Comparing five statistical methods of differential methylation identification using bisulfite sequencing data

Statistical Applications in Genetics and Molecular Biology
Xiaoqing Yu, Shuying Sun

Abstract

We are presenting a comprehensive comparative analysis of five differential methylation (DM) identification methods: methylKit, BSmooth, BiSeq, HMM-DM, and HMM-Fisher, which are developed for bisulfite sequencing (BS) data. We summarize the features of these methods from several analytical aspects and compare their performances using both simulated and real BS datasets. Our comparison results are summarized below. First, parameter settings may largely affect the accuracy of DM identification. Different from default settings, modified parameter settings yield higher sensitivity and/or lower false positive rates. Second, all five methods show more accurate results when identifying simulated DM regions that are long and have small within-group variation, but they have low concordance, probably due to the different approaches they have used for DM identification. Third, HMM-DM and HMM-Fisher yield relatively higher sensitivity and lower false positive rates than others, especially in DM regions with large variation. Finally, we have found that among the three methods that involve methylation estimation (methylKit, BSmooth, and BiSeq), BiSeq can best present raw methylation signals. Therefore, based on these results, we suggest that...Continue Reading

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Citations

May 21, 2016·Briefings in Functional Genomics·Fayou WangXiaoqi Zheng
Mar 24, 2017·Briefings in Bioinformatics·Adib ShafiSorin Draghici
Mar 17, 2020·Journal of Computational Biology : a Journal of Computational Molecular Cell Biology·Boying Gong, Elizabeth Purdom
Feb 9, 2016·Statistical Applications in Genetics and Molecular Biology·Shuying Sun, Xiaoqing Yu
Feb 18, 2016·Statistical Applications in Genetics and Molecular Biology·Xiaoqing Yu, Shuying Sun
Jul 26, 2017·PeerJ·Gunjune KimJames H Westwood
Jul 10, 2021·Epigenomics·Ryu MinegishiSeiichi Mori
Aug 13, 2021·Bioinformatics·Oleksii NikolaienkoStian Knappskog

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Methods Mentioned

BETA
methylation sequencing
RRBS
WGBS
methylation profiling

Software Mentioned

eDMR
BRAT
BiSeq
MethylSig
QDMR
HMM
Integrated Genome Viewer
DM
BEAT
MPs

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