title: Predicting tumor purity from methylation microarray data.
abstract: BACKGROUND
  In cancer genomics research, one important problem is that the solid tissue sample obtained from clinical settings is always a mixture of cancer and normal cells. The sample mixture brings complication in data analysis and results in biased findings if not correctly accounted for. Estimating tumor purity is of great interest, and a number of methods have been developed using gene expression, copy number variation or point mutation data.
  
  
  RESULTS
  We discover that in cancer samples, the distributions of data from Illumina Infinium 450 k methylation microarray are highly correlated with tumor purities. We develop a simple but effective method to estimate purities from the microarray data. Analyses of the Cancer Genome Atlas lung cancer data demonstrate favorable performance of the proposed method.
  
  
  METHODS
  The method is implemented in InfiniumPurify, which is freely available at https://bitbucket.org/zhengxiaoqi/infiniumpurify.
  
  
  BACKGROUND
  xqzheng@shnu.edu.cn or hao.wu@emory.edu
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Department of Mathematics, Shanghai Normal University, Shanghai 200234, 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 02215, MA, USA and.
authors.forename: Hua-Jun
authors.initials: HJ
authors.lastname: Wu
authors.affiliation: Department of Mathematics, Shanghai Normal University, Shanghai 200234, China.
authors.forename: Weiwei
authors.initials: W
authors.lastname: Zhang
authors.affiliation: Department of Mathematics, Shanghai Normal University, Shanghai 200234, China.
authors.forename: Jun
authors.initials: J
authors.lastname: Wang
authors.affiliation: Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA 30322, USA.
authors.forename: Hao
authors.initials: H
authors.lastname: Wu
authors.affiliation: Department of Mathematics, Shanghai Normal University, Shanghai 200234, China.
authors.forename: Xiaoqi
authors.initials: X
authors.lastname: Zheng
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D056915:DNA Copy Number Variations; D019175:DNA Methylation; D020869:Gene Expression Profiling; D015894:Genome, Human; D023281:Genomics / Q000379:methods*; D006801:Humans; D008175:Lung Neoplasms / Q000235:genetics* / Q000473:pathology*