MethylSig

A whole genome DNA methylation analysis pipeline

Yongseok Park, Maria Figueroa, Laura S. Rozek, Maureen A. Sartor

Research output: Contribution to journalArticle

76 Citations (Scopus)

Abstract

Motivation: 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 (bis-seq) 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. Results: We present a statistical analysis package, methylSig, to analyse genome-wide methylation differences between samples from different treatments or disease groups. MethylSig takes into account both read coverage and biological variation by utilizing a beta-binomial approach across biological samples for a CpG site or region, and identifies relevant differences in CpG methylation. It can also incorporate local information to improve group methylation level and/or 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 when the number of samples is three or more per group. Our simulations show that methylSig has higher sensitivity compared with several alternative methods. The use of methylSig is illustrated with a comparison of different subtypes of acute leukemia and normal bone marrow samples.

Original languageEnglish (US)
Pages (from-to)2414-2422
Number of pages9
JournalBioinformatics
Volume30
Issue number17
DOIs
StatePublished - Sep 1 2014
Externally publishedYes

Fingerprint

Methylation
DNA Methylation
Genome
Pipelines
Genes
Sequencing
DNA sequences
Beta-binomial
Gene expression
Sample Size
Statistical methods
Bone
Leukemia
Variance Estimation
Gene Regulation
Type I error
Bone Marrow
Small Sample Size
Specifications
False Positive

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

Cite this

MethylSig : A whole genome DNA methylation analysis pipeline. / Park, Yongseok; Figueroa, Maria; Rozek, Laura S.; Sartor, Maureen A.

In: Bioinformatics, Vol. 30, No. 17, 01.09.2014, p. 2414-2422.

Research output: Contribution to journalArticle

Park, Yongseok ; Figueroa, Maria ; Rozek, Laura S. ; Sartor, Maureen A. / MethylSig : A whole genome DNA methylation analysis pipeline. In: Bioinformatics. 2014 ; Vol. 30, No. 17. pp. 2414-2422.
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