A flexible ChIP-sequencing simulation toolkit
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12859_2021_Article_4097.pdf
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Author(s)
Zheng, An
Lamkin, Michael
Qiu, Yutong
Ren, Kevin
Goren, Alon
Gymrek, Melissa
Date Issued
April 20, 2021
Publisher
BioMed Central
Citation
BMC Bioinformatics. 2021 Apr 20;22(1):201
Version
Final published version
Abstract
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.
MIT Department
Massachusetts Institute of Technology. Department of Mathematics
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1186/s12859-021-04097-5
