Please use this identifier to cite or link to this item: https://doi.org/10.1038/s41431-019-0412-7
Title: Specific phenotype semantics facilitate gene prioritization in clinical exome sequencing
Authors: Tomar, S 
Sethi, R
Lai, PS 
Keywords: Genetic Association Studies
Genetic Predisposition to Disease
Humans
Phenotype
ROC Curve
Semantics
Whole Exome Sequencing
Issue Date: 1-Sep-2019
Publisher: Springer Science and Business Media LLC
Citation: Tomar, S, Sethi, R, Lai, PS (2019-09-01). Specific phenotype semantics facilitate gene prioritization in clinical exome sequencing. European Journal of Human Genetics 27 (9) : 1389-1397. ScholarBank@NUS Repository. https://doi.org/10.1038/s41431-019-0412-7
Abstract: © 2019, European Society of Human Genetics. Selection and prioritization of phenotype-centric variants remains a challenging part of variant analysis and interpretation in clinical exome sequencing. Phenotype-driven shortlisting of patient-specific gene lists can avoid missed diagnosis. Here, we analyzed the relevance of using primary Human Phenotype Ontology identifiers (HPO IDs) in prioritizing Mendelian disease genes across 30 in-house, 10 previously reported, and 10 recently published cases using three popular web-based gene prioritization tools (OMIMExplorer, VarElect & Phenolyzer). We assessed partial HPO-based gene prioritization using randomly chosen and top 10%, 30%, and 50% HPO IDs based on information content and found high variance within rank ratios across the former vs the latter. This signified that randomly selected less-specific HPO IDs for a given disease phenotype performed poorly by ranking probe gene farther away from the top rank. In contrast, the use of top 10%, 30%, and 50% HPO IDs individually could rank the probe gene among the top 1% in the ranked list of genes that was equivalent to the results when the full list of HPO IDs were used. Hence, we conclude that use of just the top 10% of HPO IDs chosen based on information content is sufficient for ranking the probe gene at top position. Our findings provide practical guidance for utilizing structured phenotype semantics and web-based gene-ranking tools to aid in identifying known as well unknown candidate gene associations in Mendelian disorders.
Source Title: European Journal of Human Genetics
URI: https://scholarbank.nus.edu.sg/handle/10635/173673
ISSN: 10184813
14765438
DOI: 10.1038/s41431-019-0412-7
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