VEPerform：一个用于评估不同效果预测器性能的web资源。

ArXiv Pub Date : 2024-12-13

Cindy Zhang, Frederick P Roth

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引用次数: 0

摘要

计算变异效应预测因子（VEPs）为错义变异的致病性分类提供了越来越有力的证据。精确率与召回率分析在评估VEP性能时很有用，特别是在针对不平衡测试集进行调整时。在这里，我们描述了VEPerform，一个基于网络的工具，用于评估vep在基因水平上的表现，使用平衡精度与召回曲线（BPRC）分析。

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VEPerform: a web resource for evaluating the performance of variant effect predictors.

Computational variant effect predictors (VEPs) are providing increasingly strong evidence to classify the pathogenicity of missense variants. Precision vs. recall analysis is useful in evaluating VEP performance, especially when adjusted for imbalanced test sets. Here, we describe VEPerform, a web-based tool for evaluating the performance of VEPs at the gene level using balanced precision vs. recall curve (BPRC) analysis.

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