methylKit: a comprehensive R package for the analysis of genome-wide DNA methylation profiles

methylKit: комплексный R-пакет для анализа полногеномных профилей метилирования ДНК
María E. Figueroa, Ari Melnick, Altuna Akalin, Christopher E. Mason, Francine E. Garrett-Bakelman, Sheng Li, Matthías Kormáksson
2012-10-03

DNA methylationbreast cancerdifferential methylation analysishydroxymethylation sequencingmethylKit
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, that rapidly analyzes genome-wide cytosine epigenetic profiles from high-throughput methylation and hydroxymethylation sequencing experiments. methylKit includes functions for clustering, sample quality visualization, differential methylation analysis and annotation features, thus automating and simplifying many of the steps for discerning statistically significant bases or regions of DNA methylation. Finally, we demonstrate methylKit on breast cancer data, in which we find statistically significant regions of differential methylation and stratify tumor subtypes. methylKit is available at http://code.google.com/p/methylkit.
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Application to breast cancer data identified significant differentially methylated regions and enabled stratification of tumor subtypes.
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The package integrates clustering, sample-quality visualization, differential methylation testing, and genomic annotation in a unified workflow.
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methylKit automates identification of statistically significant methylated bases and genomic regions from high-throughput sequencing data.
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methylKit is an R package designed for rapid genome-wide analysis of cytosine methylation and hydroxymethylation sequencing profiles.

genome-wide cytosine DNA methylation and hydroxymethylation profiles from high-throughput sequencing experiments, including breast cancer samples

statistically significant differential methylation regions and bases, including their clustering, quality patterns, annotation, and association with breast cancer tumor subtypes

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2012-10-03
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Authors
María E. Figueroa
Ari Melnick
Altuna Akalin
Christopher E. Mason
Francine E. Garrett-Bakelman
Sheng Li
Matthías Kormáksson
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