Format

Send to

Choose Destination
Bioinformatics. 2015 Jun 1;31(11):1839-41. doi: 10.1093/bioinformatics/btv020. Epub 2015 Jan 20.

MethylMix: an R package for identifying DNA methylation-driven genes.

Author information

1
Department of Medicine, Stanford Center for Biomedical Informatics, Stanford, CA 94305-5479, USA.

Abstract

DNA methylation is an important mechanism regulating gene transcription, and its role in carcinogenesis has been extensively studied. Hyper and hypomethylation of genes is an alternative mechanism to deregulate gene expression in a wide range of diseases. At the same time, high-throughput DNA methylation assays have been developed generating vast amounts of genome wide DNA methylation measurements. Yet, few tools exist that can formally identify hypo and hypermethylated genes that are predictive of transcription and thus functionally relevant for a particular disease. To accommodate this lack of tools, we developed MethylMix, an algorithm implemented in R to identify disease specific hyper and hypomethylated genes. MethylMix is based on a beta mixture model to identify methylation states and compares them with the normal DNA methylation state. MethylMix introduces a novel metric, the 'Differential Methylation value' or DM-value defined as the difference of a methylation state with the normal methylation state. Finally, matched gene expression data are used to identify, besides differential, transcriptionally predictive methylation states by focusing on methylation changes that effect gene expression.

AVAILABILITY AND IMPLEMENTATION:

MethylMix was implemented as an R package and is available in bioconductor.

PMID:
25609794
PMCID:
PMC4443673
DOI:
10.1093/bioinformatics/btv020
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Silverchair Information Systems Icon for PubMed Central
Loading ...
Support Center