{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T22:22:04Z","timestamp":1787955724324,"version":"build-2784847793"},"reference-count":57,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/501100004381","name":"Western University","doi-asserted-by":"publisher","award":["Start Up Funds"],"award-info":[{"award-number":["Start Up Funds"]}],"id":[{"id":"10.13039\/501100004381","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004381","name":"Western University","doi-asserted-by":"publisher","award":["USRI Award"],"award-info":[{"award-number":["USRI Award"]}],"id":[{"id":"10.13039\/501100004381","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Bioinform Biol Insights"],"published-print":{"date-parts":[[2026,3]]},"abstract":"<jats:p>\n                    Epigenetic age is a biological age estimate based on nuclear DNA methylation patterns. Epigenetic clocks measure biological age by analyzing predictable changes in DNA methylation sites associated with aging. This study introduces EpigeneticAgePipeline, an R package that streamlines the estimation of epigenetic age metrics including Horvath, Horvath skin and blood, Hannum, PhenoAge\/Levine, GrimAge (V1 and V2), and DunedinPACE plus additional acceleration metrics based on all other clocks. Quality control includes detection\n                    <jats:italic toggle=\"yes\">P<\/jats:italic>\n                    -value filtering (sample- and probe-level), bead-count thresholds, and Illumina quality control intensity checks. EpigeneticAgePipeline supports Illumina Infinium methylation microarrays (HumanMethylation27, HumanMethylation450, HumanMethylationEPIC\/EPICv2, and Human Methylation Screening Array). It offers functionalities including data preprocessing, normalization, cell count imputation, residual generation accounting for principal components and batch effects, and extensive visualizations for improved interpretability. Validation was performed using GEO data set GSE237561, confirming the accuracy of the pipeline. EpigeneticAgePipeline provides an integrated workflow from raw data to advanced statistical analyses and visualizations, improving usability over existing tools. In addition to the traditional clocks mentioned, the package also integrates a set of additional epigenetic age clocks (PedBE, Wu, TL, BLUP, and EN). Future updates will include emerging epigenetic age measures to maintain relevance in this evolving field.\n                  <\/jats:p>","DOI":"10.1177\/11779322261433665","type":"journal-article","created":{"date-parts":[[2026,3,30]],"date-time":"2026-03-30T11:12:30Z","timestamp":1774869150000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["EpigeneticAgePipeline: An R Package for Comprehensive Assessment of Epigenetic Age Metrics From Methylation Microarrays"],"prefix":"10.1177","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-2942-5939","authenticated-orcid":false,"given":"Stanislav","family":"Rayevskiy","sequence":"first","affiliation":[{"name":"Department of Pathology and Laboratory Medicine, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-7058-1629","authenticated-orcid":false,"given":"Quinn","family":"Le","sequence":"additional","affiliation":[{"name":"Department of Pathology and Laboratory Medicine, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julia","family":"Nguyen","sequence":"additional","affiliation":[{"name":"Department of Pathology and Laboratory Medicine, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-8669-6178","authenticated-orcid":false,"given":"Steven Q.","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Pathology and Laboratory Medicine, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2737-0549","authenticated-orcid":false,"given":"Christina A.","family":"Castellani","sequence":"additional","affiliation":[{"name":"Department of Pathology and Laboratory Medicine, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada"},{"name":"Department of Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada"},{"name":"McKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA"},{"name":"Children\u2019s Health Research Institute, London Health Sciences Centre Research Institute, London, ON, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,3,30]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11357-023-00871-w"},{"key":"e_1_3_3_3_2","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btaa825"},{"key":"e_1_3_3_4_2","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btu049"},{"key":"e_1_3_3_5_2","unstructured":"Bioconductor. n.d. 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