title: PCAN: phenotype consensus analysis to support disease-gene association.
abstract: BACKGROUND
  Bridging genotype and phenotype is a fundamental biomedical challenge that underlies more effective target discovery and patient-tailored therapy. Approaches that can flexibly and intuitively, integrate known gene-phenotype associations in the context of molecular signaling networks are vital to effectively prioritize and biologically interpret genes underlying disease traits of interest.
  
  
  RESULTS
  We describe Phenotype Consensus Analysis (PCAN); a method to assess the consensus semantic similarity of phenotypes in a candidate gene's signaling neighborhood. We demonstrate that significant phenotype consensus (p < 0.05) is observable for ~67% of 4,549 OMIM disease-gene associations, using a combination of high quality String interactions + Metabase pathways and use Joubert Syndrome to demonstrate the ease with which a significant result can be interrogated to highlight discriminatory traits linked to mechanistically related genes.
  
  
  CONCLUSIONS
  We advocate phenotype consensus as an intuitive and versatile method to aid disease-gene association, which naturally lends itself to the mechanistic deconvolution of diverse phenotypes. We provide PCAN to the community as an R package ( http://bioconductor.org/packages/PCAN/ ) to allow flexible configuration, extension and standalone use or integration to supplement existing gene prioritization workflows.
authors.affiliation: Clarivate Analytics (formerly the IP & Science business of Thomson Reuters), 5901 Priestly Dr., #200, Carlsbad, CA, 92008, USA.
authors.forename: Patrice
authors.initials: P
authors.lastname: Godard
authors.affiliation: Translational Bioinformatics, UCB Pharma, 208 Bath Road, Slough, SL1 3WE, UK. matthew.page@ucb.com.
authors.forename: Matthew
authors.identifier: http://orcid.org/0000-0002-3571-0374
authors.initials: M
authors.lastname: Page
mesh_terms: D000015:Abnormalities, Multiple / Q000235:genetics; D002531:Cerebellum / Q000002:abnormalities; D004194:Disease / Q000235:genetics*; D005124:Eye Abnormalities / Q000235:genetics; D005796:Genes; D005838:Genotype; D006801:Humans; D052177:Kidney Diseases, Cystic / Q000235:genetics; D010641:Phenotype; D012160:Retina / Q000002:abnormalities; D015398:Signal Transduction; D012984:Software
keywords: Biological networks; Disease-gene association; Genetics; Phenotype; Semantic similarity