Gene set enrichment analysis for genome-wide DNA methylation data
Abstract DNA methylation is one of the most commonly studied epigenetic marks, due to its role in disease and development. Illumina methylation arrays have been extensively used to measure methylation across the human genome. Methylation array analysis has primarily focused on preprocessing, normali...
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Online Access: | https://doi.org/10.1186/s13059-021-02388-x |
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doaj-8b21e2a9af45434f9a81cd00204941132021-06-13T11:54:30ZengBMCGenome Biology1474-760X2021-06-0122112610.1186/s13059-021-02388-xGene set enrichment analysis for genome-wide DNA methylation dataJovana Maksimovic0Alicia Oshlack1Belinda Phipson2Peter MacCallum Cancer CentrePeter MacCallum Cancer CentrePeter MacCallum Cancer CentreAbstract DNA methylation is one of the most commonly studied epigenetic marks, due to its role in disease and development. Illumina methylation arrays have been extensively used to measure methylation across the human genome. Methylation array analysis has primarily focused on preprocessing, normalization, and identification of differentially methylated CpGs and regions. GOmeth and GOregion are new methods for performing unbiased gene set testing following differential methylation analysis. Benchmarking analyses demonstrate GOmeth outperforms other approaches, and GOregion is the first method for gene set testing of differentially methylated regions. Both methods are publicly available in the missMethyl Bioconductor R package.https://doi.org/10.1186/s13059-021-02388-xDNA methylationGene set analysisDifferential methylationStatistical analysis |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jovana Maksimovic Alicia Oshlack Belinda Phipson |
spellingShingle |
Jovana Maksimovic Alicia Oshlack Belinda Phipson Gene set enrichment analysis for genome-wide DNA methylation data Genome Biology DNA methylation Gene set analysis Differential methylation Statistical analysis |
author_facet |
Jovana Maksimovic Alicia Oshlack Belinda Phipson |
author_sort |
Jovana Maksimovic |
title |
Gene set enrichment analysis for genome-wide DNA methylation data |
title_short |
Gene set enrichment analysis for genome-wide DNA methylation data |
title_full |
Gene set enrichment analysis for genome-wide DNA methylation data |
title_fullStr |
Gene set enrichment analysis for genome-wide DNA methylation data |
title_full_unstemmed |
Gene set enrichment analysis for genome-wide DNA methylation data |
title_sort |
gene set enrichment analysis for genome-wide dna methylation data |
publisher |
BMC |
series |
Genome Biology |
issn |
1474-760X |
publishDate |
2021-06-01 |
description |
Abstract DNA methylation is one of the most commonly studied epigenetic marks, due to its role in disease and development. Illumina methylation arrays have been extensively used to measure methylation across the human genome. Methylation array analysis has primarily focused on preprocessing, normalization, and identification of differentially methylated CpGs and regions. GOmeth and GOregion are new methods for performing unbiased gene set testing following differential methylation analysis. Benchmarking analyses demonstrate GOmeth outperforms other approaches, and GOregion is the first method for gene set testing of differentially methylated regions. Both methods are publicly available in the missMethyl Bioconductor R package. |
topic |
DNA methylation Gene set analysis Differential methylation Statistical analysis |
url |
https://doi.org/10.1186/s13059-021-02388-x |
work_keys_str_mv |
AT jovanamaksimovic genesetenrichmentanalysisforgenomewidednamethylationdata AT aliciaoshlack genesetenrichmentanalysisforgenomewidednamethylationdata AT belindaphipson genesetenrichmentanalysisforgenomewidednamethylationdata |
_version_ |
1721379369993109504 |