Phrank measures phenotype sets similarity to greatly improve Mendelian diagnostic disease prioritization.

Autor: Jagadeesh KA; Department of Computer Science, Stanford University, Stanford, California, 94305, USA., Birgmeier J; Department of Computer Science, Stanford University, Stanford, California, 94305, USA., Guturu H; Department of Pediatrics, Stanford University, Stanford, California, 94305, USA., Deisseroth CA; Department of Computer Science, Stanford University, Stanford, California, 94305, USA., Wenger AM; Department of Pediatrics, Stanford University, Stanford, California, 94305, USA., Bernstein JA; Department of Pediatrics, Stanford University, Stanford, California, 94305, USA., Bejerano G; Department of Computer Science, Stanford University, Stanford, California, 94305, USA. bejerano@stanford.edu.; Department of Pediatrics, Stanford University, Stanford, California, 94305, USA. bejerano@stanford.edu.; Department of Developmental Biology, Stanford University, Stanford, California, 94305, USA. bejerano@stanford.edu.
Jazyk: angličtina
Zdroj: Genetics in medicine : official journal of the American College of Medical Genetics [Genet Med] 2019 Feb; Vol. 21 (2), pp. 464-470. Date of Electronic Publication: 2018 Jul 12.
DOI: 10.1038/s41436-018-0072-y
Abstrakt: Purpose: Exome sequencing and diagnosis is beginning to spread across the medical establishment. The most time-consuming part of genome-based diagnosis is the manual step of matching the potentially long list of patient candidate genes to patient phenotypes to identify the causative disease.
Methods: We introduce Phrank (for phenotype ranking), an information theory-inspired method that utilizes a Bayesian network to prioritize candidate diseases or genes, as a stand-alone module that can be run with any underlying knowledgebase and any variant filtering scheme.
Results: Phrank outperforms existing methods at ranking the causative disease or gene when applied to 169 real patient exomes with Mendelian diagnoses. Phrank's greatest improvement is in disease space, where across all 169 patients it ranks only 3 diseases on average ahead of the true diagnosis, whereas Phenomizer ranks 32 diseases ahead of the causal one.
Conclusions: Using Phrank to rank all patient candidate genes or diseases, as they start working through a new case, will save the busy clinician much time in deriving a genetic diagnosis.
Databáze: MEDLINE
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