フルテキストファイル
著者
Ebiki, Matsutaka The Development of Innovative Future Medical Treatment, Graduate School of Medical Sciences, Tottori University
Okazaki, Tetsuya Division of Child Neurology, Department of Brain and Neurosciences, School of Medicine, Tottori University Faculty of Medicine / Division of Clinical Genetics, Tottori University Hospital / Technical Department, Tottori University 研究者総覧 KAKEN
Kai, Masachika Research Initiative Center, Organization for Research Initiative and Promotion, Tottori University
Adachi, Kaori Research Strategy Division, Organization for Research Initiative and Promotion, Tottori University 研究者総覧 KAKEN
Namba, Eiji Division of Clinical Genetics, Tottori University Hospital / Technical Department, Tottori University / Research Strategy Division, Organization for Research Initiative and Promotion, Tottori University 研究者総覧 KAKEN
キーワード
computational biology
databases
genetic
whole exome sequencing
抄録
Background: During 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.
Methods: We 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 1000 Genomes Project. The later “in-house” study used exome data from 20 Japanese patients with Mendelian disorders. In both studies, we utilized 1-5 terms of “Human Phenotype Ontology” as clinical information.
Results: In 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.
Conclusion: The 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.
出版者
Tottori University Medical Press
資料タイプ
学術雑誌論文
外部リンク
ISSN・ISBN
05135710
書誌ID
AA00892882
掲載誌名
Yonago Acta Medica
最新掲載誌名
Yonago Acta Medica
62
3
開始ページ
244
終了ページ
252
Original Article
発行日
2019-09-13
出版者DOI
著者版フラグ
出版社版
著作権表記
注があるものを除き、この著作物は日本国著作権法により保護されています。 / This work is protected under Japanese Copyright Law unless otherwise noted.
掲載情報
Ebiki M, Okazaki T, Kai M, Adachi K, Nanba E. Comparison of Causative Variant Prioritization Tools Using Next-generation Sequencing Data in Japanese Patients with Mendelian Disorders. Yonago Acta Medica. 2019;62:244-252.
部局名
医学部・医学系研究科・医学部附属病院
言語
英語