snakePipes: facilitating flexible, scalable and integrative epigenomic analysis

Abstract

Summary: Due to the rapidly increasing scale and diversity of epigenomic data, modular and scalable analysis workflows are of wide interest. Here we present snakePipes, a workflow package for processing and downstream analysis of data from common epigenomic assays: ChIP-seq, RNA-seq, Bisulfite-seq, ATAC-seq, Hi-C and single-cell RNA-seq. snakePipes enables users to assemble variants of each workflow and to easily install and upgrade the underlying tools, via its simple command-line wrappers and yaml files.

Availability and implementation: snakePipes can be installed via conda: `conda install -c mpi-ie -c bioconda -c conda-forge snakePipes'. Source code (https://github.com/maxplanck-ie/snakepipes) and documentation (https://snakepipes.readthedocs.io/en/latest/) are available online.

Supplementary information: Supplementary data are available at Bioinformatics online.

Fig. 1.

Setup, execution and results from snakePipes. (a) All configurable parameters for snakepipes are defined as YAML files during setup. However, most parameters can be overwritten during execution by providing another YAML file, adding flexibility to the analysis. (b) Output of HiC (track 1), WGBS (track 2), ATAC-seq (track 3), allele-specific ChIP-seq (tracks 3–7) and RNA-seq (tracks 8–9) workflows, plotted using pyGenomeTracks (Ramírez et al., 2018)