| name | snakemake |
| description | Snakemake — Python-based workflow management for reproducible bioinformatics (rules, conda/container integration, cluster execution). Use when encoding shotgun metagenomics DAGs as Snakefiles or adopting community metagenomics snakemake pipelines. Upstream: https://github.com/snakemake/snakemake. Route via research-analysis / metagenomics-workflow / setup. Alternative: nextflow.
|
| license | MIT |
| category | utilities |
| tags | ["Snakemake","workflow","reproducibility","pipeline","conda","HPC"] |
| upstream | https://github.com/snakemake/snakemake |
| stage | utilities |
Snakemake
Upstream: snakemake/snakemake ·
Docs: https://snakemake.readthedocs.io/
Citation
Mölder, F. et al. Sustainable data analysis with Snakemake.
F1000Res. 10, 33 (2021). https://doi.org/10.12688/f1000research.29032.2
Original: Köster, J. & Rahmann, S. Snakemake—a scalable bioinformatics workflow
engine. Bioinformatics 28, 2520–2522 (2012).
https://doi.org/10.1093/bioinformatics/bts480
See also docs/references.md.
Analytical thinking
Snakemake maps well to rule-based metagenomics DAGs (QC → assembly → … →
multiqc / tables for research-analysis). Use conda/mamba or containers per
rule; pin Snakemake major version and environment YAML hashes. Prefer dry-run
(-n) before cluster submit.
How to run
snakemake -j 16 --use-conda
Decision tree
Workflow manager?
├─ Snakemake / conda-centric → snakemake
├─ Nextflow / nf-core → nextflow
└─ Manual stages → metagenomics-workflow + setup
Related skills
nextflow · setup · metagenomics-workflow · research-analysis ·
tool-selection · multiqc
