As the most abundant internal RNA modification, N 6-methyladenosine (m6A) affects the fate of RNA through various mechanisms and regulates essential biological processes. In this study, we developed exomePeak2, a novel computational tool for the comprehensive analysis of the m6A epitranscriptome using data generated by Methylated RNA Immunoprecipitation Sequencing (MeRIP-seq), the most widely adopted method for transcriptome-wide profiling of m6A RNA methylation. With a novel statistical model that efficiently addresses the common GC content bias and the variable immunoprecipitation (IP) efficiency in MeRIP-seq data, exomePeak2 achieves state-of-the-art performance in m6A site detection (or peak calling) and differential methylation analysis compared to competing approaches. Additionally, exomePeak2 provides a number of critical functions for MeRIP-seq analysis, such as unraveling the dynamics of RNA methylation in an absolute sense, handling strand-specific libraries for clear discrimination of anti-sense transcripts, performing peak calling with or without a reference transcriptome, and motif-based methylation level quantification at near base-resolution. These capabilities enable more reliable and comprehensive epitranscriptome analysis of MeRIP-seq data. exomePeak2 is also applicable to techniques implementing similar working principles for other modifications, such as hMeRIP-seq for 5-hydroxymethylcytidine (hm5C) and acRIP-seq for N 4-acetylcytidine (ac4C). exomePeak2, together with a comprehensive MeRIP-seq analysis protocol, is freely available from GitHub: https://github.com/ZW-xjtlu/exomePeak2.
Zhou et al. (Tue,) studied this question.