GemBS: High throughput processing for DNA methylation data from bisulfite sequencing

Angelika Merkel, Marcos Fernández-Callejo, Eloi Casals, Santiago Marco-Sola, Ronald Schuyler, Ivo G. Gut, Simon C. Heath

Research output: Contribution to journalArticleResearch

10 Citations (Scopus)

Abstract

© The Author(s) 2018. Motivation DNA methylation is essential for normal embryogenesis and development in mammals and can be captured at single base pair resolution by whole genome bisulfite sequencing (WGBS). Current available analysis tools are becoming rapidly outdated as they lack sensible functionality and efficiency to handle large amounts of data now commonly created. Results We developed gemBS, a fast high-throughput bioinformatics pipeline specifically designed for large scale BS-Seq analysis that combines a high performance BS-mapper (GEM3) and a variant caller specifically for BS-Seq data (BScall). gemBS provides genotype information and methylation estimates for all genomic cytosines in different contexts (CpG and non-CpG) and a set of quality reports for comprehensive and reproducible analysis. gemBS is highly modular and can be easily automated, while producing robust and accurate results.
Original languageEnglish
Pages (from-to)737-742
JournalBioinformatics
Volume35
DOIs
Publication statusPublished - 1 Mar 2019

Fingerprint Dive into the research topics of 'GemBS: High throughput processing for DNA methylation data from bisulfite sequencing'. Together they form a unique fingerprint.

Cite this