GeneYenta: A Phenotype­Based Rare Disease Case Matching Tool Based on Online Dating Algorithms for the Acceleration of Exome Interpretation. Issue 4 (19th March 2015)

• Record Type: Journal Article
• Authors: Gottlieb, Michael M.; Arenillas, David J.; Maithripala, Savanie; Maurer, Zachary D.; Tarailo­Graovac, Maja; Armstrong, Linlea; Patel, Millan; van Karnebeek, Clara; Wasserman, Wyeth W.
• Is Part Of: Human mutation. Volume 36:Issue 4(2015:Apr.)
• Page Start: 432
• Page End: 438
• Publication Date: 2015-03-19
• Subjects: Human chromosome abnormalities -- Periodicals; Mutation (Biology) -- Periodicals; 616.04205
• DOI: 10.1002/humu.22772
• Languages: English
• ISSNs: 1059-7794

Abstract

<abstract abstract-type="graphical" xml:lang="en" id="humu22772-abs-0001"> <title> <x xml:space="preserve">Abstract</x> </title> <p>We introduce a web tool, GeneYenta, which facilitates rare disease diagnostics by allowing clinicians to compare patient phenotypes online in order to exchange genomic data offline. The procedure for matching patient phenotypes, inspired by online dating services, uses an ontology‐based semantic case matching algorithm with attribute weighting. We evaluate our system against three other matching algorithms using a curated reference data set and 19 clinician entered cases, and find that the inclusion of clinician weights can augment phenotype matching. <boxed-text content-type="graphic" position="anchor" orientation="portrait"><graphic position="anchor" mimetype="image" xlink:href="ark:/27927/pgjdndb2wt" orientation="portrait" xlink:type="simple" xmlns:xlink="http://www.w3.org/1999/xlink" /></boxed-text></p> </abstract>