title: GeneTIER: prioritization of candidate disease genes using tissue-specific gene expression profiles.
abstract: BACKGROUND
  In attempts to determine the genetic causes of human disease, researchers are often faced with a large number of candidate genes. Linkage studies can point to a genomic region containing hundreds of genes, while the high-throughput sequencing approach will often identify a great number of non-synonymous genetic variants. Since systematic experimental verification of each such candidate gene is not feasible, a method is needed to decide which genes are worth investigating further. Computational gene prioritization presents itself as a solution to this problem, systematically analyzing and sorting each gene from the most to least likely to be the disease-causing gene, in a fraction of the time it would take a researcher to perform such queries manually.
  
  
  RESULTS
  Here, we present Gene TIssue Expression Ranker (GeneTIER), a new web-based application for candidate gene prioritization. GeneTIER replaces knowledge-based inference traditionally used in candidate disease gene prioritization applications with experimental data from tissue-specific gene expression datasets and thus largely overcomes the bias toward the better characterized genes/diseases that commonly afflict other methods. We show that our approach is capable of accurate candidate gene prioritization and illustrate its strengths and weaknesses using case study examples.
  
  
  METHODS
  Freely available on the web at http://dna.leeds.ac.uk/GeneTIER/.
  
  
  BACKGROUND
  umaan@leeds.ac.uk
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors: Section of Genetics, Institute of Biomedical and Clinical Sciences, School of Medicine, University of Leeds, St James's University Hospital and.
authors: Agne
authors: A
authors: Antanaviciute
authors: Section of Genetics, Institute of Biomedical and Clinical Sciences, School of Medicine, University of Leeds, St James's University Hospital and.
authors: Catherine
authors: C
authors: Daly
authors: Yorkshire Regional Genetics Service, St James's University Hospital, Leeds, UK.
authors: Laura A
authors: LA
authors: Crinnion
authors: Section of Genetics, Institute of Biomedical and Clinical Sciences, School of Medicine, University of Leeds, St James's University Hospital and.
authors: Alexander F
authors: AF
authors: Markham
authors: Yorkshire Regional Genetics Service, St James's University Hospital, Leeds, UK.
authors: Christopher M
authors: CM
authors: Watson
authors: Section of Genetics, Institute of Biomedical and Clinical Sciences, School of Medicine, University of Leeds, St James's University Hospital and.
authors: David T
authors: DT
authors: Bonthron
authors: Section of Genetics, Institute of Biomedical and Clinical Sciences, School of Medicine, University of Leeds, St James's University Hospital and.
authors: Ian M
authors: IM
authors: Carr
mesh_terms: D000465:Algorithms; D019540:Area Under Curve; D004194:Disease / Q000235:genetics*; D056726:Genetic Association Studies / Q000379:methods*; D006801:Humans; D009928:Organ Specificity / Q000235:genetics*; D012372:ROC Curve; D059467:Transcriptome / Q000235:genetics*