Chaining proteinfold

CHANGELOG.md

@@ -39,6 +39,7 @@ Initial release of nf-core/multiplesequencealign, created with the [nf-core](htt
 - [[#147](https://github.com/nf-core/multiplesequencealign/pull/147)] - Add small testing profile + some fixes of the shiny app.
 - [[#148](https://github.com/nf-core/multiplesequencealign/pull/148)] - Add UPP module.
 - [[#150](https://github.com/nf-core/multiplesequencealign/pull/150)] - Update modules and readme for pre-release.
+- [[#174](https://github.com/nf-core/multiplesequencealign/issues/174)] - Add the chaining of proteinfold output to MSA input.
 
 ### `Fixed`
 

README.md

@@ -38,9 +38,8 @@ The pipeline performs the following steps:
 
 ## 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.
 
 #### 1. SAMPLESHEET
 
@@ -57,9 +56,8 @@ toxin,toxin.fa,toxin-ref.fa,toxin_structures,toxin_template.txt
 
 Each row represents a set of sequences (in this case the seatoxin and toxin protein families) to be aligned and the associated (if available) reference alignments and dependency files (this can be anything from protein structure or any other information you would want to use in your favourite MSA tool).
 
-:::note
-The only required input is the id column and either fasta or dependencies.
-:::
+> [!NOTE]
+> The only required input is the id column and either fasta or dependencies.
 
 #### 2. TOOLSHEET
 
@@ -78,9 +76,8 @@ FAMSA, -gt upgma -medoidtree, FAMSA,
 FAMSA,,REGRESSIVE,
 ```
 
-:::note
-The only required input is aligner.
-:::
+> [!NOTE]
+> The only required input is aligner.
 
 #### 3. RUN THE PIPELINE
 

docs/usage/chaining_with_proteinfold.md

@@ -0,0 +1,42 @@
+# Using nf-core/proteinfold to generate the input protein structures
+
+Structural aligners leverage protein structural information to render the MSA.
+
+You can provide your PDB structures via the samplesheet, as outlined in the primary usage documentation. However, if you do not already have protein structures available, you may opt to use protein structure prediction tools to create these models.
+
+To facilitate this, we offer seamless integration with the nf-core/proteinfold pipeline, enabling you to generate the protein structures required for this workflow.
+
+To do so, you only need to build one samplesheet file, in the exact format required by nf-core/multiplesequencealign pipeline.
+This is made compatible with nf-core/proteinfold and will predict and output the structures in the format required by the nf-core/multiplesquencealign pipeline.
+
+Now, to run you simply can use the following code.
+Please refer to the [proteinfold documentation](https://nf-co.re/proteinfold/1.0.0/) for picking your favourite params.
+
+Here we showcase how to run proteinfold in its colabfold local flavour - but it works for all the proteinfold modes.
+
+```bash
+nextflow run nf-core/proteinfold --input ./samplesheet.csv \
+                                --outdir ./proteinfold_results \
+                                --split_fasta \
+                                -r dev \
+                                --mode colabfold \
+                                --colabfold_server local \
+                                --colabfold_db <null (default) | PATH> \
+                                --num_recycle 3 \
+                                --use_amber <true/false> \
+                                --colabfold_model_preset "AlphaFold2-ptm" \
+                                --use_gpu <true/false> \
+                                --db_load_mode 0
+                                -profile <docker/singularity/podman/shifter/charliecloud/conda/institute>
+
+
+nextflow run nf-core/multiplesequencealign --input ./samplesheet.csv \
+                                        --tools ./toolsheet.csv \
+                                        --dependencies_dir ./proteinfold_results/*/*/top_ranked_structures \
+                                        --outdir ./results \
+                                        -profile <docker/singularity/podman/shifter/charliecloud/conda/institute>
+
+```
+
+> [!NOTE]
+> The one imporant parameter NOT to forget in proteinfold for the chaining is `--split_fasta`. This will allow to use a multifasta file as input for monomer predictions, needed by the MSA pipeline. Also, currently the changes needed for the chaining are only present in the dev branch of proteinfold, so also do not forget `-r dev`. The rest of the proteinfold parameters can and should be tuned according to your preferences for your proteinfold run. Please refer to the proteinfold documentation for this.

modules.json

@@ -7,7 +7,7 @@
                 "nf-core": {
                     "clustalo/align": {
                         "branch": "master",
-                        "git_sha": "666652151335353eef2fcd58880bcef5bc2928e1",
+                        "git_sha": "2a8530b890878747f5063a894bad9fb2abd5c071",
                         "installed_by": ["modules"]
                     },
                     "clustalo/guidetree": {
@@ -99,12 +99,12 @@
                     },
                     "tcoffee/alncompare": {
                         "branch": "master",
-                        "git_sha": "666652151335353eef2fcd58880bcef5bc2928e1",
+                        "git_sha": "ffa000ab3c33df25a165b5f9a039c4cbb665a77b",
                         "installed_by": ["modules"]
                     },
                     "tcoffee/consensus": {
                         "branch": "master",
-                        "git_sha": "66b22564bc1bc0db7292f2073cdef954ead773e7",
+                        "git_sha": "023e51187884ea6cc7290767486f551565f1b77a",
                         "installed_by": ["modules"]
                     },
                     "tcoffee/irmsd": {
@@ -143,17 +143,17 @@
                 "nf-core": {
                     "utils_nextflow_pipeline": {
                         "branch": "master",
-                        "git_sha": "3aa0aec1d52d492fe241919f0c6100ebf0074082",
+                        "git_sha": "c2b22d85f30a706a3073387f30380704fcae013b",
                         "installed_by": ["subworkflows"]
                     },
                     "utils_nfcore_pipeline": {
                         "branch": "master",
-                        "git_sha": "1b6b9a3338d011367137808b49b923515080e3ba",
+                        "git_sha": "1b89f75f1aa2021ec3360d0deccd0f6e97240551",
                         "installed_by": ["subworkflows"]
                     },
                     "utils_nfschema_plugin": {
                         "branch": "master",
-                        "git_sha": "bbd5a41f4535a8defafe6080e00ea74c45f4f96c",
+                        "git_sha": "2fd2cd6d0e7b273747f32e465fdc6bcc3ae0814e",
                         "installed_by": ["subworkflows"]
                     }
                 }