A Bayesian framework to identify methylcytosines from high-throughput bisulfite sequencing data.

ABSTRACT: High-throughput bisulfite sequencing technologies have provided a comprehensive and well-fitted way to investigate DNA methylation at single-base resolution. However, there are substantial bioinformatic challenges to distinguish precisely methylcytosines from unconverted cytosines based on bisulfite sequencing data. The challenges arise, at least in part, from cell heterozygosis caused by multicellular sequencing and the still limited number of statistical methods that are available for methylcytosine calling based on bisulfite sequencing data. Here, we present an algorithm, termed Bycom, a new Bayesian model that can perform methylcytosine calling with high accuracy. Bycom considers cell heterozygosis along with sequencing errors and bisulfite conversion efficiency to improve calling accu

SUBMITTER: Xie Q 

PROVIDER: S-EPMC4177668 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature