Variant Impact Predictor database (VIPdb), version 2: trends from three decades of genetic variant impact predictors.

IF 3.8 3区 医学 Q2 GENETICS & HEREDITY
Yu-Jen Lin, Arul S Menon, Zhiqiang Hu, Steven E Brenner
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引用次数: 0

Abstract

Background: Variant interpretation is essential for identifying patients' disease-causing genetic variants amongst the millions detected in their genomes. Hundreds of Variant Impact Predictors (VIPs), also known as Variant Effect Predictors (VEPs), have been developed for this purpose, with a variety of methodologies and goals. To facilitate the exploration of available VIP options, we have created the Variant Impact Predictor database (VIPdb).

Results: The Variant Impact Predictor database (VIPdb) version 2 presents a collection of VIPs developed over the past three decades, summarizing their characteristics, ClinGen calibrated scores, CAGI assessment results, publication details, access information, and citation patterns. We previously summarized 217 VIPs and their features in VIPdb in 2019. Building upon this foundation, we identified and categorized an additional 190 VIPs, resulting in a total of 407 VIPs in VIPdb version 2. The majority of the VIPs have the capacity to predict the impacts of single nucleotide variants and nonsynonymous variants. More VIPs tailored to predict the impacts of insertions and deletions have been developed since the 2010s. In contrast, relatively few VIPs are dedicated to the prediction of splicing, structural, synonymous, and regulatory variants. The increasing rate of citations to VIPs reflects the ongoing growth in their use, and the evolving trends in citations reveal development in the field and individual methods.

Conclusions: VIPdb version 2 summarizes 407 VIPs and their features, potentially facilitating VIP exploration for various variant interpretation applications. VIPdb is available at  https://genomeinterpretation.org/vipdb.

变异影响预测数据库(VIPdb),第 2 版:三十年来遗传变异影响预测的趋势。
背景:变异解读对于从患者基因组中检测到的数百万个基因变异中识别出患者的致病基因变异至关重要。为此,人们开发了数百种变异影响预测器(VIP),也称为变异效应预测器(VEP),其方法和目标各不相同。为了便于探索可用的 VIP 选项,我们创建了变体影响预测因子数据库(VIPdb):变异影响预测因子数据库(VIPdb)第 2 版汇集了过去 30 年间开发的 VIP,总结了它们的特点、ClinGen 校准分数、CAGI 评估结果、出版详情、访问信息和引用模式。我们曾在 2019 年的 VIPdb 中总结了 217 项 VIP 及其特征。在此基础上,我们又识别并分类了 190 个要人,从而使 VIPdb 第 2 版中的要人总数达到 407 个。大多数 VIP 都能预测单核苷酸变异和非同义变异的影响。自 2010 年代以来,已开发出更多专门用于预测插入和缺失影响的 VIP。相比之下,专门预测剪接、结构、同义和调控变异的VIP相对较少。VIPs的引用率不断上升反映了其使用的持续增长,而引用率的变化趋势则揭示了该领域和个别方法的发展:VIPdb第2版总结了407个VIP及其特征,为各种变异解释应用中的VIP探索提供了潜在的便利。VIPdb可在https://genomeinterpretation.org/vipdb。
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来源期刊
Human Genomics
Human Genomics GENETICS & HEREDITY-
CiteScore
6.00
自引率
2.20%
发文量
55
审稿时长
11 weeks
期刊介绍: Human Genomics is a peer-reviewed, open access, online journal that focuses on the application of genomic analysis in all aspects of human health and disease, as well as genomic analysis of drug efficacy and safety, and comparative genomics. Topics covered by the journal include, but are not limited to: pharmacogenomics, genome-wide association studies, genome-wide sequencing, exome sequencing, next-generation deep-sequencing, functional genomics, epigenomics, translational genomics, expression profiling, proteomics, bioinformatics, animal models, statistical genetics, genetic epidemiology, human population genetics and comparative genomics.
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