The Snakemake workflow management system is a tool to create reproducible and scalable data analyses. Snakemake is highly popular, with on average more than 7 new citations per week in 2021, and almost 400k downloads. Workflows are described via a human readable, Python based language. They can be seamlessly scaled to server, cluster, grid and cloud environments without the need to modify the workflow definition. Finally, Snakemake workflows can entail a description of required software, which will be automatically deployed to any execution environment.
Homepage: https://snakemake.github.io
Copyright (c) 2012-2022 Johannes Köster [email protected] (see LICENSE)
This repo (EdinburghGenomics/snakemake) contains patches to make Snakemake DAG building significantly faster on Lustre
filesystems where stat calls are relatively slow. It was primarily made to support the data pipelines found
elsewhere under the EdinburghGenomics GitHub area.
I'd hope to re-work some or all of these as enhancements in upstream, but for now they actually break features of Snakemake (albeit ones that I don't use!) so I can't just make a PR from this fork.