GArcho44/snvs-annotation-pipeline
None
Overview
Latest release: None, Last update: 2025-11-06
Linting: linting: failed, Formatting: formatting: failed
Wrappers: bio/fastqc bio/multiqc
Deployment
Step 1: Install Snakemake and Snakedeploy
Snakemake and Snakedeploy are best installed via the Conda. It is recommended to install conda via Miniforge. Run
conda create -c conda-forge -c bioconda -c nodefaults --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
For other installation methods, refer to the Snakemake and Snakedeploy documentation.
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/GArcho44/snvs-annotation-pipeline . --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 using apptainer/singularity, use
snakemake --cores all --sdm apptainer
To run the workflow using a combination of conda and apptainer/singularity for software deployment, use
snakemake --cores all --sdm conda apptainer
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.
Workflow overview
This workflow is a best-practice workflow for <structure-aware annotation of microbial SNPs>.
The workflow is built using snakemake and consists of the following 3 main configurable modules:
A. Sequence-based functional annotation of SNPs & Genes B. retrieval of high-confidence structure models from AFDB and ESMatlas protein structure databases C. Measurement and prediction of structure-aware properties for protein residues affected from missense SNPs
Running the workflow
Input data
A) A variant calling file (.vcf) that follows the required format (see Experimental Design)
B) Species reference genome(s)
Parameters
This table lists all parameters that can be adjusted/modified to run the workflow.
parameter |
type |
details |
default |
|---|---|---|---|
species |
|||
species_id |
str |
species specific identifier, mandatory |
|
ref_genome |
|||
path |
str |
path to reference genome file |
|
conf_score |
|||
confidence_score |
num |
pLDDT confidence score filter |
80 |
Linting and formatting
Linting results
1WorkflowError in file "/tmp/tmp_6_fqpum/workflow/Snakefile", line 5:
2Workflow defines configfile ../config/config.yml but it is not present or accessible (full checked path: /tmp/config/config.yml).
Formatting results
1[DEBUG]
2[DEBUG] In file "/tmp/tmp_6_fqpum/workflow/Snakefile": Formatted content is different from original
3[DEBUG]
4[DEBUG]
5[INFO] 1 file(s) would be changed 😬
6[INFO] 2 file(s) would be left unchanged 🎉
7
8snakefmt version: 0.11.2