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

IF 11.5 2区 生物学 Q1 GENETICS & HEREDITY Genomics, Proteomics & Bioinformatics Pub Date : 2023-04-01 DOI:10.1016/j.gpb.2022.07.005
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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Abstract

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 frequencies, 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/.

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mvPPT:一种用于错义变体的高效、灵敏的致病性预测工具。
下一代测序技术既促进了人类基因组变异的发现,也加剧了致病变异鉴定的挑战。在这项研究中,我们开发了错义变体致病性预测工具(mvPPT),这是一种基于梯度增强的高度敏感和准确的错义变体分类器。mvPPT采用了具有广泛变异谱的高置信度训练集,并提取了三类特征,包括现有预测工具的得分、频率(等位基因频率、氨基酸频率和基因型频率)和基因组背景。与已建立的预测因子相比,无论数据来源如何,mvPPT在所有测试集中都取得了卓越的性能。此外,我们的研究还为训练集和特征选择策略提供了指导,并揭示了高度相关的特征,这可能进一步为变异致病性提供生物学见解。mvPPT可在http://www.mvppt.club/.
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Genomics, Proteomics & Bioinformatics
Genomics, Proteomics & Bioinformatics Biochemistry, Genetics and Molecular Biology-Biochemistry
CiteScore
14.30
自引率
4.20%
发文量
844
审稿时长
61 days
期刊介绍: Genomics, Proteomics and Bioinformatics (GPB) is the official journal of the Beijing Institute of Genomics, Chinese Academy of Sciences / China National Center for Bioinformation and Genetics Society of China. It aims to disseminate new developments in the field of omics and bioinformatics, publish high-quality discoveries quickly, and promote open access and online publication. GPB welcomes submissions in all areas of life science, biology, and biomedicine, with a focus on large data acquisition, analysis, and curation. Manuscripts covering omics and related bioinformatics topics are particularly encouraged. GPB is indexed/abstracted by PubMed/MEDLINE, PubMed Central, Scopus, BIOSIS Previews, Chemical Abstracts, CSCD, among others.
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