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 language | English (US) |
---|---|
Pages (from-to) | 131-145 |
Number of pages | 15 |
Journal | Genome Research |
Volume | 31 |
Issue number | 1 |
DOIs | |
State | Published - Jan 2021 |
ASJC Scopus subject areas
- Genetics
- Genetics(clinical)