{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,5]],"date-time":"2026-02-05T11:58:23Z","timestamp":1770292703449,"version":"3.49.0"},"reference-count":29,"publisher":"Oxford University Press (OUP)","issue":"8","funder":[{"DOI":"10.13039\/100000066","name":"National Institute of Environmental Health Sciences","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000066","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,8,2]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Gene Set Enrichment Analysis (GSEA) is widely used to interpret DNA methylation data by associating differentially methylated sites with biological pathways. However, existing GSEA methods struggle with several challenges in methylation data, including probe dependency, probe number bias, and the complexity of gene-probe mapping. These limitations can lead to biased enrichment results, reduced statistical power, and computational inefficiencies.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>We introduce gsGene and gsPG, two novel GSEA methods specifically designed for DNA methylation data. gsGene aggregates association signals at gene level while correcting for probe dependency and probe number bias, enabling more biologically meaningful enrichment analysis. gsPG takes a different approach by conducting gene set enrichment using summary statistics for independent probe groups based on gene annotation, mitigating biases from multi-mapping probes. Both methods improve computational efficiency, enhance statistical power, and effectively control type I error rates. Comprehensive evaluations in two large datasets demonstrate superior performance compared to existing methods. Furthermore, we propose a novel beta distribution fitting strategy to improve enrichment P-value estimation, providing a computationally efficient alternative to traditional permutation-based gene set methods.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>These methods are implemented in the R package dmGsea, which is freely available on GitHub and Bioconductor (DOI: 10.18129\/B9.bioc.dmGsea). The package supports Illumina 450K, EPIC, and mouse methylation arrays and can be extended to other omics data with user-provided probe-to-gene mapping annotations.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btaf422","type":"journal-article","created":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T16:51:07Z","timestamp":1753375867000},"source":"Crossref","is-referenced-by-count":1,"title":["Efficient gene set analysis for DNA methylation addressing probe dependency and bias"],"prefix":"10.1093","volume":"41","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9034-8902","authenticated-orcid":false,"given":"Zongli","family":"Xu","sequence":"first","affiliation":[{"name":"Biostatistics & Computational Biology Branch, National Institute of Environmental Health Sciences, NIH , Research Triangle Park, NC 27709,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alison A","family":"Motsinger-Reif","sequence":"additional","affiliation":[{"name":"Biostatistics & Computational Biology Branch, National Institute of Environmental Health Sciences, NIH , Research Triangle Park, NC 27709,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2473-9745","authenticated-orcid":false,"given":"Liang","family":"Niu","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Health Informatics and Data Sciences, College of Medicine, University of Cincinnati , Cincinnati, OH 45267,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2025,7,24]]},"reference":[{"key":"2025081213183600000_btaf422-B1","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1089\/omi.2015.0168","article-title":"GeneAnalytics: an integrative gene set analysis tool for next generation sequencing, RNAseq and microarray data","volume":"20","author":"Ben-Ari Fuchs","year":"2016","journal-title":"Omics"},{"key":"2025081213183600000_btaf422-B2","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1111\/j.2517-6161.1995.tb02031.x","article-title":"Controlling the false discovery rate\u2014a practical and powerful approach to multiple testing","volume":"57","author":"Benjamini","year":"1995","journal-title":"J R Stat Soc B"},{"key":"2025081213183600000_btaf422-B3","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v101.i01","article-title":"The poolr package for combining independent and dependent p values","volume":"101","author":"Cinar","year":"2022","journal-title":"J Stat Softw"},{"key":"2025081213183600000_btaf422-B4","doi-asserted-by":"crossref","first-page":"3514","DOI":"10.1093\/bioinformatics\/btz073","article-title":"ebGSEA: an improved gene set enrichment analysis method for epigenome-wide-association studies","volume":"35","author":"Dong","year":"2019","journal-title":"Bioinformatics"},{"key":"2025081213183600000_btaf422-B5","doi-asserted-by":"crossref","first-page":"140","DOI":"10.5195\/jmla.2018.253","article-title":"The human disease database","volume":"106","author":"Espe","year":"2018","journal-title":"J Med Libr Assoc"},{"key":"2025081213183600000_btaf422-B6","volume-title":"Statistical Methods for Research Workers","author":"Fisher","year":"1932"},{"key":"2025081213183600000_btaf422-B7","doi-asserted-by":"crossref","first-page":"559","DOI":"10.1002\/gepi.20408","article-title":"A new measure of the effective number of tests, a practical tool for comparing families of non-independent significance tests","volume":"33","author":"Galwey","year":"2009","journal-title":"Genet Epidemiol"},{"key":"2025081213183600000_btaf422-B8","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1002\/gepi.20310","article-title":"A multiple testing correction method for genetic association studies using correlated single nucleotide polymorphisms","volume":"32","author":"Gao","year":"2008","journal-title":"Genet Epidemiol"},{"key":"2025081213183600000_btaf422-B9","doi-asserted-by":"crossref","first-page":"545","DOI":"10.1093\/bib\/bbz158","article-title":"Toward a gold standard for benchmarking gene set enrichment analysis","volume":"22","author":"Geistlinger","year":"2021","journal-title":"Brief Bioinform"},{"key":"2025081213183600000_btaf422-B10","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1038\/nprot.2008.211","article-title":"Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources","volume":"4","author":"Huang","year":"2009","journal-title":"Nat Protoc"},{"key":"2025081213183600000_btaf422-B11","doi-asserted-by":"crossref","first-page":"3587","DOI":"10.1093\/bioinformatics\/bti565","article-title":"Ontological analysis of gene expression data: current tools, limitations, and open problems","volume":"21","author":"Khatri","year":"2005","journal-title":"Bioinformatics"},{"key":"2025081213183600000_btaf422-B12","doi-asserted-by":"crossref","first-page":"e1002375","DOI":"10.1371\/journal.pcbi.1002375","article-title":"Ten years of pathway analysis: current approaches and outstanding challenges","volume":"8","author":"Khatri","year":"2012","journal-title":"PLoS Comput Biol"},{"key":"2025081213183600000_btaf422-B13","doi-asserted-by":"publisher","author":"Korotkevich","year":"2021","DOI":"10.1101\/060012"},{"key":"2025081213183600000_btaf422-B14","doi-asserted-by":"crossref","first-page":"W90","DOI":"10.1093\/nar\/gkw377","article-title":"Enrichr: a comprehensive gene set enrichment analysis web server 2016 update","volume":"44","author":"Kuleshov","year":"2016","journal-title":"Nucleic Acids Res"},{"key":"2025081213183600000_btaf422-B15","doi-asserted-by":"crossref","first-page":"2356","DOI":"10.1093\/bioinformatics\/btac076","article-title":"blitzGSEA: efficient computation of gene set enrichment analysis through gamma distribution approximation","volume":"38","author":"Lachmann","year":"2022","journal-title":"Bioinformatics"},{"key":"2025081213183600000_btaf422-B16","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1038\/sj.hdy.6800717","article-title":"Adjusting multiple testing in multilocus analyses using the eigenvalues of a correlation matrix","volume":"95","author":"Li","year":"2005","journal-title":"Heredity"},{"key":"2025081213183600000_btaf422-B17","doi-asserted-by":"crossref","first-page":"D983","DOI":"10.1093\/nar\/gky1027","article-title":"EWAS Atlas: a curated knowledgebase of epigenome-wide association studies","volume":"47","author":"Li","year":"2019","journal-title":"Nucleic Acids Res"},{"key":"2025081213183600000_btaf422-B18","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1186\/s13059-021-02388-x","article-title":"Gene set enrichment analysis for genome-wide DNA methylation data","volume":"22","author":"Maksimovic","year":"2021","journal-title":"Genome Biol"},{"key":"2025081213183600000_btaf422-B19","doi-asserted-by":"crossref","first-page":"100591","DOI":"10.1016\/j.xgen.2024.100591","article-title":"Gene-environment interactions within a precision environmental health framework","volume":"4","author":"Motsinger-Reif","year":"2024","journal-title":"Cell Genom"},{"key":"2025081213183600000_btaf422-B20","doi-asserted-by":"crossref","first-page":"2659","DOI":"10.1093\/bioinformatics\/btw285","article-title":"RCP: a novel probe design bias correction method for Illumina Methylation BeadChip","volume":"32","author":"Niu","year":"2016","journal-title":"Bioinformatics"},{"key":"2025081213183600000_btaf422-B21","doi-asserted-by":"crossref","first-page":"765","DOI":"10.1086\/383251","article-title":"A simple correction for multiple testing for single-nucleotide polymorphisms in linkage disequilibrium with each other","volume":"74","author":"Nyholt","year":"2004","journal-title":"Am J Hum Genet"},{"key":"2025081213183600000_btaf422-B22","doi-asserted-by":"crossref","first-page":"1958","DOI":"10.1093\/bioinformatics\/bty892","article-title":"methylGSA: a Bioconductor package and Shiny app for DNA methylation data length bias adjustment in gene set testing","volume":"35","author":"Ren","year":"2019","journal-title":"Bioinformatics"},{"key":"2025081213183600000_btaf422-B23","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1093\/bioinformatics\/btl633","article-title":"Enrichment or depletion of a GO category within a class of genes: which test?","volume":"23","author":"Rivals","year":"2007","journal-title":"Bioinformatics"},{"key":"2025081213183600000_btaf422-B25","volume-title":"The American Soldier: Adjustment During Army Life","author":"Stouffer","year":"1949"},{"key":"2025081213183600000_btaf422-B26","doi-asserted-by":"crossref","first-page":"15545","DOI":"10.1073\/pnas.0506580102","article-title":"Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles","volume":"102","author":"Subramanian","year":"2005","journal-title":"Proc Natl Acad Sci USA"},{"key":"2025081213183600000_btaf422-B27","volume-title":"Methods of Statistics","author":"Tippett","year":"1931"},{"key":"2025081213183600000_btaf422-B28","doi-asserted-by":"crossref","first-page":"e133","DOI":"10.1093\/nar\/gks461","article-title":"Camera: a competitive gene set test accounting for inter-gene correlation","volume":"40","author":"Wu","year":"2012","journal-title":"Nucleic Acids Res"},{"key":"2025081213183600000_btaf422-B29","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1186\/s12864-016-3426-3","article-title":"RELIC: a novel dye-bias correction method for Illumina Methylation BeadChip","volume":"18","author":"Xu","year":"2017","journal-title":"Bmc Genomics"},{"key":"2025081213183600000_btaf422-B30","doi-asserted-by":"crossref","first-page":"e20","DOI":"10.1093\/nar\/gkv907","article-title":"ENmix: a novel background correction method for Illumina HumanMethylation450 BeadChip","volume":"44","author":"Xu","year":"2016","journal-title":"Nucleic Acids Res"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btaf422\/63841707\/btaf422.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/41\/8\/btaf422\/63841707\/btaf422.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/41\/8\/btaf422\/63841707\/btaf422.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,12]],"date-time":"2025-08-12T17:18:46Z","timestamp":1755019126000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/doi\/10.1093\/bioinformatics\/btaf422\/8211909"}},"subtitle":[],"editor":[{"given":"Peter","family":"Robinson","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2025,7,24]]},"references-count":29,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2025,8,2]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btaf422","relation":{},"ISSN":["1367-4811"],"issn-type":[{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2025,8]]},"published":{"date-parts":[[2025,7,24]]},"article-number":"btaf422"}}