title: A vertex similarity-based framework to discover and rank orphan disease-related genes.
abstract: BACKGROUND
  A rare or orphan disease (OD) is any disease that affects a small percentage of the population. While opportunities now exist to accelerate progress toward understanding the basis for many more ODs, the prioritization of candidate genes is still a critical step for disease-gene identification. Several network-based frameworks have been developed to address this problem with varied results.
  
  
  RESULTS
  We have developed a novel vertex similarity (VS) based parameter-free prioritizing framework to identify and rank orphan disease candidate genes. We validate our approach by using 1598 known orphan disease-causing genes (ODGs) representing 172 orphan diseases (ODs). We compare our approach with a state-of-art parameter-based approach (PageRank with Priors or PRP) and with another parameter-free method (Interconnectedness or ICN). Our results show that VS-based approach outperforms ICN and is comparable to PRP. We further apply VS-based ranking to identify and rank potential novel candidate genes for several ODs.
  
  
  CONCLUSIONS
  We demonstrate that VS-based parameter-free ranking approach can be successfully used for disease candidate gene prioritization and can complement other network-based methods for candidate disease gene ranking. Importantly, our VS-ranked top candidate genes for the ODs match the known literature, suggesting several novel causal relationships for further investigation.
authors.affiliation: Department of Computer Science, University of Cincinnati, Cincinnati, Ohio 45229, USA.
authors.forename: Cheng
authors.initials: C
authors.lastname: Zhu
authors.forename: Akash
authors.initials: A
authors.lastname: Kushwaha
authors.forename: Kenneth
authors.initials: K
authors.lastname: Berman
authors.forename: Anil G
authors.initials: AG
authors.lastname: Jegga
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D006801:Humans; D008962:Models, Theoretical; D060066:Protein Interaction Maps; D035583:Rare Diseases / Q000235:genetics*