KonstantinBurkin/cbai
None
Overview
Topics:
Latest release: None, Last update: 2022-07-13
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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/KonstantinBurkin/cbai . --tag None
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
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.
Sample and unit sheet
- Add samples to
config/samples.tsv
. Only the columnsample
is mandatory, but any additional columns can be added. - For each sample, add one or more sequencing units (runs, lanes or replicates) to the unit sheet
config/units.tsv
. For each unit, define platform, and either one (columnfq1
) or two (columnsfq1
,fq2
) FASTQ files (these can point to anywhere in your system).
The pipeline will jointly call all samples that are defined, following the GATK best practices.
Linting and formatting
Linting results
Workflow defines that rule get_genome is eligible for caching between workflows (use the --cache argument to enable this).
Workflow defines that rule genome_faidx is eligible for caching between workflows (use the --cache argument to enable this).
Workflow defines that rule genome_dict is eligible for caching between workflows (use the --cache argument to enable this).
Workflow defines that rule get_known_variation is eligible for caching between workflows (use the --cache argument to enable this).
Workflow defines that rule remove_iupac_codes is eligible for caching between workflows (use the --cache argument to enable this).
Workflow defines that rule tabix_known_variants is eligible for caching between workflows (use the --cache argument to enable this).
Workflow defines that rule bwa_index is eligible for caching between workflows (use the --cache argument to enable this).
Lints for rule minimap_index (line 217, /tmp/tmpec9g10io/workflow/rules/ref.smk):
* No log directive defined:
Without a log directive, all output will be printed to the terminal. In
distributed environments, this means that errors are harder to discover.
In local environments, output of concurrent jobs will be mixed and become
unreadable.
Also see:
https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#log-files
Lints for rule multiqc (line 50, /tmp/tmpec9g10io/workflow/rules/qc.smk):
* Migrate long run directives into scripts or notebooks:
Long run directives hamper workflow readability. Use the script or
notebook direcive instead. Note that the script or notebook directive does
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Formatting results
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PEP8 recommends block comments appear before what they describe
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[INFO] 5 file(s) would be changed 😬
[INFO] 4 file(s) would be left unchanged 🎉
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