{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,6]],"date-time":"2025-11-06T12:23:03Z","timestamp":1762431783188,"version":"3.37.3"},"reference-count":40,"publisher":"Oxford University Press (OUP)","issue":"7","license":[{"start":{"date-parts":[[2019,11,26]],"date-time":"2019-11-26T00:00:00Z","timestamp":1574726400000},"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\/501100012166","name":"National Key R&D Program of China","doi-asserted-by":"crossref","award":["2018YFA0900600"],"award-info":[{"award-number":["2018YFA0900600"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61902061","61572327","61972257"],"award-info":[{"award-number":["61902061","61572327","61972257"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100007219","name":"Natural Science Foundation of Shanghai","doi-asserted-by":"publisher","award":["19ZR1437000"],"award-info":[{"award-number":["19ZR1437000"]}],"id":[{"id":"10.13039\/100007219","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Science and Technology Research Project of Jiangxi Education Department","award":["GJJ170445"],"award-info":[{"award-number":["GJJ170445"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,4,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Motivation<\/jats:title><jats:p>Inference of differentially methylated (DM) CpG sites between two groups of tumor samples with different geno- or pheno-types is a critical step to uncover the epigenetic mechanism of tumorigenesis, and identify biomarkers for cancer subtyping. However, as a major source of confounding factor, uneven distributions of tumor purity between two groups of tumor samples will lead to biased discovery of DM sites if not properly accounted for.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>We here propose InfiniumDM, a generalized least square model to adjust tumor purity effect for differential methylation analysis. Our method is applicable to a variety of experimental designs including with or without normal controls, different sources of normal tissue contaminations. We compared our method with conventional methods including minfi, limma and limma corrected by tumor purity using simulated datasets. Our method shows significantly better performance at different levels of differential methylation thresholds, sample sizes, mean purity deviations and so on. We also applied the proposed method to breast cancer samples from TCGA database to further evaluate its performance. Overall, both simulation and real data analyses demonstrate favorable performance over existing methods serving similar purpose.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and implementation<\/jats:title><jats:p>InfiniumDM is a part of R package InfiniumPurify, which is freely available from GitHub (https:\/\/github.com\/Xiaoqizheng\/InfiniumPurify).<\/jats:p><\/jats:sec><jats:sec><jats:title>Supplementary information<\/jats:title><jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/btz885","type":"journal-article","created":{"date-parts":[[2019,11,23]],"date-time":"2019-11-23T20:09:28Z","timestamp":1574539768000},"page":"2017-2024","source":"Crossref","is-referenced-by-count":5,"title":["Detection of differentially methylated CpG sites between tumor samples with uneven tumor purities"],"prefix":"10.1093","volume":"36","author":[{"given":"Weiwei","family":"Zhang","sequence":"first","affiliation":[{"name":"Department of Mathematics, School of Science, East China University of Technology , Nanchang, Jiangxi 330013, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8359-0533","authenticated-orcid":false,"given":"Ziyi","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Biostatistics and Bioinformatics, Emory University , Atlanta, GA 30322, USA"}]},{"given":"Nana","family":"Wei","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Shanghai Normal University , Shanghai 200234, China"}]},{"given":"Hua-Jun","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health , Boston, MA 02215, USA"}]},{"given":"Xiaoqi","family":"Zheng","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Shanghai Normal University , Shanghai 200234, China"}]}],"member":"286","published-online":{"date-parts":[[2019,11,26]]},"reference":[{"key":"2023062312013693400_btz885-B1","doi-asserted-by":"crossref","first-page":"1865","DOI":"10.1093\/bioinformatics\/btt301","article-title":"DeMix: deconvolution for mixed cancer transcriptomes using raw measured data","volume":"29","author":"Ahn","year":"2013","journal-title":"Bioinformatics"},{"key":"2023062312013693400_btz885-B2","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1146\/annurev-med-111314-035900","article-title":"Epigenetic therapeutics: a new weapon in the war against cancer","volume":"67","author":"Ahuja","year":"2016","journal-title":"Annu. 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