friendsofstrandseq/mosaicatcher-pipeline

Integrated workflow for SV calling from single-cell Strand-seq data

Overview

Topics: bioinformatics pipeline snakemake strand-seq mosaicatcher genomics

Latest release: 2.3.5, Last update: 2024-07-30

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Deployment

Step 1: Install Snakemake and Snakedeploy

Snakemake and Snakedeploy are best installed via the Mamba package manager (a drop-in replacement for conda). If you have neither Conda nor Mamba, it is recommended to install Miniforge. More details regarding Mamba can be found here.

When using Mamba, run

mamba create -c conda-forge -c bioconda --name snakemake snakemake snakedeploy

to install both Snakemake and Snakedeploy in an isolated environment. For all following commands ensure that this environment is activated via

conda activate snakemake

Step 2: Deploy workflow

With Snakemake and Snakedeploy installed, the workflow can be deployed as follows. First, create an appropriate project working directory on your system and enter it:

mkdir -p path/to/project-workdir
cd path/to/project-workdir

In all following steps, we will assume that you are inside of that directory. Then run

snakedeploy deploy-workflow https://github.com/friendsofstrandseq/mosaicatcher-pipeline . --tag 2.3.5

Snakedeploy will create two folders, workflow and config. The former contains the deployment of the chosen workflow as a Snakemake module, the latter contains configuration files which will be modified in the next step in order to configure the workflow to your needs.

Step 3: Configure workflow

To configure the workflow, adapt config/config.yml to your needs following the instructions below.

Step 4: Run workflow

The deployment method is controlled using the --software-deployment-method (short --sdm) argument.

To run the workflow with automatic deployment of all required software via conda/mamba, use

snakemake --cores all --sdm conda

To run the workflow using a combination of conda and apptainer/singularity for software deployment, use

snakemake --cores all --sdm conda apptainer

Snakemake will automatically detect the main Snakefile in the workflow subfolder and execute the workflow module that has been defined by the deployment in step 2.

For further options such as cluster and cloud execution, see the docs.

Step 5: Generate report

After finalizing your data analysis, you can automatically generate an interactive visual HTML report for inspection of results together with parameters and code inside of the browser using

snakemake --report report.zip

Configuration

The following section is imported from the workflow’s config/README.md.

General settings

To configure this workflow, modify config/config.yaml according to your needs, following the explanations provided in the file.

Samples

At this moment, mosaicatcher-pipeline is designed to automatically produce a configuration file saved in the input folder selected based on the parameter <input_bam_location>. This configuration file looks like the following when running the pipeline with ashleys-qc-pipeline preprocessing module disabled (BAM input):

File	Folder	Sample	Cell	Full_path
BM510x3PE20401	.tests/data_CHR21	RPE-BM510	BM510x3PE20401	.tests/data_CHR21/RPE-BM510/all/BM510x3PE20401.sort.mdup.bam
BM510x3PE20402	.tests/data_CHR21	RPE-BM510	BM510x3PE20402	.tests/data_CHR21/RPE-BM510/all/BM510x3PE20402.sort.mdup.bam

If the ashleys-qc-pipeline preprocessing module is enabled (FASTQ input), thus the configuration file looks like the following:

File	Folder	Sample	Cell	Full_path
BM510x3PE20401.1	.tests/data_CHR21	RPE-BM510	BM510x3PE20401	.tests/data_CHR21/RPE-BM510/fastq/BM510x3PE20401.1.fastq.gz
BM510x3PE20401.2	.tests/data_CHR21	RPE-BM510	BM510x3PE20401	.tests/data_CHR21/RPE-BM510/fastq/BM510x3PE20401.2.fastq.gz
BM510x3PE20402.1	.tests/data_CHR21	RPE-BM510	BM510x3PE20402	.tests/data_CHR21/RPE-BM510/fastq/BM510x3PE20402.1.fastq.gz
BM510x3PE20402.2	.tests/data_CHR21	RPE-BM510	BM510x3PE20402	.tests/data_CHR21/RPE-BM510/fastq/BM510x3PE20402.2.fastq.gz

This configuration file is then used to create the dictionnary and lists needed to flag wildcards and identify the samples, the different cells for each of them and the associated files.

Linting and formatting

Linting results

/tmp/tmpo3lak8m3/friendsofstrandseq-mosaicatcher-pipeline-2b6921d/workflow/scripts/utils/pipeline_aesthetic_start.py:18: SyntaxWarning: invalid escape sequence '\ '
  smk = """
/tmp/tmpo3lak8m3/friendsofstrandseq-mosaicatcher-pipeline-2b6921d/workflow/scripts/utils/pipeline_aesthetic_start.py:26: SyntaxWarning: invalid escape sequence '\/'
  wf_name = """
/tmp/tmpo3lak8m3/friendsofstrandseq-mosaicatcher-pipeline-2b6921d/workflow/scripts/utils/pipeline_aesthetic_start.py:138: SyntaxWarning: invalid escape sequence '\ '
  smk = """
/tmp/tmpo3lak8m3/friendsofstrandseq-mosaicatcher-pipeline-2b6921d/workflow/scripts/utils/pipeline_aesthetic_start.py:145: SyntaxWarning: invalid escape sequence '\/'
  wf_name = """
Traceback (most recent call last):

  File "/home/runner/micromamba-root/envs/snakemake-workflow-catalog/lib/python3.12/site-packages/snakemake/cli.py", line 2011, in args_to_api
    any_lint = workflow_api.lint()
               ^^^^^^^^^^^^^^^^^^^

  File "/home/runner/micromamba-root/envs/snakemake-workflow-catalog/lib/python3.12/site-packages/snakemake/api.py", line 337, in _handle_no_dag
    return method(self, *args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

  File "/home/runner/micromamba-root/envs/snakemake-workflow-catalog/lib/python3.12/site-packages/snakemake/api.py", line 354, in lint
    workflow.include(

... (truncated)

Formatting results

[DEBUG] 
[DEBUG] In file "/tmp/tmpo3lak8m3/friendsofstrandseq-mosaicatcher-pipeline-2b6921d/workflow/rules/setup.smk":  Formatted content is different from original
[DEBUG] 
[DEBUG] 
[DEBUG] 
[DEBUG] In file "/tmp/tmpo3lak8m3/friendsofstrandseq-mosaicatcher-pipeline-2b6921d/workflow/rules/count.smk":  Formatted content is different from original
[DEBUG] 
[DEBUG] 
[DEBUG] 
[DEBUG] 
[DEBUG] 
<unknown>:2: SyntaxWarning: invalid escape sequence '\d'
<unknown>:1: SyntaxWarning: invalid escape sequence '\d'
[DEBUG] 
[DEBUG] 
[DEBUG] 
[DEBUG] In file "/tmp/tmpo3lak8m3/friendsofstrandseq-mosaicatcher-pipeline-2b6921d/workflow/rules/aggregate_fct.smk":  Formatted content is different from original
[DEBUG] 
[ERROR] In file "/tmp/tmpo3lak8m3/friendsofstrandseq-mosaicatcher-pipeline-2b6921d/workflow/rules/external_data_v8.smk":  InvalidPython: Black error:

… (truncated)