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BioinformaticsGenome biology
Peer-reviewed journal article

RADAR: Differential analysis of MeRIP-seq data with a random effect model

Zijie Scott ZhangiD, Qi ZhangiD, Mark A. EckertiD, Allen C. ZhuiD, Agnieszka ChryplewicziD, Dario F. De JesusiD, Decheng ReniD, Rohit KulkarniiD, Ernst R. LengyeliD, Chuan HeiD, Mengjie CheniD

Abstract

Epitranscriptome profiling using MeRIP-seq is a powerful technique for in vivo functional studies of reversible RNA modifications. We develop RADAR, a comprehensive analytical tool for detecting differentially methylated loci in MeRIP-seq data. RADAR enables accurate identification of altered methylation sites by accommodating variability of pre-immunoprecipitation expression level and post-immunoprecipitation count using different strategies. In addition, it is compatible with complex study design when covariates need to be incorporated in the analysis. Through simulation and real datasets analyses, we show that RADAR leads to more accurate and reproducible differential methylation analysis results than alternatives, which is available at https://github.com/scottzijiezhang/RADAR.

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