1. snakePipes enable flexible, scalable and integrative epigenomic analysis
- Author
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Bhardwaj, Michael Rauer, Katarzyna Sikora, Thomas Manke, Steffen Heyne, Andreas S. Richter, Fabian Kilpert, Devon Ryan, and Leily Rabbani
- Subjects
Flexibility (engineering) ,Downstream (software development) ,Computer science ,Process (engineering) ,Scale (chemistry) ,Scalability ,Data analysis ,Genomics ,Data science ,Epigenomics - Abstract
The scale and diversity of epigenomics data has been rapidly increasing and ever more studies now present analyses of data from multiple epigenomic techniques. Performing such integrative analysis is time-consuming, especially for exploratory research, since there are currently no pipelines available that allow fast processing of datasets from multiple epigenomic assays while also allow for flexibility in running or upgrading the workflows. Here we present a solution to this problem: snakePipes, which can process and perform downstream analysis of data from all common epigenomic techniques (ChIP-seq, RNA-seq, Bisulfite-seq, ATAC-seq, Hi-C and single-cell RNA-seq) in a single package. We demonstrate how snakePipes can simplify integrative analysis by reproducing and extending the results from a recently published large-scale epigenomics study with a few simple commands. snakePipes are available under an open-source license at https://github.com/maxplanck-ie/snakepipes.
- Published
- 2018