snakePipes: facilitating flexible, scalable and integrative epigenomic analysis

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  • Vivek Bhardwaj
    Max Planck Institute of Immunobiology and Epigenetics , 79108 Freiburg, Germany
  • Steffen Heyne
    Max Planck Institute of Immunobiology and Epigenetics , 79108 Freiburg, Germany
  • Katarzyna Sikora
    Max Planck Institute of Immunobiology and Epigenetics , 79108 Freiburg, Germany
  • Leily Rabbani
    Max Planck Institute of Immunobiology and Epigenetics , 79108 Freiburg, Germany
  • Michael Rauer
    Max Planck Institute of Immunobiology and Epigenetics , 79108 Freiburg, Germany
  • Fabian Kilpert
    Institutes of Neurogenetics & Cardiogenetics, University of Lübeck , 23562 Lübeck, Germany
  • Andreas S Richter
    Genedata AG , 4053 Basel, Switzerland
  • Devon P Ryan
    Max Planck Institute of Immunobiology and Epigenetics , 79108 Freiburg, Germany
  • Thomas Manke
    Max Planck Institute of Immunobiology and Epigenetics , 79108 Freiburg, Germany
  • Bonnie Berger
    editor

Abstract

<jats:title>Abstract</jats:title> <jats:sec> <jats:title>Summary</jats:title> <jats:p>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.</jats:p> </jats:sec> <jats:sec> <jats:title>Availability and implementation</jats:title> <jats:p>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.</jats:p> </jats:sec> <jats:sec> <jats:title>Supplementary information</jats:title> <jats:p>Supplementary data are available at Bioinformatics online.</jats:p> </jats:sec>

Journal

  • Bioinformatics

    Bioinformatics 35 (22), 4757-4759, 2019-05-27

    Oxford University Press (OUP)

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