BMC Bioinformatics (Apr 2021)

A flexible ChIP-sequencing simulation toolkit

  • An Zheng,
  • Michael Lamkin,
  • Yutong Qiu,
  • Kevin Ren,
  • Alon Goren,
  • Melissa Gymrek

DOI
https://doi.org/10.1186/s12859-021-04097-5
Journal volume & issue
Vol. 22, no. 1
pp. 1 – 10

Abstract

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Abstract Background A major challenge in evaluating quantitative ChIP-seq analyses, such as peak calling and differential binding, is a lack of reliable ground truth data. Accurate simulation of ChIP-seq data can mitigate this challenge, but existing frameworks are either too cumbersome to apply genome-wide or unable to model a number of important experimental conditions in ChIP-seq. Results We present ChIPs, a toolkit for rapidly simulating ChIP-seq data using statistical models of key experimental steps. We demonstrate how ChIPs can be used for a range of applications, including benchmarking analysis tools and evaluating the impact of various experimental parameters. ChIPs is implemented as a standalone command-line program written in C++ and is available from https://github.com/gymreklab/chips . Conclusions ChIPs is an efficient ChIP-seq simulation framework that generates realistic datasets over a flexible range of experimental conditions. It can serve as an important component in various ChIP-seq analyses where ground truth data are needed.

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