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

HEPeak: an HMM-based exome peak-finding package for RNA epigenome sequencing data.
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DOI:
10.1186/1471-2164-16-s4-s2
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发表时间:
2015
期刊:
影响因子:
4.4
通讯作者:
Huang Y
Huang Y
中科院分区:
生物学2区
文献类型:
--
作者:
Cui X;Meng J;Rao MK;Chen Y;Huang Y

文献摘要

被引文献

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甲基化RNA免疫沉淀结合RNA测序(MeRIP-seq)正在以更高的分辨率彻底改变RNA表观基因组学的从头研究。然而,这项新技术带来了独特的生物信息学问题,需要新颖而复杂的统计计算解决方案,旨在识别和表征转录组范围内的甲基转录组。我们开发了HEP,这是一种基于隐马尔可夫模型(HMM)的外显子组峰值发现算法,用于使用MeRIP-seq数据预测转录组甲基化位点。与exomePeak(我们先前开发的MeRIP-seq峰调用算法)相比,HEPeak对m6 A峰区域中的连续箱之间的相关性进行建模,并且它是一种基于模型的方法,其允许严格的统计推断。在模拟的MeRIP-seq数据集上评估HEPeak,并且实现了比exomePeak更高的灵敏度和特异性。HEPeak还应用于来自人HEK 293 T细胞系和小鼠中脑细胞的真实的MeRIP-seq数据集,并且显示能够概括转录物中已知的m6 A分布并鉴定长非编码RNA中的新m6 A位点。本文提出了一种基于隐马尔可夫模型的MeRIP-seq数据峰识别算法HEPeak。HEPeak是用R语言编写的,并且是公开可用的。
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. 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 m6A 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 m6A distribution in transcripts and identify novel m6A sites in long non-coding RNAs. 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.