HEPeak: an HMM-based exome peak-finding package for RNA epigenome sequencing data

• Published in: BMC genomics Vol. 16; no. Suppl 4; p. S2
• Main Authors: Cui, Xiaodong, Meng, Jia, Rao, Manjeet K, Chen, Yidong, Huang, Yufei
• Format: Journal Article
• Language: English
• Published: London BioMed Central 21.04.2015
• Subjects: Algorithms; Animal Genetics and Genomics; Animals; Biomedical and Life Sciences; Cells, Cultured; Epigenomics - methods; Exome; HEK293 Cells; Humans; Life Sciences; Markov Chains; Mesencephalon - cytology; Methylation; Mice; Microarrays; Microbial Genetics and Genomics; Plant Genetics and Genomics; Proteomics; RNA Processing, Post-Transcriptional; RNA, Messenger - chemistry; RNA, Messenger - metabolism; Sequence Analysis, RNA - methods; Read Count; Peak Region; Hide Markov Model; Methylation Status; Receiver Operating Characteristic
• ISSN: 1471-2164; 1471-2164
• DOI: 10.1186/1471-2164-16-S4-S2

Background Methylated RNA Immunoprecipatation combined with RNA sequencing (MeRIP-seq) is revolutionizing the de novo study of RNA epigenomics at a higher resolution. However, this new technology poses unique bioinformatics problems that call for novel and sophisticated statistical computational solutions, aiming at identifying and characterizing transcriptome-wide methyltranscriptome. Results We developed HEP, a Hidden Markov Model (HMM)-based Exome Peak-finding algorithm for predicting transcriptome methylation sites using MeRIP-seq data. In contrast to exomePeak, our previously developed MeRIP-seq peak calling algorithm, HEPeak models the correlation between continuous bins in an m 6 A peak region and it is a model-based approach, which admits rigorous statistical inference. HEPeak was evaluated on a simulated MeRIP-seq dataset and achieved higher sensitivity and specificity than exomePeak. HEPeak was also applied to real MeRIP-seq datasets from human HEK293T cell line and mouse midbrain cells and was shown to be able to recapitulate known m 6 A distribution in transcripts and identify novel m 6 A sites in long non-coding RNAs. Conclusions In this paper, a novel HMM-based peak calling algorithm, HEPeak, was developed for peak calling for MeRIP-seq data. HEPeak is written in R and is publicly available.