Snakemake

Table of contents

• What is Snakemake?

What is Snakemake?

Snakemake is a workflow management system that enables scalable and reproducible data analysis workflows. It was created by Johannes Köster and is particularly popular in bioinformatics, computational biology, and data science. Snakemake uses a Python-based domain-specific language (DSL) to define workflows as rules, making them readable, maintainable, and reproducible.

Snakemake is particularly well-suited for:

• Bioinformatics: Genomics pipelines, sequence analysis, variant calling
• Data Science: Reproducible data analysis workflows, statistical pipelines
• Scientific Computing: Computational research workflows, data processing
• HPC Workflows: Workflows that need to run on high-performance computing clusters

Key features of Snakemake include:

• Python-based: Workflows are defined using Python syntax with rule-based DSL
• Reproducibility: Built-in support for containers (Docker, Singularity/Apptainer) and Conda environments
• Automatic parallelization: Automatically parallelizes workflow execution based on available resources
• Portability: Workflows can run on local machines, HPC clusters, and cloud platforms
• Dry-run capability: Can preview workflow execution without running it
• Rich ecosystem: Large collection of bioinformatics workflows and integrations