Estimating and accounting for tumor purity in the analysis of DNA methylation data from cancer studies

• Type of Material: Article
• Authors: Xiaoqi Zheng, Shanghai Normal University; Naiqian Zhang, Weifang University; Hao Wu, Emory University; Hua-Jun Wu, Harvard School of Public Health
• Language: English
• Date: 2017-01-25
• Publisher: BioMed Central
• Publication Version: Final Published Version
• Copyright Statement: © 2017, The Author(s).
• Final Published Version (URL): http://dx.doi.org/10.1186/s13059-016-1143-5
• Title of Journal or Parent Work: Genome Biology
• ISSN: 1474-7596
• Volume: 18
• Issue: 1
• Start Page: 17
• End Page: 17
• Grant/Funding Information: This project was supported by the National Natural Science Foundation of China (61572327 to XZ, 31601079 to NZ) and National Institute of General Medical Sciences (R01GM122083 to HW).
• Keywords: Tumor purity; DNA methylation; Cancer epigenomics; Differential methylation
• Research Categories: Biology, Biostatistics; Health Sciences, Public Health

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.