RT Journal Article
SR Electronic
T1 Strategies for analyzing bisulfite sequencing data
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 109512
DO 10.1101/109512
A1 Katarzyna Wreczycka
A1 Alexer Gosdschan
A1 Dilmurat Yusuf
A1 Björn Grüning
A1 Yassen Assenov
A1 Altuna Akalin
YR 2017
UL http://biorxiv.org/content/early/2017/02/17/109512.abstract
AB DNA methylation is one of the main epigenetic modifications in the eukaryotic genome and has been shown to play a role in cell-type specific regulation of gene expression, and therefore cell-type identity. Bisulfite sequencing is the gold-standard for measuring methylation over the genomes of interest. Here, we review several techniques used for the analysis of high-throughput bisulfite sequencing. We introduce specialized short-read alignment techniques as well as pre/post-alignment quality check methods to ensure data quality. Furthermore, we discuss subsequent analysis steps after alignment. We introduce various differential methylation methods and compare their performance using simulated and real bisulfite-sequencing datasets. We also discuss the methods used to segment methylomes in order to pinpoint regulatory regions. We introduce annotation methods that can be used further classification of regions returned by segmentation or differential methylation methods. Lastly, we review software packages that implement strategies to efficiently deal with large bisulfite sequencing datasets locally and also discuss online analysis workflows that do not require any prior programming skills. The analysis strategies described in this review will guide researchers at any level to the best practices of bisulfite-sequencing analysis.