title: Integrating human omics data to prioritize candidate genes.
abstract: BACKGROUND
  The identification of genes involved in human complex diseases remains a great challenge in computational systems biology. Although methods have been developed to use disease phenotypic similarities with a protein-protein interaction network for the prioritization of candidate genes, other valuable omics data sources have been largely overlooked in these methods.
  
  
  METHODS
  With this understanding, we proposed a method called BRIDGE to prioritize candidate genes by integrating disease phenotypic similarities with such omics data as protein-protein interactions, gene sequence similarities, gene expression patterns, gene ontology annotations, and gene pathway memberships. BRIDGE utilizes a multiple regression model with lasso penalty to automatically weight different data sources and is capable of discovering genes associated with diseases whose genetic bases are completely unknown.
  
  
  RESULTS
  We conducted large-scale cross-validation experiments and demonstrated that more than 60% known disease genes can be ranked top one by BRIDGE in simulated linkage intervals, suggesting the superior performance of this method. We further performed two comprehensive case studies by applying BRIDGE to predict novel genes and transcriptional networks involved in obesity and type II diabetes.
  
  
  CONCLUSIONS
  The proposed method provides an effective and scalable way for integrating multi omics data to infer disease genes. Further applications of BRIDGE will be benefit to providing novel disease genes and underlying mechanisms of human diseases.
authors.forename: Yong
authors.initials: Y
authors.lastname: Chen
authors.forename: Xuebing
authors.initials: X
authors.lastname: Wu
authors.affiliation: Department of Automation, MOE Key Laboratory of Bioinformatics; Bioinformatics Division and Center for Synthetic & Systems Biology, TNLIST, Tsinghua University, Beijing 100084, China. ruijiang@tsinghua.edu.cn.
authors.forename: Rui
authors.initials: R
authors.lastname: Jiang
mesh_terms: D003924:Diabetes Mellitus, Type 2 / Q000235:genetics / Q000378:metabolism; D020869:Gene Expression Profiling; D053263:Gene Regulatory Networks; D023281:Genomics / Q000379:methods*; D006801:Humans; D020407:Internet; D009765:Obesity / Q000235:genetics / Q000378:metabolism; D025941:Protein Interaction Mapping; D049490:Systems Biology / Q000379:methods*; D014584:User-Computer Interface