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v2026.1714 entries · CC-BY 4.0
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Snakemake (concept)

A Python-based workflow management system that expresses computational pipelines as rules with explicit inputs, outputs, and shell or script bodies, and infers a directed acyclic graph (DAG) of jobs from those rules.

ByCASRAI Editorial Board
· Last updated 21 May 2026

Examples

Worked examples

  • Is an instance

    A genomics paper distributing its analysis as a Snakemake workflow with a `--use-conda` flag.

  • Is an instance

    A Snakemake pipeline executed locally for development and on Slurm for production.

Counter-examples

Looks similar, but isn't

  • Not an instance

    A pure CWL pipeline (different language).

  • Not an instance

    A bash script with no DAG inference.

Editorial commentary

Snakemake is widely used in bioinformatics for its declarative-yet-familiar Python syntax. It integrates with conda environments and container images, supports cluster and cloud execution, and produces provenance metadata. The 'concept' qualifier marks this entry as covering the methodological pattern rather than tracking implementation releases.

References

  • Koster, Rahmann, 'Snakemake — a scalable bioinformatics workflow engine' (Bioinformatics, 2012); Molder et al., 'Sustainable data analysis with Snakemake' (F1000Research, 2021).

Also known as

Snakemake

Machine-readable encodings

Use in your systems

JATS XML <role> element
xml
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Schema.org DefinedTerm (JSON-LD)
json
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