI pipeline run tests as required +# For example: adding multiple test runs with different parameters +# Remember that you can parallelise this by using strategy.matrix +# run: | +# nextflow run ${GITHUB_WORKSPACE} -profile test,docker --outdir ./results From 1aaaf42ce8b47738f34d0ef7e37249f5c80953e4 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Tue, 16 Jan 2024 15:56:05 +0000 Subject: [PATCH 135/149] attempt at better ci --- .github/workflows/ci.yml | 146 +++++++++++++++++---------------------- 1 file changed, 65 insertions(+), 81 deletions(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 1e66f51..669db10 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -1,10 +1,13 @@ -name: nf-core CI # This workflow runs the pipeline with the minimal test dataset to check that it completes without any syntax errors +name: nf-core CI on: push: branches: - - dev + - "dev" pull_request: + branches: + - "dev" + - "master" release: types: [published] @@ -17,67 +20,65 @@ concurrency: cancel-in-progress: true jobs: - nftest-changes: - name: Check for changes (nf-test) - runs-on: ubuntu-latest + list: + name: List Tests + if: "${{ github.event_name != 'push' || (github.event_name == 'push' && github.repository == 'nf-core/molkart') }}" outputs: - tags: ${{ steps.filter.outputs.changes }} - + # Expose matched filters as job 'modules' output variable + tests: ${{ steps.list.outputs.tests }} + runs-on: ubuntu-latest steps: - uses: actions/checkout@v3 - - name: Combine all tags.yml files - id: get_tags - run: find . -name "tags.yml" -not -path "./.github/*" -exec cat {} + > .github/tags.yml + - name: Setup Nextflow + uses: nf-core/setup-nextflow@v1 - - name: debug - run: cat .github/tags.yml + - name: Install nf-test + if: steps.cache-software.outputs.cache-hit != 'true' + run: | + wget -qO- https://code.askimed.com/install/nf-test | bash + sudo mv nf-test /usr/local/bin/ - - uses: frouioui/paths-filter@main - id: filter - with: - filters: ".github/tags.yml" - token: "" - nftest: - name: ${{ matrix.tags }} ${{ matrix.profile }} NF ${{ matrix.NXF_VER }} + - name: List nf-test + id: list + run: | + echo "tests=$(nf-test list --silent --format=json)" >> "$GITHUB_OUTPUT" + + test: + name: ${{ matrix.tags }} (${{ matrix.profile }}-${{ matrix.NXF_VER }}) + # Only run on push if this is the nf-core dev branch (merged PRs) + if: needs.list.outputs.tests != '[]' + needs: [list] runs-on: ubuntu-latest - needs: nftest-changes - if: needs.nftest-changes.outputs.tags != '[]' strategy: - fail-fast: false matrix: - tags: ["${{ fromJson(needs.nftest-changes.outputs.tags) }}"] - profile: ["docker", "singularity"] - TEST_DATA_BASE: - - "test-datasets/data" NXF_VER: - "23.04.0" - "latest-everything" + profile: ["docker", "singularity"] + test: ["${{ fromJson(needs.list.outputs.tests) }}"] exclude: - - tags: "custom/dumpsoftwareversions" - env: - NXF_ANSI_LOG: false - TEST_DATA_BASE: "${{ github.workspace }}/test-datasets" - SENTIEON_LICENSE_BASE64: ${{ secrets.SENTIEON_LICENSE_BASE64 }} + - test: "tests/subworkflows/local/grohmm/main.nf.test@3508b8c9" + - test: "tests/subworkflows/local/grohmm/main.nf.test@716555be" + - test: "tests/subworkflows/local/grohmm/main.nf.test@306b4b15" steps: - - uses: actions/checkout@v3 - - - uses: actions/setup-java@v3 - with: - distribution: "temurin" - java-version: "17" - - name: Setup Nextflow - uses: nf-core/setup-nextflow@v1 + - name: Check out pipeline code + uses: actions/checkout@v4 - - name: Cache nf-test installation + - name: Cache Nextflow installation id: cache-software uses: actions/cache@v3 with: path: | /usr/local/bin/nf-test /home/runner/.nf-test/nf-test.jar - key: ${{ runner.os }}-${{ env.NFTEST_VER }}-nftest + key: methylseq-${{ runner.os }}-${{ matrix.NXF_VER }} + + - name: Install Nextflow + uses: nf-core/setup-nextflow@v1 + with: + version: "${{ matrix.NXF_VER }}" - name: Install nf-test if: steps.cache-software.outputs.cache-hit != 'true' @@ -85,28 +86,6 @@ jobs: wget -qO- https://code.askimed.com/install/nf-test | bash sudo mv nf-test /usr/local/bin/ - - name: Setup apptainer - if: matrix.profile == 'singularity' - uses: eWaterCycle/setup-apptainer@main - - - name: Set up Singularity - if: matrix.profile == 'singularity' - run: | - mkdir -p $NXF_SINGULARITY_CACHEDIR - mkdir -p $NXF_SINGULARITY_LIBRARYDIR - - # Set up secrets - - name: Set up nextflow secrets - if: env.SENTIEON_LICENSE_BASE64 != null - run: | - nextflow secrets set SENTIEON_LICENSE_BASE64 ${{ secrets.SENTIEON_LICENSE_BASE64 }} - nextflow secrets set SENTIEON_AUTH_MECH_BASE64 ${{ secrets.SENTIEON_AUTH_MECH_BASE64 }} - SENTIEON_ENCRYPTION_KEY=$(echo -n "${{ secrets.ENCRYPTION_KEY_BASE64 }}" | base64 -d) - SENTIEON_LICENSE_MESSAGE=$(echo -n "${{ secrets.LICENSE_MESSAGE_BASE64 }}" | base64 -d) - SENTIEON_AUTH_DATA=$(python3 bin/license_message.py encrypt --key "$SENTIEON_ENCRYPTION_KEY" --message "$SENTIEON_LICENSE_MESSAGE") - SENTIEON_AUTH_DATA_BASE64=$(echo -n "$SENTIEON_AUTH_DATA" | base64 -w 0) - nextflow secrets set SENTIEON_AUTH_DATA_BASE64 $SENTIEON_AUTH_DATA_BASE64 - # Test the module - name: Run nf-test run: | @@ -116,25 +95,30 @@ jobs: --tap=test.tap \ --verbose - confirm-pass: - runs-on: ubuntu-latest - needs: - - pytest - - nftest - if: always() - steps: - - name: All tests ok - if: ${{ success() || !contains(needs.*.result, 'failure') }} - run: exit 0 - - name: One or more tests failed - if: ${{ contains(needs.*.result, 'failure') }} - run: exit 1 - - - name: debug-print - if: always() + - name: Set up Singularity + if: matrix.profile == 'singularity' + uses: eWaterCycle/setup-singularity@v5 + with: + singularity-version: 3.7.1 + + - name: Run nf-test + run: | + nf-test test \ + --profile="test,${{ matrix.profile }}" \ + ${{ matrix.test }} \ + --junitxml=${{ matrix.test }}-${{ matrix.profile }}.xml + + - name: Publish Test Report + uses: mikepenz/action-junit-report@v3 + if: success() || failure() # run this step even if previous step failed + with: + path: ${{ matrix.test }}-${{ matrix.profile }}.xml + + - name: Output log on failure + if: failure() run: | - echo "toJSON(needs) = ${{ toJSON(needs) }}" - echo "toJSON(needs.*.result) = ${{ toJSON(needs.*.result) }}" + sudo apt install bat > /dev/null + batcat --decorations=always --color=always ${{ github.workspace }}/.nf-test/tests/*/output/pipeline_info/software_versions.yml ## nftest: # name: Run pipeline with test data From e7bce41422f1c213ac1d9799c649f7fefebcc9e1 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Tue, 16 Jan 2024 16:22:16 +0000 Subject: [PATCH 136/149] attempt at ci --- .github/workflows/ci.yml | 11 ++++++----- 1 file changed, 6 insertions(+), 5 deletions(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 669db10..8eeb716 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -58,9 +58,11 @@ jobs: profile: ["docker", "singularity"] test: ["${{ fromJson(needs.list.outputs.tests) }}"] exclude: - - test: "tests/subworkflows/local/grohmm/main.nf.test@3508b8c9" - - test: "tests/subworkflows/local/grohmm/main.nf.test@716555be" - - test: "tests/subworkflows/local/grohmm/main.nf.test@306b4b15" + - tag: "custom/dumpsoftwareversions" + - tag: "deepcell/mesmer" + - tag: "mindagap" + - tag: "custom/dumpsoftwareversions" + - tag: "multiqc" steps: - name: Check out pipeline code @@ -73,7 +75,7 @@ jobs: path: | /usr/local/bin/nf-test /home/runner/.nf-test/nf-test.jar - key: methylseq-${{ runner.os }}-${{ matrix.NXF_VER }} + key: molkart-${{ runner.os }}-${{ matrix.NXF_VER }} - name: Install Nextflow uses: nf-core/setup-nextflow@v1 @@ -92,7 +94,6 @@ jobs: nf-test test \ --profile=${{ matrix.profile }} \ --tag ${{ matrix.tags }} \ - --tap=test.tap \ --verbose - name: Set up Singularity From 68d0b1572ac5b3d42623a61b3150144a5fdb86b6 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Tue, 16 Jan 2024 16:36:10 +0000 Subject: [PATCH 137/149] ci attempt --- .github/workflows/ci.yml | 6 ------ 1 file changed, 6 deletions(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 8eeb716..668cf46 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -57,12 +57,6 @@ jobs: - "latest-everything" profile: ["docker", "singularity"] test: ["${{ fromJson(needs.list.outputs.tests) }}"] - exclude: - - tag: "custom/dumpsoftwareversions" - - tag: "deepcell/mesmer" - - tag: "mindagap" - - tag: "custom/dumpsoftwareversions" - - tag: "multiqc" steps: - name: Check out pipeline code From 950ab231ee2b194ba15029f889d4d8b11379f666 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Tue, 16 Jan 2024 16:46:39 +0000 Subject: [PATCH 138/149] ci attempt --- .github/workflows/ci.yml | 1 + 1 file changed, 1 insertion(+) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 668cf46..3bb3435 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -101,6 +101,7 @@ jobs: nf-test test \ --profile="test,${{ matrix.profile }}" \ ${{ matrix.test }} \ + --tag ${{ matrix.tags }} \ --junitxml=${{ matrix.test }}-${{ matrix.profile }}.xml - name: Publish Test Report From be09362a474bfb6f2f3de2eca6c44dc228f2d41e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Tue, 16 Jan 2024 17:03:23 +0000 Subject: [PATCH 139/149] ci attempt --- .github/workflows/ci.yml | 39 ++++++--------------------------------- 1 file changed, 6 insertions(+), 33 deletions(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 3bb3435..e20257b 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -82,6 +82,12 @@ jobs: wget -qO- https://code.askimed.com/install/nf-test | bash sudo mv nf-test /usr/local/bin/ + - name: Set up Singularity + if: matrix.profile == 'singularity' + uses: eWaterCycle/setup-singularity@v5 + with: + singularity-version: 3.7.1 + # Test the module - name: Run nf-test run: | @@ -90,18 +96,11 @@ jobs: --tag ${{ matrix.tags }} \ --verbose - - name: Set up Singularity - if: matrix.profile == 'singularity' - uses: eWaterCycle/setup-singularity@v5 - with: - singularity-version: 3.7.1 - - name: Run nf-test run: | nf-test test \ --profile="test,${{ matrix.profile }}" \ ${{ matrix.test }} \ - --tag ${{ matrix.tags }} \ --junitxml=${{ matrix.test }}-${{ matrix.profile }}.xml - name: Publish Test Report @@ -115,29 +114,3 @@ jobs: run: | sudo apt install bat > /dev/null batcat --decorations=always --color=always ${{ github.workspace }}/.nf-test/tests/*/output/pipeline_info/software_versions.yml - -## nftest: -# name: Run pipeline with test data -# Only run on push if this is the nf-core dev branch (merged PRs) -# if: "${{ github.event_name != 'push' || (github.event_name == 'push' && github.repository == 'nf-core/molkart') }}" -# runs-on: ubuntu-latest -# strategy: -# matrix: -# NXF_VER: -# - "23.04.0" -# - "latest-everything" -# steps: -# - name: Check out pipeline code -# uses: actions/checkout@v4 - -# - name: Install Nextflow -# uses: nf-core/setup-nextflow@v1 -# with: -# version: "${{ matrix.NXF_VER }}"# - -# - name: Run pipeline with test data -# TODO nf-core: You can customise CI pipeline run tests as required -# For example: adding multiple test runs with different parameters -# Remember that you can parallelise this by using strategy.matrix -# run: | -# nextflow run ${GITHUB_WORKSPACE} -profile test,docker --outdir ./results From b8e753054451c186fefad47f15c1eba7c9bca5a5 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Tue, 16 Jan 2024 17:05:12 +0000 Subject: [PATCH 140/149] ci attempt --- .github/workflows/ci.yml | 8 -------- 1 file changed, 8 deletions(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index e20257b..4dd4f64 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -88,14 +88,6 @@ jobs: with: singularity-version: 3.7.1 - # Test the module - - name: Run nf-test - run: | - nf-test test \ - --profile=${{ matrix.profile }} \ - --tag ${{ matrix.tags }} \ - --verbose - - name: Run nf-test run: | nf-test test \ From c33fdc688c4a067cbd21daf8eec2e510770326d7 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Tue, 16 Jan 2024 17:24:45 +0000 Subject: [PATCH 141/149] removed singularity from ci test --- .github/workflows/ci.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 4dd4f64..ffca402 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -55,7 +55,7 @@ jobs: NXF_VER: - "23.04.0" - "latest-everything" - profile: ["docker", "singularity"] + profile: ["docker"] #TODO add "singularity" test: ["${{ fromJson(needs.list.outputs.tests) }}"] steps: From 59c7ece4cb1327c0ec494850e78bf83d8d73773d Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Tue, 16 Jan 2024 17:37:27 +0000 Subject: [PATCH 142/149] updated base.config --- CHANGELOG.md | 2 ++ conf/base.config | 10 +++++----- 2 files changed, 7 insertions(+), 5 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 78205fb..09a47f7 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -9,6 +9,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 - mindagap_boxsize, mindagap_loopnum, mindagap_edges parameters - updated mindagap version and adapted molkart.nf and modules.config to match updated mindagap module version +- CI testing with nf-test +- updated base.config to account for ilastik's high memory use ## v1.0.1dev - [2024.01.08] diff --git a/conf/base.config b/conf/base.config index 1c2c62a..8a67abc 100644 --- a/conf/base.config +++ b/conf/base.config @@ -9,8 +9,6 @@ */ process { - - // TODO nf-core: Check the defaults for all processes cpus = { check_max( 1 * task.attempt, 'cpus' ) } memory = { check_max( 6.GB * task.attempt, 'memory' ) } time = { check_max( 4.h * task.attempt, 'time' ) } @@ -24,8 +22,6 @@ process { // These labels are used and recognised by default in DSL2 files hosted on nf-core/modules. // If possible, it would be nice to keep the same label naming convention when // adding in your local modules too. - // TODO nf-core: Customise requirements for specific processes. - // See https://www.nextflow.io/docs/latest/config.html#config-process-selectors withLabel:process_single { cpus = { check_max( 1 , 'cpus' ) } memory = { check_max( 6.GB * task.attempt, 'memory' ) } @@ -57,9 +53,13 @@ process { } withLabel:error_retry { errorStrategy = 'retry' - maxRetries = 2 + maxRetries = 3 } withName:CUSTOM_DUMPSOFTWAREVERSIONS { cache = false } + + withName:'ILASTIK_PIXELCLASSIFICATION|ILASTIK_MULTICUT' { + label = "process_high" + } } From 181c2acdd4d08461ac165f72fc64087a3db6bf48 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Fri, 19 Jan 2024 12:39:31 +0000 Subject: [PATCH 143/149] metromap and logo update --- CHANGELOG.md | 1 + assets/nf-core-molkart_logo_light.png | Bin 70183 -> 430197 bytes docs/images/molkart_workflow.png | Bin 588106 -> 634720 bytes docs/images/nf-core-molkart_logo_dark.png | Bin 70262 -> 425272 bytes docs/images/nf-core-molkart_logo_light.png | Bin 70183 -> 430197 bytes 5 files changed, 1 insertion(+) diff --git a/CHANGELOG.md b/CHANGELOG.md index 09a47f7..91a7053 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -11,6 +11,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 - updated mindagap version and adapted molkart.nf and modules.config to match updated mindagap module version - CI testing with nf-test - updated base.config to account for ilastik's high memory use +- updated metromap and logos ## v1.0.1dev - [2024.01.08] diff --git 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assets/nf-core-molkart_logo_light.png, docs/images/nf-core-molkart_logo_light.png, docs/images/nf-core-molkart_logo_dark.png should not be changed. --- CHANGELOG.md | 1 - assets/nf-core-molkart_logo_light.png | Bin 430197 -> 70183 bytes docs/images/molkart_workflow.png | Bin 634720 -> 588106 bytes docs/images/nf-core-molkart_logo_dark.png | Bin 425272 -> 70262 bytes docs/images/nf-core-molkart_logo_light.png | Bin 430197 -> 70183 bytes 5 files changed, 1 deletion(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 91a7053..09a47f7 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -11,7 +11,6 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 - updated mindagap version and adapted molkart.nf and modules.config to match updated mindagap module version - CI testing with nf-test - updated base.config to account for ilastik's high memory use -- updated metromap and logos ## v1.0.1dev - [2024.01.08] diff --git a/assets/nf-core-molkart_logo_light.png 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docs/images/molkart_workflow.png | Bin 588106 -> 634720 bytes 2 files changed, 1 insertion(+) diff --git a/CHANGELOG.md b/CHANGELOG.md index 09a47f7..72f3787 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -11,6 +11,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 - updated mindagap version and adapted molkart.nf and modules.config to match updated mindagap module version - CI testing with nf-test - updated base.config to account for ilastik's high memory use +- updated metromap ## v1.0.1dev - [2024.01.08] diff --git a/docs/images/molkart_workflow.png b/docs/images/molkart_workflow.png index bd97795c75dc165e0320f8e960945c32a04efc8e..2d3de1c001b22537c6105867a9413e1a3c65508b 100644 GIT binary patch literal 634720 zcmeFZWmuJKw>FHjOcV?Rky2VD1f)wrK^j4&I|b=(3`FUWP+9>&I;XUPlypuyq+>Ga zj(6Ok&-3j4?)S&{{oeCf3vkwb#fbAf$GGly^0MOR&t5x=gM)Kk;^BP-9GoljI5=kn zPM?HlSUX*G;MW<;hblHWI4so2|HmAYgze!;659vLwu%;pwhlVh1~?854lK{iO>Oja 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nf-core-bot Date: Fri, 19 Jan 2024 12:56:43 +0000 Subject: [PATCH 146/149] [automated] Fix linting with Prettier --- .devcontainer/devcontainer.json | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/.devcontainer/devcontainer.json b/.devcontainer/devcontainer.json index 4ecfbfe..4a9bc5c 100644 --- a/.devcontainer/devcontainer.json +++ b/.devcontainer/devcontainer.json @@ -18,11 +18,11 @@ "python.linting.flake8Path": "/opt/conda/bin/flake8", "python.linting.pycodestylePath": "/opt/conda/bin/pycodestyle", "python.linting.pydocstylePath": "/opt/conda/bin/pydocstyle", - "python.linting.pylintPath": "/opt/conda/bin/pylint" + "python.linting.pylintPath": "/opt/conda/bin/pylint", }, // Add the IDs of extensions you want installed when the container is created. - "extensions": ["ms-python.python", "ms-python.vscode-pylance", "nf-core.nf-core-extensionpack"] - } - } + "extensions": ["ms-python.python", "ms-python.vscode-pylance", "nf-core.nf-core-extensionpack"], + }, + }, } From ae4c361cbafb5f2bde551cfe05b909453b2bfe7c Mon Sep 17 00:00:00 2001 From: Florian Wuennemann Date: Wed, 24 Jan 2024 09:14:49 +0100 Subject: [PATCH 147/149] Update test_full.config Changed mindagap params for full test to reduce runtime. --- conf/test_full.config | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/conf/test_full.config b/conf/test_full.config index 586de22..30c1090 100644 --- a/conf/test_full.config +++ b/conf/test_full.config @@ -17,7 +17,7 @@ params { input = 'https://raw.githubusercontent.com/nf-core/test-datasets/molkart/test_data/samplesheets/samplesheet_full_test.csv' segmentation_method = "mesmer,cellpose" - mindagap_boxsize = 7 - mindagap_loopnum = 100 + mindagap_boxsize = 3 + mindagap_loopnum = 40 cellpose_pretrained_model = "nuclei" } From 749646810d84c299958a6cf8a6d47751b2ec917d Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Wed, 24 Jan 2024 13:50:04 +0000 Subject: [PATCH 148/149] updated mesmer to exlude leftover todo --- modules.json | 2 +- modules/nf-core/deepcell/mesmer/tests/main.nf.test | 2 -- 2 files changed, 1 insertion(+), 3 deletions(-) diff --git a/modules.json b/modules.json index 4b26013..85bce5c 100644 --- a/modules.json +++ b/modules.json @@ -17,7 +17,7 @@ }, "deepcell/mesmer": { "branch": "master", - "git_sha": "cc78b60f09035580096230a7e73e3846689be698", + "git_sha": "81fcaa73c7f1668a1c289464da88bf5eff582bcd", "installed_by": ["modules"] }, "ilastik/multicut": { diff --git a/modules/nf-core/deepcell/mesmer/tests/main.nf.test b/modules/nf-core/deepcell/mesmer/tests/main.nf.test index 29645d5..9546c1e 100644 --- a/modules/nf-core/deepcell/mesmer/tests/main.nf.test +++ b/modules/nf-core/deepcell/mesmer/tests/main.nf.test @@ -1,5 +1,3 @@ -// TODO nf-core: Once you have added the required tests, please run the following command to build this file: -// nf-core modules test deepcell/mesmer nextflow_process { name "Test Process DEEPCELL_MESMER" From 14841aec064ef14252ba0ab1662bfe1d08da7017 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kre=C5=A1imir=20Be=C5=A1tak?= Date: Wed, 24 Jan 2024 15:21:14 +0000 Subject: [PATCH 149/149] version bump 1.0.0 --- assets/multiqc_config.yml | 4 ++-- nextflow.config | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/assets/multiqc_config.yml b/assets/multiqc_config.yml index 820f824..16519ec 100644 --- a/assets/multiqc_config.yml +++ b/assets/multiqc_config.yml @@ -3,9 +3,9 @@ custom_logo_url: https://github.com/nf-core/molkart/ custom_logo_title: "nf-core/molkart" report_comment: > - This report has been generated by the nf-core/molkart + This report has been generated by the nf-core/molkart analysis pipeline. For information about how to interpret these results, please see the - documentation. + documentation. report_section_order: "nf-core-molkart-methods-description": order: -1000 diff --git a/nextflow.config b/nextflow.config index 7afc0d3..b7a0dbd 100644 --- a/nextflow.config +++ b/nextflow.config @@ -257,7 +257,7 @@ manifest { description = """An analysis pipeline for Molecular Cartography data from Resolve Biosciences.""" mainScript = 'main.nf' nextflowVersion = '!>=23.04.0' - version = '1.0dev' + version = '1.0.0' doi = '' }

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    Process Name \\", + " \\ Software Version
    CUSTOM_DUMPSOFTWAREVERSIONSpython3.11.7
    yaml5.4.1
    TOOL1tool10.11.9
    TOOL2tool21.9
    WorkflowNextflow