title: contamDE: differential expression analysis of RNA-seq data for contaminated tumor samples.
abstract: Accurate detection of differentially expressed genes between tumor and normal samples is a primary approach of cancer-related biomarker identification. Due to the infiltration of tumor surrounding normal cells, the expression data derived from tumor samples would always be contaminated with normal cells. Ignoring such cellular contamination would deflate the power of detecting DE genes and further confound the biological interpretation of the analysis results. For the time being, there does not exists any differential expression analysis approach for RNA-seq data in literature that can properly account for the contamination of tumor samples.
  
  
  
  Without appealing to any extra information, we develop a new method 'contamDE' based on a novel statistical model that associates RNA-seq expression levels with cell types. It is demonstrated through simulation studies that contamDE could be much more powerful than the existing methods that ignore the contamination. In the application to two cancer studies, contamDE uniquely found several potential therapy and prognostic biomarkers of prostate cancer and non-small cell lung cancer.
  
  
  
  An R package contamDE is freely available at http://homepage.fudan.edu.cn/zhangh/softwares/
  
  
  
  zhanghfd@fudan.edu.cn
  
  
  
  Supplementary data are available at Bioinformatics online.
authors.affiliation: State Key Laboratory of Genetic Engineering and Institute of Biostatistics, School of Life Sciences, Fudan University, Shanghai 200433, People's Republic of China and.
authors.forename: Qi
authors.initials: Q
authors.lastname: Shen
authors.affiliation: State Key Laboratory of Genetic Engineering and Institute of Biostatistics, School of Life Sciences, Fudan University, Shanghai 200433, People's Republic of China and.
authors.forename: Jiyuan
authors.initials: J
authors.lastname: Hu
authors.affiliation: State Key Laboratory of Genetic Engineering and Institute of Biostatistics, School of Life Sciences, Fudan University, Shanghai 200433, People's Republic of China and.
authors.forename: Ning
authors.initials: N
authors.lastname: Jiang
authors.affiliation: State Key Laboratory of Genetic Engineering and Institute of Biostatistics, School of Life Sciences, Fudan University, Shanghai 200433, People's Republic of China and.
authors.forename: Xiaohua
authors.initials: X
authors.lastname: Hu
authors.affiliation: School of Biosciences, University of Birmingham, Birmingham B15 2TT, UK.
authors.forename: Zewei
authors.initials: Z
authors.lastname: Luo
authors.affiliation: State Key Laboratory of Genetic Engineering and Institute of Biostatistics, School of Life Sciences, Fudan University, Shanghai 200433, People's Republic of China and.
authors.forename: Hong
authors.initials: H
authors.lastname: Zhang
mesh_terms: D020869:Gene Expression Profiling; D006801:Humans; D009369:Neoplasms / Q000235:genetics*; D012313:RNA; D017423:Sequence Analysis, RNA; D012984:Software
chemical_list: D012313:RNA