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bioRxiv · 10.1101/396655

Divine: Prioritizing Genes for Rare Mendelian Disease in Whole Exome Sequencing Data

Hong, C.·Clemenceau, J. R.·Yeu, Y.·Hwang, T. H.
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Abstract

MotivationRecent studies showed that a phenotype-driven analysis of whole exome sequencing (WES) could provide more accurate and clinically relevant genetic variants.\n\nResultsWe develop a computational tool called Divine that integrates patients phenotype(s) and WES data with 30 prior biological knowledge (e.g., human phenotype ontology, gene ontology, pathway database, protein-protein interaction networks, pathogenicity by the amino acid change due to polymorphism, and hot-spot protein domains) to prioritize potential disease-causing genes. In a retrospective study with 22 real and four simulated data set, Divine ranks the same pathogenic genes confirmed by the original studies 5th on average out of a thousand of mutated genes and outperforms existing state-of-the-art methods.\n\nAvailabilityhttps://github.com/hwanglab/divine\n\nContacthwangt@ccf.org\n\nSupplementary informationSupplementary Document is attached at the end of the page.

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Hong, C., Clemenceau, J. R., Yeu, Y., Hwang, T. H.. 2018-08-21. Divine: Prioritizing Genes for Rare Mendelian Disease in Whole Exome Sequencing Data. https://doi.org/10.1101/396655

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