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

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/.

YY1TargetDB: an integral information resource for Yin Yang 1 target loci.

Yin Yang 1 (YY1), a ubiquitously expressed transcription factor, plays a critical role in regulating cell development, differentiation, cellular proliferation and tumorigenesis. Previous studies identified many YY1-regulated target genes in both human and mouse. Emerging global mapping by Chromatin ImmnoPrecipitation (ChIP)-based high-throughput experiments indicate that YY1 binds to a vast number of loci genome-wide. However, the information is widely scattered in many disparate poorly cross-indexed literatures; a large portion was only published recently by the ENCODE consortium with limited annotation. A centralized database, which annotates and organizes YY1-binding loci and target motifs in a systematic way with easy access, will be valuable resources for the research community. We therefore implemented a web-based YY1 Target loci Database (YY1TargetDB). This database contains YY1-binding loci (binding peaks) from ChIP-seq and ChIP-on-chip experiments, computationally predicated YY1 and cofactor motifs within each locus. It also collects the experimentally verified YY1-binding motifs from individual researchers. The current version of YY1TargetDB contains 92 314 binding loci identified by ChIP-based experiments; 157 200 YY1-binding motifs in which 42 are experimentally verified and 157 158 are computationally predicted; and 130 759 binding motifs for 47 cofactors. Database URL: http://www.myogenesisdb.org/YY1TargetDB.