epic: find diffusely enriched domains in ChIP-Seq data

epic is a modern reimplementation of the extremely popular SICER algorithm for finding broad, diffusely enriched regions in ChIP-Seq data. epic focuses on speed, innovation and ease of use.

In addtion to the classic SICER algorithm, epic contains an array of tools to help you do differential analysis of ChIP-Seq data from multiple conditions.

Novel features

  • epic creates output files that allow you to leverage state-of-the-art statistical software to do rigorous differential analyses of experimental conditions
  • epic creates bigwigs and bed files that allow you to visualize and explore the results in genome browsers


epic contains a slew of improvements

  • Python 2.7 and 3+ compatible
  • much faster and multicore
  • easy to install and use; exists both in Bioconda and PyPI
  • accepts both single- and paired-end reads
  • can analyse multiple ChIP and input files at the same time (and even mix paired and single end files in the same analysis)
  • sensible defaults - only needs the files to analyse as command line args
  • effective genome size autoselected based on read length (autodetected) and genome
  • epic can compute the effective genome fraction for you, allowing you to analyze any genome for which you have a fasta file
  • (soon) metadata for all genomes in UCSC is available so you only need to give the genome name for the species you wish to analyse
  • accepts custom genomes and assemblies
  • automatically tested, which safely and easily allows contributions
  • continually used, updated and maintained by the author

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