- epiG: statistical inference and profiling of DNA methylation from whole-genome bisulfite sequencing data.
epiG: statistical inference and profiling of DNA methylation from whole-genome bisulfite sequencing data.
Genome biology (2017-02-23)
Martin Vincent, Kamilla Mundbjerg, Jakob Skou Pedersen, Gangning Liang, Peter A Jones, Torben Falck Ørntoft, Karina Dalsgaard Sørensen, Carsten Wiuf
PMID28222791
ABSTRACT
The study of epigenetic heterogeneity at the level of individual cells and in whole populations is the key to understanding cellular differentiation, organismal development, and the evolution of cancer. We develop a statistical method, epiG, to infer and differentiate between different epi-allelic haplotypes, annotated with CpG methylation status and DNA polymorphisms, from whole-genome bisulfite sequencing data, and nucleosome occupancy from NOMe-seq data. We demonstrate the capabilities of the method by inferring allele-specific methylation and nucleosome occupancy in cell lines, and colon and tumor samples, and by benchmarking the method against independent experimental data.