title: Integrating heterogeneous genomic data to accurately identify disease subtypes.
abstract: BACKGROUND
  High-throughput biotechnologies have been widely used to characterize clinical samples from various perspectives e.g., epigenomics, genomics and transcriptomics. However, because of the heterogeneity of these technologies and their outputs, individual analysis of the various types of data is hard to create a comprehensive view of disease subtypes. Integrative methods are of pressing need.
  
  
  METHODS
  In this study, we evaluated the possible issues that hamper integrative analysis of the heterogeneous disease data types, and proposed iBFE, an effective and efficient computational method to subvert those issues from a feature extraction perspective.
  
  
  RESULTS
  Strict experiments on both simulated and real datasets demonstrated that iBFE can easily overcome issues caused by scale conflicts, noise conflicts, incompleteness of patient relationships, and conflicts between patient relationships, and that iBFE can effectively combine the merits of DNA methylation, mRNA expression and microRNA (miRNA) expression datasets to accurately identify disease subtypes of significantly different prognosis.
  
  
  CONCLUSIONS
  iBFE is an effective and efficient method for integrative analysis of heterogeneous genomic data to accurately identify disease subtypes. The Matlab code of iBFE is freely available from http://zhangroup.aporc.org/iBFE.
authors.affiliation: MOH Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China. renxwise@gmail.com.
authors.forename: Xianwen
authors.initials: X
authors.lastname: Ren
authors.affiliation: MOH Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China. fuhua@ipbcams.ac.cn.
authors.forename: Hua
authors.initials: H
authors.lastname: Fu
authors.affiliation: MOH Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China. zdsys@vip.sina.com.
authors.forename: Qi
authors.initials: Q
authors.lastname: Jin
mesh_terms: D000818:Animals; D019175:DNA Methylation / Q000235:genetics; D004273:DNA, Neoplasm / Q000235:genetics; D030541:Databases, Genetic; D023281:Genomics; D006801:Humans; D035683:MicroRNAs / Q000235:genetics; D009369:Neoplasms / Q000175:diagnosis / Q000235:genetics*; D012333:RNA, Messenger / Q000235:genetics; D012334:RNA, Neoplasm / Q000235:genetics; D012984:Software
chemical_list: D004273:DNA, Neoplasm; D035683:MicroRNAs; D012333:RNA, Messenger; D012334:RNA, Neoplasm