PLoS ONE (Jan 2014)

Methy-Pipe: an integrated bioinformatics pipeline for whole genome bisulfite sequencing data analysis.

  • Peiyong Jiang,
  • Kun Sun,
  • Fiona M F Lun,
  • Andy M Guo,
  • Huating Wang,
  • K C Allen Chan,
  • Rossa W K Chiu,
  • Y M Dennis Lo,
  • Hao Sun

DOI
https://doi.org/10.1371/journal.pone.0100360
Journal volume & issue
Vol. 9, no. 6
p. e100360

Abstract

Read online

DNA methylation, one of the most important epigenetic modifications, plays a crucial role in various biological processes. The level of DNA methylation can be measured using whole-genome bisulfite sequencing at single base resolution. However, until now, there is a paucity of publicly available software for carrying out integrated methylation data analysis. In this study, we implemented Methy-Pipe, which not only fulfills the core data analysis requirements (e.g. sequence alignment, differential methylation analysis, etc.) but also provides useful tools for methylation data annotation and visualization. Specifically, it uses Burrow-Wheeler Transform (BWT) algorithm to directly align bisulfite sequencing reads to a reference genome and implements a novel sliding window based approach with statistical methods for the identification of differentially methylated regions (DMRs). The capability of processing data parallelly allows it to outperform a number of other bisulfite alignment software packages. To demonstrate its utility and performance, we applied it to both real and simulated bisulfite sequencing datasets. The results indicate that Methy-Pipe can accurately estimate methylation densities, identify DMRs and provide a variety of utility programs for downstream methylation data analysis. In summary, Methy-Pipe is a useful pipeline that can process whole genome bisulfite sequencing data in an efficient, accurate, and user-friendly manner. Software and test dataset are available at http://sunlab.lihs.cuhk.edu.hk/methy-pipe/.