Title |
Gene-set analysis is severely biased when applied to genome-wide methylation data
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Published in |
Bioinformatics, June 2013
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DOI | 10.1093/bioinformatics/btt311 |
Pubmed ID | |
Authors |
Paul Geeleher, Lori Hartnett, Laurance J. Egan, Aaron Golden, Raja Affendi Raja Ali, Cathal Seoighe |
Abstract |
DNA methylation is an epigenetic mark that can stably repress gene expression. Because of its biological and clinical significance, several methods have been developed to compare genome-wide patterns of methylation between groups of samples. The application of gene set analysis to identify relevant groups of genes that are enriched for differentially methylated genes is often a major component of the analysis of these data. This can be used, for example, to identify processes or pathways that are perturbed in disease development. We show that gene-set analysis, as it is typically applied to genome-wide methylation assays, is severely biased as a result of differences in the numbers of CpG sites associated with different classes of genes and gene promoters. |
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