Maggie Po-Yuan Fu, Sarah Martin Merrill, Keegan Korthauer, Michael Steffen Kobor
{"title":"Examining cellular heterogeneity in human DNA methylation studies: Overview and recommendations.","authors":"Maggie Po-Yuan Fu, Sarah Martin Merrill, Keegan Korthauer, Michael Steffen Kobor","doi":"10.1016/j.xpro.2025.103638","DOIUrl":null,"url":null,"abstract":"<p><p>Intersample cellular heterogeneity (ISCH) is one of the largest contributors to DNA methylation (DNAme) variability. It is imperative to account for ISCH to accurately interpret analysis results in epigenome-wide association studies. We compiled this primer based on the current literature to guide researchers through the process of estimating and accounting for ISCH in DNA methylation studies. This primer outlines the procedure of bioinformatic ISCH prediction, including using reference-based and reference-free algorithms. It then follows with descriptions of several methods to account for ISCH in downstream analyses, including robust linear regression and principal-component-analysis-based adjustments. Finally, we outlined three methods for estimating differential DNAme signals in a cell-type-specific manner. Throughout the primer, we provided statistical and biological justification for our recommendations, as well as R code examples for ease of implementation.</p>","PeriodicalId":34214,"journal":{"name":"STAR Protocols","volume":"6 1","pages":"103638"},"PeriodicalIF":1.3000,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11969412/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"STAR Protocols","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.xpro.2025.103638","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/2/12 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
Intersample cellular heterogeneity (ISCH) is one of the largest contributors to DNA methylation (DNAme) variability. It is imperative to account for ISCH to accurately interpret analysis results in epigenome-wide association studies. We compiled this primer based on the current literature to guide researchers through the process of estimating and accounting for ISCH in DNA methylation studies. This primer outlines the procedure of bioinformatic ISCH prediction, including using reference-based and reference-free algorithms. It then follows with descriptions of several methods to account for ISCH in downstream analyses, including robust linear regression and principal-component-analysis-based adjustments. Finally, we outlined three methods for estimating differential DNAme signals in a cell-type-specific manner. Throughout the primer, we provided statistical and biological justification for our recommendations, as well as R code examples for ease of implementation.