Predicting genome-wide DNA methylation using methylation marks, genomic position, and DNA regulatory elements.

ABSTRACT:

Background

Recent assays for individual-specific genome-wide DNA methylation profiles have enabled epigenome-wide association studies to identify specific CpG sites associated with a phenotype. Computational prediction of CpG site-specific methylation levels is critical to enable genome-wide analyses, but current approaches tackle average methylation within a locus and are often limited to specific genomic regions.

Results

We characterize genome-wide DNA methylation patterns, and show that correlation among CpG sites decays rapidly, making predictions solely based on neighboring sites challenging. We built a random forest classifier to predict methylation levels at CpG site resolution using features including neighboring CpG site methylation levels and genomic distance, co-l

SUBMITTER: Zhang W 

PROVIDER: S-EPMC4389802 | biostudies-literature | 2015 Jan

REPOSITORIES: biostudies-literature