Genepanel.iobio - an easy to use web tool for generating disease- and phenotype-associated gene lists

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作者
Aditya Ekawade
Matt Velinder
Alistair Ward
Tonya DiSera
Chase Miller
Yi Qiao
Gabor Marth
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[1] University of Utah School of Medicine,USTAR Center for Genetic Discovery, Department of Human Genetics
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BMC Medical Genomics | / 12卷
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When ordering genetic testing or triaging candidate variants in exome and genome sequencing studies, it is critical to generate and test a comprehensive list of candidate genes that succinctly describe the complete and objective phenotypic features of disease. Significant efforts have been made to curate gene:disease associations both in academic research and commercial genetic testing laboratory settings. However, many of these valuable resources exist as islands and must be used independently, generating static, single-resource gene:disease association lists. Here we describe genepanel.iobio (https://genepanel.iobio.io) an easy to use, free and open-source web tool for generating disease- and phenotype-associated gene lists from multiple gene:disease association resources, including the NCBI Genetic Testing Registry (GTR), Phenolyzer, and the Human Phenotype Ontology (HPO). We demonstrate the utility of genepanel.iobio by applying it to complex, rare and undiagnosed disease cases that had reached a diagnostic conclusion. We find that genepanel.iobio is able to correctly prioritize the gene containing the diagnostic variant in roughly half of these challenging cases. Importantly, each component resource contributed diagnostic value, showing the benefits of this aggregate approach. We expect genepanel.iobio will improve the ease and diagnostic value of generating gene:disease association lists for genetic test ordering and whole genome or exome sequencing variant prioritization.
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  • [1] Genepanel.iobio - an easy to use web tool for generating disease- and phenotype-associated gene lists
    Ekawade, Aditya
    Velinder, Matt
    Ward, Alistair
    DiSera, Tonya
    Miller, Chase
    Qiao, Yi
    Marth, Gabor
    BMC MEDICAL GENOMICS, 2019, 12 (01)