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P heno T ips: Patient Phenotyping Software for Clinical and Research Use
Author(s) -
Girdea Marta,
Dumitriu Sergiu,
Fiume Marc,
Bowdin Sarah,
Boycott Kym M.,
Chénier Sébastien,
Chitayat David,
Faghfoury Hanna,
Meyn M. Stephen,
Ray Peter N.,
So Joyce,
Stavropoulos Dimitri J.,
Brudno Michael
Publication year - 2013
Publication title -
human mutation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.981
H-Index - 162
eISSN - 1098-1004
pISSN - 1059-7794
DOI - 10.1002/humu.22347
Subject(s) - workflow , interface (matter) , computer science , omim : online mendelian inheritance in man , software , ontology , phenotype , standardization , user interface , bioinformatics , world wide web , data mining , biology , database , programming language , genetics , philosophy , bubble , epistemology , maximum bubble pressure method , parallel computing , gene , operating system
We have developed PhenoTips: open source software for collecting and analyzing phenotypic information for patients with genetic disorders. Our software combines an easy-to-use interface, compatible with any device that runs a Web browser, with a standardized database back end. The PhenoTips' user interface closely mirrors clinician workflows so as to facilitate the recording of observations made during the patient encounter. Collected data include demographics, medical history, family history, physical and laboratory measurements, physical findings, and additional notes. Phenotypic information is represented using the Human Phenotype Ontology; however, the complexity of the ontology is hidden behind a user interface, which combines simple selection of common phenotypes with error-tolerant, predictive search of the entire ontology. PhenoTips supports accurate diagnosis by analyzing the entered data, then suggesting additional clinical investigations and providing Online Mendelian Inheritance in Man (OMIM) links to likely disorders. By collecting, classifying, and analyzing phenotypic information during the patient encounter, PhenoTips allows for streamlining of clinic workflow, efficient data entry, improved diagnosis, standardization of collected patient phenotypes, and sharing of anonymized patient phenotype data for the study of rare disorders. Our source code and a demo version of PhenoTips are available at http://phenotips.org.