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A common way to measure DNA methylation is the calculation of beta values, which are bounded variables of the form <jats:italic>M<\/jats:italic>\/(<jats:italic>M<\/jats:italic>+<jats:italic>U<\/jats:italic>) that are generated by Illumina\u2019s 450k BeadChip array. The statistical analysis of beta values is considered to be challenging, as traditional methods for the analysis of bounded variables, such as M-value regression and beta regression, are based on regularity assumptions that are often too strong to adequately describe the distribution of beta values.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>We develop a statistical model for the analysis of beta values that is derived from a bivariate gamma distribution for the signal intensities <jats:italic>M<\/jats:italic> and <jats:italic>U<\/jats:italic>. By allowing for possible correlations between <jats:italic>M<\/jats:italic> and <jats:italic>U<\/jats:italic>, the proposed model explicitly takes into account the data-generating process underlying the calculation of beta values. Using simulated data and a real sample of DNA methylation data from the Heinz Nixdorf Recall cohort study, we demonstrate that the proposed model fits our data significantly better than beta regression and M-value regression.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusion<\/jats:title>\n                <jats:p>The proposed model contributes to an improved identification of associations between beta values and covariates such as clinical variables and lifestyle factors in epigenome-wide association studies. It is as easy to apply to a sample of beta values as beta regression and M-value regression.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12859-016-1347-4","type":"journal-article","created":{"date-parts":[[2016,11,22]],"date-time":"2016-11-22T12:44:39Z","timestamp":1479818679000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":52,"title":["A statistical model for the analysis of beta values in DNA methylation studies"],"prefix":"10.1186","volume":"17","author":[{"given":"Leonie","family":"Weinhold","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Simone","family":"Wahl","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sonali","family":"Pechlivanis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Per","family":"Hoffmann","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matthias","family":"Schmid","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2016,11,22]]},"reference":[{"key":"1347_CR1","doi-asserted-by":"publisher","first-page":"6","DOI":"10.1101\/gad.947102","volume":"16","author":"A Bird","year":"2002","unstructured":"Bird A. 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