A novel algorithm for calling mRNA m6A peaks by modeling biological variances in MeRIP-seq data.

ABSTRACT:

Motivation

N(6)-methyl-adenosine (m(6)A) is the most prevalent mRNA methylation but precise prediction of its mRNA location is important for understanding its function. A recent sequencing technology, known as Methylated RNA Immunoprecipitation Sequencing technology (MeRIP-seq), has been developed for transcriptome-wide profiling of m(6)A. We previously developed a peak calling algorithm called exomePeak. However, exomePeak over-simplifies data characteristics and ignores the reads' variances among replicates or reads dependency across a site region. To further improve the performance, new model is needed to address these important issues of MeRIP-seq data.

Results

We propose a novel, graphical model-based peak calling method, MeTPeak, for transcriptome-wide detection of m(6

SUBMITTER: Cui X 

PROVIDER: S-EPMC4908365 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature