{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T08:39:48Z","timestamp":1783586388552,"version":"3.55.0"},"reference-count":10,"publisher":"Oxford University Press (OUP)","issue":"7","license":[{"start":{"date-parts":[[2018,9,1]],"date-time":"2018-09-01T00:00:00Z","timestamp":1535760000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"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"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["P30-ES006096"],"award-info":[{"award-number":["P30-ES006096"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,4,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Both \u03b2-value and M-value have been used as metrics to measure methylation levels. The M-value is more statistically valid for the differential analysis of methylation levels. However, the \u03b2-value is much more biologically interpretable and needs to be reported when M-value method is used for conducting differential methylation analysis. There is an urgent need to know how to interpret the degree of differential methylation from the M-value. In M-value linear regression model, differential methylation M-value \u0394M can be easily obtained from the coefficient estimate, but it is not straightforward to get the differential methylation \u03b2-value, \u0394\u03b2 since it cannot be obtained from the coefficient alone.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>To fill the gap, we have built a bridge to connect the statistically sound M-value linear regression model and the biologically interpretable \u0394\u03b2. In this article, three methods were proposed to calculate differential methylation values, \u0394\u03b2 from M-value linear regression model and compared with the \u0394\u03b2 directly obtained from \u03b2-value linear regression model. We showed that under the condition that M-value linear regression model is correct, the method M-model-coef is the best among the four methods. M-model-M-mean method works very well too. If the coefficients \u03b10,\u00a0\u03b12,\u2026\u03b1p are not given (as \u2018MethLAB\u2019 package), the M-model-M-mean method should be used. The \u0394\u03b2 directly obtained from \u03b2-value linear regression model can give very biased results, especially when M-values are not in (\u22122, 2) or \u03b2-values are not in (0.2, 0.8).<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>The dataset for example is available at the National Center for Biotechnology Information Gene Expression Omnibus repository, GSE104778.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Supplementary information<\/jats:title>\n                  <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/bty778","type":"journal-article","created":{"date-parts":[[2018,9,1]],"date-time":"2018-09-01T04:01:06Z","timestamp":1535774466000},"page":"1094-1097","source":"Crossref","is-referenced-by-count":67,"title":["Differential methylation values in differential methylation analysis"],"prefix":"10.1093","volume":"35","author":[{"given":"Changchun","family":"Xie","sequence":"first","affiliation":[{"name":"Department of Environmental Health, University of Cincinnati, Cincinnati, OH, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuet-Kin","family":"Leung","sequence":"additional","affiliation":[{"name":"Department of Environmental Health, University of Cincinnati, Cincinnati, OH, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aimin","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Environmental Health, University of Cincinnati, Cincinnati, OH, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ding-Xin","family":"Long","sequence":"additional","affiliation":[{"name":"School of Public Health, University of South China, Hengyang, Hunan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Catherine","family":"Hoyo","sequence":"additional","affiliation":[{"name":"Department of Biological Sciences, North Carolina State University, Raleigh, NC, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuk-Mei","family":"Ho","sequence":"additional","affiliation":[{"name":"Department of Environmental Health, University of Cincinnati, Cincinnati, OH, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2018,9,1]]},"reference":[{"key":"2023013107263100300_bty778-B1","doi-asserted-by":"crossref","first-page":"587","DOI":"10.1186\/1471-2105-11-587","article-title":"Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis","volume":"11","author":"Du","year":"2010","journal-title":"BMC Bioinformatics"},{"key":"2023013107263100300_bty778-B2","doi-asserted-by":"crossref","first-page":"225","DOI":"10.4161\/epi.7.3.19284","article-title":"MethLAB: a graphical user interface package for the analysis of array-based DNA methylation data","volume":"7","author":"Kilaru","year":"2012","journal-title":"Epigenetics"},{"key":"2023013107263100300_bty778-B3","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1038\/nrg2732","article-title":"Principles and challenges of genome-wide DNA methylation analysis","volume":"11","author":"Laird","year":"2010","journal-title":"Nat. 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