首页|mvPPT:A Highly Efficient and Sensitive Pathogenicity Prediction Tool for Missense Variants

mvPPT:A Highly Efficient and Sensitive Pathogenicity Prediction Tool for Missense Variants

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Next-generation sequencing technologies both boost the discovery of variants in the human genome and exacerbate the challenges of pathogenic variant identification.In this study,we developed Pathogenicity Prediction Tool for missense variants(mvPPT),a highly sensitive and accurate missense variant classifier based on gradient boosting.mvPPT adopts high-confidence training sets with a wide spectrum of variant profiles,and extracts three categories of features,including scores from existing prediction tools,frequencies(allele frequencies,amino acid frequen-cies,and genotype frequencies),and genomic context.Compared with established predictors,mvPPT achieves superior performance in all test sets,regardless of data source.In addition,our study also provides guidance for training set and feature selection strategies,as well as reveals highly relevant features,which may further provide biological insights into variant pathogenicity.mvPPT is freely available at http://www.mvppt.club/.

Machine learningMissense variantGenomicsComputational biologyPathogenicity prediction

Shi-Yuan Tong、Ke Fan、Zai-Wei Zhou、Lin-Yun Liu、Shu-Qing Zhang、Yinghui Fu、Guang-Zhong Wang、Ying Zhu、Yong-Chun Yu

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Jing'an District Central Hospital of Shanghai,State Key Laboratory of Medical Neurobiology,MOE Frontiers Center for Brain Science,Institutes of Brain Science,Fudan University,Shanghai 200032,China

Shanghai Xunyin Biotechnology Co.,Ltd.,Shanghai 201802,China

CAS Key Laboratory of Computational Biology,Shanghai Institute of Nutrition and Health,University of Chinese Academy of Sciences,Chinese Academy of Sciences,Shanghai 200031,China

Huashan Hospital,State Key Laboratory of Medical Neurobiology,MOE Frontiers Center for Brain Science,Institutes of Brain Science,Fudan University,Shanghai 200032,China

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National Key R&D Program of ChinaShanghai Natural Science Foundation,ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaShanghai Municipal Science and Technology Major ProjectZJ LabShanghai Center for Brain Science and Brain-Inspired Technology,ChinaFoundation of Shanghai Municipal Education Commission,ChinaCollaborative Innovation Program of Shanghai Municipal Health Commission,China

2021ZD020250020ZR1403800319004768207125931930044317250122018SHZDZX012019-01-07-00-07-E000622020CXJQ01

2023

10.1016/j.gpb.2022.07.005

基因组蛋白质组与生物信息学报(英文版)
中国科学院北京基因组研究所

基因组蛋白质组与生物信息学报(英文版)

CSTPCDCSCD
影响因子：0.495
ISSN：1672-0229
年,卷(期)：2023.21(2)
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