methylSig: A Whole-Genome DNA Methylation Analysis Pipeline

• Activity Number: 248
• Type: Contributed
• Date/Time: Monday, August 4, 2014 : 2:00 PM to 3:50 PM
• Sponsor: Section on Statistical Computing
• Author(s): Yong Seok Park*+ and Maureen A. Sartor and Maria E. Figueroa and Laura S. Rosek
• Companies: University of Pittsburgh and University of Michigan and University of Michigan and University of Michigan
• Keywords: DNA methylation ; epigenetic ; Beta-binomial distribution ; Cancer ; CpG island ; Bisulfite treatment

Abstract

DNA methylation plays critical roles in gene regulation and cellular specification without altering DNA sequences. The wide application of reduced representation bisulfite sequencing(RRBS) and whole genome bisulfite sequencing opens the door to study DNA methylation at single CpG site resolution. One challenging question is how best to test for significant methylation differences between groups of biological samples in order to minimize false positive findings.

We present a statistical analysis package, methylSig, to analyze genome-wide methylation differences between samples from different treatment of disease groups. MethylSig takes into account both the read coverage and biological variation by utilizing a beta-binomial distribution across biological samples for the same CpG site or region to identify relevant differences in CpG methylation. It can also incorporate local information to improve variance estimation for experiments with small sample size. A permutation study based on data from enhanced RRBS samples shows that methylSig maintains a well-calibrated type-I error.

MethylSig is available as an R package at http://sartorlab.ccmb.med.umich.edu/software.