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Amplicon_analysis-galaxy

A Galaxy tool wrapper to Mauro Tutino's Amplicon_analysis pipeline script at https://github.com/MTutino/Amplicon_analysis

The pipeline can analyse paired-end 16S rRNA data from Illumina Miseq (Casava >= 1.8) and performs the following operations:

  • QC and clean up of input data
  • Removal of singletons and chimeras and building of OTU table and phylogenetic tree
  • Beta and alpha diversity of analysis

Usage documentation

Usage of the tool (including required inputs) is documented within the help section of the tool XML.

Installing the tool in a Galaxy instance

The following sections describe how to install the tool files, dependencies and reference data, and how to configure the Galaxy instance to detect the dependencies and reference data correctly at run time.

1. Install the tool from the toolshed

The core tool is hosted on the Galaxy toolshed, so it can be installed directly from there (this is the recommended route):

Alternatively it can be installed manually; in this case there are two files to install:

  • amplicon_analysis_pipeline.xml (the Galaxy tool definition)
  • amplicon_analysis_pipeline.py (the Python wrapper script)

Put these in a directory that is visible to Galaxy (e.g. a tools/Amplicon_analysis/ folder), and modify the tools_conf.xml file to tell Galaxy to offer the tool by adding the line e.g.:

<tool file="Amplicon_analysis/amplicon_analysis_pipeline.xml" />

2. Install the reference data

The script References.sh from the pipeline package at https://github.com/MTutino/Amplicon_analysis can be run to install the reference data, for example:

cd /path/to/pipeline/data
wget https://github.com/MTutino/Amplicon_analysis/raw/master/References.sh
/bin/bash ./References.sh

will install the data in /path/to/pipeline/data.

NB The final amount of data downloaded and uncompressed will be around 9GB.

3. Configure reference data location in Galaxy

The final step is to make your Galaxy installation aware of the location of the reference data, so it can locate them both when the tool is run.

The tool locates the reference data via an environment variable called AMPLICON_ANALYSIS_REF_DATA_PATH, which needs to set to the parent directory where the reference data has been installed.

There are various ways to do this, depending on how your Galaxy installation is configured:

  • For local instances: add a line to set it in the config/local_env.sh file of your Galaxy installation (you may need to create a new empty file first), e.g.:

    export AMPLICON_ANALYSIS_REF_DATA_PATH=/path/to/pipeline/data

  • For production instances: set the value in the job_conf.xml configuration file, e.g.:

    <destination id="amplicon_analysis">
   <env id="AMPLICON_ANALYSIS_REF_DATA_PATH">/path/to/pipeline/data</env>
</destination>

    and then specify that the pipeline tool uses this destination:

    <tool id="amplicon_analysis_pipeline" destination="amplicon_analysis"/>

    (For more about job destinations see the Galaxy documentation at https://docs.galaxyproject.org/en/master/admin/jobs.html#job-destinations)

4. Enable rendering of HTML outputs from pipeline

To ensure that HTML outputs are displayed correctly in Galaxy (for example the Vsearch OTU table heatmaps), Galaxy needs to be configured not to sanitize the outputs from the Amplicon_analysis tool.

Either:

  • For local instances: set sanitize_all_html = False in config/galaxy.ini (nb don't do this on production servers or public instances!); or
  • For production instances: add the Amplicon_analysis tool to the display whitelist in the Galaxy instance:
    • Set sanitize_whitelist_file = config/whitelist.txt in config/galaxy.ini and restart Galaxy;
    • Go to Admin>Manage Display Whitelist, check the box for Amplicon_analysis (hint: use your browser's 'find-in-page' search function to help locate it) and click on Submit new whitelist to update the settings.

Additional details

Some other things to be aware of:

  • Note that using the Silva database requires a minimum of 18Gb RAM

Known problems

  • Only the VSEARCH pipeline in Mauro's script is currently available via the Galaxy tool; the USEARCH and QIIME pipelines have yet to be implemented.

  • The images in the tool help section are not visible if the tool has been installed locally, or if it has been installed in a Galaxy instance which is served from a subdirectory.

    These are both problems with Galaxy and not the tool, see galaxyproject/galaxy#4490 and galaxyproject/galaxy#1676

Appendix: installing the dependencies manually

If the tool is installed from the Galaxy toolshed (recommended) then the dependencies should be installed automatically and this step can be skipped.

Otherwise the install_amplicon_analysis_deps.sh script can be used to fetch and install the dependencies locally, for example:

install_amplicon_analysis.sh /path/to/local_tool_dependencies

(This is the same script as is used to install dependencies from the toolshed.) This can take some time to complete, and when completed will have created a directory called Amplicon_analysis-1.2.3 containing the dependencies under the specified top level directory.

NB The installed dependencies will occupy around 2.6G of disk space.

You will need to make sure that the bin subdirectory of this directory is on Galaxy's PATH at runtime, for the tool to be able to access the dependencies - for example by adding a line to the local_env.sh file like:

export PATH=/path/to/local_tool_dependencies/Amplicon_analysis-1.2.3/bin:$PATH

History

Version Changes
1.3.5.0 Updated to Amplicon_Analysis_Pipeline version 1.3.5.
1.2.3.0 Updated to Amplicon_Analysis_Pipeline version 1.2.3; install dependencies via tool_dependencies.xml.
1.2.2.0 Updated to Amplicon_Analysis_Pipeline version 1.2.2 (removes jackknifed analysis which is not captured by Galaxy tool)
1.2.1.0 Updated to Amplicon_Analysis_Pipeline version 1.2.1 (adds option to use the Human Oral Microbiome Database v15.1, and updates SILVA database to v123)
1.1.0 First official version on Galaxy toolshed.
1.0.6 Expand inline documentation to provide detailed usage guidance.
1.0.5

Updates including:

  • Capture read counts from quality control as new output dataset
  • Capture FastQC per-base quality boxplots for each sample as new output dataset
  • Add support for -l option (sliding window length for trimming)
  • Default for -L set to "200"
1.0.4

Various updates:

  • Additional outputs are captured when a "Categories" file is supplied (alpha diversity rarefaction curves and boxplots)
  • Sample names derived from Fastqs in a collection of pairs are trimmed to SAMPLE_S* (for Illumina-style Fastq filenames)
  • Input Fastqs can now be of more general fastq type
  • Log file outputs are captured in new output dataset
  • User can specify a "title" for the job which is copied into the dataset names (to distinguish outputs from different runs)
  • Improved detection and reporting of problems with input Metatable
1.0.3 Take the sample names from the collection dataset names when using collection as input (this is now the default input mode); collect additional output dataset; disable usearch-based pipelines (i.e. UPARSE and QIIME).
1.0.2 Enable support for FASTQs supplied via dataset collections and fix some broken output datasets.
1.0.1 Initial version