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MobiDL DeepVariant

WDL workflow for short-read variant calling using deepvariant in capture-based panel sequencing.


📌 Overview

WDL workflow for short-read variant calling using DeepVariant. It is designed to be modular, reproducible, and optimized for use in clinical settings.


🛠️ Requirements

Software Dependencies

  • WDL (Workflow Description Language)
  • Cromwell (Workflow Execution Engine)
  • Apptainer (for containerized tools)

Apptainer images

This workflow is designed to be used on HPC cluster with apptainer images. You could install images from this repo : https://github.com/MobiDL/apptainer-recipes

Inputs

  • Sam/Bam/Cram file(s)
  • Reference genome (e.g., GRCh38)
  • Target regions (BED file for panel definition)

🚀 Quick Start

⚠️ For maximum compatibility across Cromwell and cluster backends, all input and output paths must be absolute paths.

1. Clone the Repository

git clone --recursive https://github.com/MobiDL/DeepVariant.git
cd DeepVariant

2. Backend Configuration

Before running the workflow, adapt the backend configuration to match your HPC environment.

Common parameters to review include:

  • queue
  • tmp_dir
  • root_dir
  • temporary-directory
  • root

These parameters are usually cluster-specific and may need to be adjusted depending on your scheduler and storage architecture.

3. Run the Test Dataset

A minimal test dataset is available in the tests directory.

Update the paths in tests/test.json, then run:

java cromwell run alignmentSR.wdl \
  -Dconfig.file=backends.conf/slurm_apptainer.conf \
  -i tests/test.json

3. Configure Inputs

Edit the inputs.json file to specify your input files and parameters:

{
  "DeepVariant.reads": "path/to/sample1.bam"
  "DeepVariant.reference": "path/to/reference.fa",
  "DeepVariant.target_regions": "path/to/targets.bed"
}

4. Run the Workflow

java cromwell run alignmentSR.wdl -Dconfig.file=backends.conf/slurm_apptainer.conf -i inputs.json

📂 Repository Structure

DeepVariant/
├── backends.conf/           # Backends sub-repository
├── modules/                 # Modules sub-repository
├── tests/                   # tests directory containing minimal dataset
├── DeepVariant.wdl          # Main workflow file
└── README.md                # This file

⚙️ Workflow Steps

deepvariant

📊 Outputs

  • VCF files: Variant Calling Format file(s)

🤝 Contributing

Contributions are welcome! Please open an issue or submit a pull request for any improvements or bug fixes.


🆘 Support

For any questions or issues, please open an issue in this repository or contact us.

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WDL workflow for short-read variant calling using DeepVariant

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