TY - JOUR
T1 - MethylKit
T2 - a comprehensive R package for the analysis of genome-wide DNA methylation profiles
AU - Akalin, Altuna
AU - Kormaksson, Matthias
AU - Li, Sheng
AU - Garrett-Bakelman, Francine E.
AU - Figueroa, Maria E.
AU - Melnick, Ari
AU - Mason, Christopher E.
N1 - Funding Information:
We wish to acknowledge the invaluable contribution of the WCMC Epigenomics Core Facility. MEF is supported by the Leukemia & Lymphoma Society Special Fellow Award and a Doris Duke Clinical Scientist Development Award. FGB is supported by a Sass Foundation Judah Folkman Fellowship. AM is supported by an LLS SCOR grant (7132-08) and a Burroughs Wellcome Clinical Translational Scientist Award. AM and CEM are supported by a Starr Cancer Consortium grant (I4-A442). CEM is supported by the National Institutes of Health (I4-A411, I4-A442, and 1R01NS076465-01).
PY - 2012/10/3
Y1 - 2012/10/3
N2 - DNA methylation is a chemical modification of cytosine bases that is pivotal for gene regulation,cellular specification and cancer development. Here, we describe an R package, methylKit, thatrapidly analyzes genome-wide cytosine epigenetic profiles from high-throughput methylation andhydroxymethylation sequencing experiments. methylKit includes functions for clustering, samplequality visualization, differential methylation analysis and annotation features, thus automatingand simplifying many of the steps for discerning statistically significant bases or regions of DNAmethylation. Finally, we demonstrate methylKit on breast cancer data, in which we find statisticallysignificant regions of differential methylation and stratify tumor subtypes. methylKit is availableat http://code.google.com/p/methylkit.
AB - DNA methylation is a chemical modification of cytosine bases that is pivotal for gene regulation,cellular specification and cancer development. Here, we describe an R package, methylKit, thatrapidly analyzes genome-wide cytosine epigenetic profiles from high-throughput methylation andhydroxymethylation sequencing experiments. methylKit includes functions for clustering, samplequality visualization, differential methylation analysis and annotation features, thus automatingand simplifying many of the steps for discerning statistically significant bases or regions of DNAmethylation. Finally, we demonstrate methylKit on breast cancer data, in which we find statisticallysignificant regions of differential methylation and stratify tumor subtypes. methylKit is availableat http://code.google.com/p/methylkit.
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U2 - 10.1186/gb-2012-13-10-R87
DO - 10.1186/gb-2012-13-10-R87
M3 - Article
C2 - 23034086
AN - SCOPUS:84866860221
VL - 13
JO - Genome Biology
JF - Genome Biology
SN - 1465-6914
IS - 10
M1 - R87
ER -