Journal
BIOINFORMATICS
Volume 34, Issue 16, Pages 2715-2723Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/bty174
Keywords
-
Categories
Funding
- National Key R&D program of China [2016YFC0902700, 2016YFA0501800]
- National Natural Science Foundation of China [31401125, 81472420, 81572256, 81772766, 81372514]
- Fundamental Research Funds for the Central Universities
- 1000 talent Plan of China
- American Heart Association [15SFRN23910002]
Ask authors/readers for more resources
Motivation: The rapid development of next-generation sequencing technology provides an opportunity to study genome-wide DNA methylation at single-base resolution. However, depletion of unmethylated cytosines brings challenges for aligning bisulfite-converted sequencing reads to a large reference. Software tools for aligning methylation reads have not yet been comprehensively evaluated, especially for the widely used reduced representation bisulfite sequencing (RRBS) that involves enrichment for CpG islands (CGIs). Results: We specially developed a simulator, RRBSsim, for benchmarking analysis of RRBS data. We performed extensive comparison of seven mapping algorithms for methylation analysis in both real and simulated RRBS data. Eighteen lung tumors and matched adjacent tissues were sequenced by the RRBS protocols. Our empirical evaluation found that methylation results were less consistent between software tools for CpG sites with low sequencing depth, medium methylation level, on CGI shores or gene body. These observations were further confirmed by simulations that indicated software tools generally had lower recall of detecting these vulnerable CpG sites and lower precision of estimating methylation levels in these CpG sites. Among the software tools tested, bwa-meth and BS-Seeker2 (bowtie2) are currently our preferred aligners for RRBS data in terms of recall, precision and speed. Existing aligners cannot efficiently handle moderately methylated CpG sites and those CpG sites on CGI shores or gene body. Interpretation of methylation results from these vulnerable CpG sites should be treated with caution. Our study reveals several important features inherent in methylation data, and RRBSsim provides guidance to advance sequence-based methylation data analysis and methodological development. Availability and implementation: RRBSsim is a simulator for benchmarking analysis of RRBS data and its source code is available at https://github.com/xwBio/RRBSsim or https://github.com/xwBio/Docker-RRBSsim. Contact: yanlu76@zju.edu.cn or pyliu@zju.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available