single-cell-snakemake documentation

TLDR

The tool cellranger-snakemake is a Snakemake wrapper for 10x Cell Ranger workflows supporting GEX, ATAC, and ARC single-cell data processing.

Description

Reproducibility and scalability are essential components of contemporary FAIR (Findable, Accessible, Interoperable, and Reproducible) single-cell ‘omics data analysis, yet preprocessing steps lack workflow infrastructure needed to standardize large-scale and collaborative studies. 10x Genomics’ Cell Ranger is critical software for preprocessing raw single-cell ‘omics modalities, but executing it reproducibly across hundreds or thousands of samples remains cumbersome, error-prone, and computationally inefficient. We present cellranger-snakemake, a Snakemake workflow wrapper that automates, scales, and standardizes Cell Ranger preprocessing for Gene Expression (GEX), Chromatin accessibility (ATAC), and multiome (ARC) data. The workflow supports flexible input specifications, integrated logging, and portable configuration files, making it straightforward to deploy in high-performance computing or cloud environments. By combining Snakemake’s reproducible workflow management with Cell Ranger, cellranger-snakemake improves reproducibility, reduces user error, and accelerates downstream single-cell ‘omics.

Contents:

• Installation instructions
  • 1. Set up conda
  • 2. Clone the repository:
  • 3. Create and activate the Conda environment:
  • 4. Install cellranger-snakemake into the environment
  • 5. Cell Ranger Installation
• Quick Start
• Tutorial and test case for development for GEX, ATAC, and ARC workflow
  • 1. Launch the conda environment
  • 2. Explore the help menus
  • 3. Generate input files for test
  • 4. Input files
  • 5. Run a dry run
  • 6. Run the tool!
  • 7. Launching on HPC
• Development Guide
  • Key Concepts
  • Developer Workflow
  • Project Architecture
  • Development Workflow
  • Testing
  • Common Pitfalls
  • Building and Editing Documentation