MAnorm2 for quantitatively comparing groups of ChIP-seq samples

Shiqi Tu, Mushan Li, Haojie Chen, Fengxiang Tan, Jian Xu, David J. Waxman, Yijing Zhang, Zhen Shao

Research output: Contribution to journalArticlepeer-review

27 Scopus citations

Abstract

Eukaryotic gene transcription is regulated by a large cohort of chromatin-associated proteins, and inferring their differential binding sites between cellular contexts requires a rigorous comparison of the corresponding ChIP-seq data. We present MAnorm2, a new computational tool for quantitatively comparing groups of ChIP-seq samples. MAnorm2 uses a hierarchical strategy for normalization of ChIP-seq data and assesses within-group variability of ChIP-seq signals based on an empirical Bayes framework. In this framework, MAnorm2 allows for abundant differential ChIP-seq signals between groups of samples as well as very different global within-group variability between groups. Using a number of real ChIP-seq data sets, we observed that MAnorm2 clearly outperformed existing tools for differential ChIP-seq analysis, especially when the groups of samples being compared had distinct global within-group variability.

Original languageEnglish (US)
Pages (from-to)131-145
Number of pages15
JournalGenome Research
Volume31
Issue number1
DOIs
StatePublished - Jan 2021

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)

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