ArticleYonago acta medica2019
Comparison of Causative Variant Prioritization Tools Using Next-generation Sequencing Data in Japanese Patients with Mendelian Disorders.
Article in Yonago acta medica, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed.
- Towards a standard benchmark for phenotype-driven variant and gene prioritisation algorithms: PhEval - Phenotypic inference Evaluation framework.BMC bioinformatics · 2025Article
- Article
- Evaluating seven bioinformatics platforms for tertiary analysis of genomic data from whole exome sequencing in a pilot group of patients.Advances in laboratory medicine · 2025Article
- Biliary atresia is associated with polygenic susceptibility in ciliogenesis and planar polarity effector genes.Journal of hepatology · 2023Article
- Evaluation of phenotype-driven gene prioritization methods for Mendelian diseases.Briefings in bioinformatics · 2022Article
- Interpretable Clinical Genomics with a Likelihood Ratio Paradigm.American journal of human genetics · 2020Article
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Abstract
backgroundDuring the investigation of causative variants of Mendelian disorders using next-generation sequencing, the enormous number of possible candidates makes the detection process complex, and the use of multidimensional methods is required. Although the utility of several variant prioritization tools has been reported, their effectiveness in Japanese patients remains largely unknown.
methodsWe selected 5 free variant prioritization tools (PhenIX, hiPHIVE, Phen-Gen, eXtasy-order statistics, and eXtasy-combined max) and assessed their effectiveness in Japanese patient populations. To compare these tools, we conducted 2 studies: one based on simulated data of 100 diseases and another based on the exome data of 20 in-house patients with Mendelian disorders. To this end we selected 100 pathogenic variants from the "Database of Pathogenic Variants (DPV)" and created 100 variant call format (VCF) files that each had pathogenic variants based on reference human genome data from the
resultsIn our analysis based on simulated disease data, the detection rate of the top 10 causative variants was 91% for hiPHIVE, and 88% for PhenIX, based on 100 sets of simulated disease VCF data. Also, both software packages detected 82% of the top 1 causative variants. When we used data from our in-house patients instead, we found that these two programs (PhenIX and hiPHIVE) produced higher detection rates than the other three systems in our study. The detection rate of the top 1 causative variant was 71.4% for PhenIX, 65.0% for hiPHIVE.
conclusionThe rates of detecting causative variants in two Exomizer software packages, hiPHIVE and PhenIX, were higher than for the other three software systems we analyzed, with respect to Japanese patients.
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