title: Estimating and accounting for tumor purity in the analysis of DNA methylation data from cancer studies.
abstract: We present a set of statistical methods for the analysis of DNA methylation microarray data, which account for tumor purity. These methods are an extension of our previously developed method for purity estimation; our updated method is flexible, efficient, and does not require data from reference samples or matched normal controls. We also present a method for incorporating purity information for differential methylation analysis. In addition, we propose a control-free differential methylation calling method when normal controls are not available. Extensive analyses of TCGA data demonstrate that our methods provide accurate results. All methods are implemented in InfiniumPurify.
authors.affiliation: Department of Mathematics, Shanghai Normal University, Shanghai, 200234, China. xqzheng@shnu.edu.cn.
authors.forename: Xiaoqi
authors.initials: X
authors.lastname: Zheng
authors.affiliation: Department of Mathematics, Weifang University, Weifang, Shandong, 261061, China.
authors.forename: Naiqian
authors.initials: N
authors.lastname: Zhang
authors.affiliation: Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, MA, 02215, USA.
authors.forename: Hua-Jun
authors.initials: HJ
authors.lastname: Wu
authors.affiliation: Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, 1518 Clifton Road, Atlanta, Georgia, 30322, USA. hao.wu@emory.edu.
authors.forename: Hao
authors.initials: H
authors.lastname: Wu
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D003198:Computer Simulation; D018899:CpG Islands; D019175:DNA Methylation; D044127:Epigenesis, Genetic; D057890:Epigenomics / Q000379:methods*; D006801:Humans; D009369:Neoplasms / Q000235:genetics*; D012372:ROC Curve
keywords: Cancer epigenomics; DNA methylation; Differential methylation; Tumor purity