FUSE:改进功能筛选中变异影响的估计和估算。

IF 11.1 Q1 CELL BIOLOGY Cell genomics Pub Date : 2024-10-09 DOI:10.1016/j.xgen.2024.100667
Tian Yu, James D Fife, Vineel Bhat, Ivan Adzhubey, Richard Sherwood, Christopher A Cassa
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引用次数: 0

摘要

深度突变扫描可对基因变异进行高通量功能评估。虽然筛查测定的表型测量结果通常与临床结果一致,但实验噪音可能会影响单个变异估计的准确性。我们开发了 FUSE(功能替代估算)管道,利用筛查测定中的集体测量来改进对变异影响的估算。FUSE 从 115 项已发表的功能测定中提取数据,评估每个氨基酸位置的平均功能效应,并对单个等位基因变异进行估计。它增强了来自不同检测平台的变体功能效应的相关性,并提高了ClinVar中29个基因的错义变体分类准确性(接收器操作特征曲线[ROC]下面积[AUC]从0.83提高到0.90)。在 BRCA1、LDLR 或 TP53 中存在罕见错义变异的英国生物库患者中,FUSE 提高了相关表型的分类准确性。FUSE 还能对未经实验筛选的置换进行变异效应推算。这种方法提高了准确性,扩大了功能筛选数据的用途。
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FUSE: Improving the estimation and imputation of variant impacts in functional screening.

Deep mutational scanning enables high-throughput functional assessment of genetic variants. While phenotypic measurements from screening assays generally align with clinical outcomes, experimental noise may affect the accuracy of individual variant estimates. We developed the FUSE (functional substitution estimation) pipeline, which leverages measurements collectively within screening assays to improve the estimation of variant impacts. Drawing data from 115 published functional assays, FUSE assesses the mean functional effect per amino acid position and makes estimates for individual allelic variants. It enhances the correlation of variant functional effects from different assay platforms and increases the classification accuracy of missense variants in ClinVar across 29 genes (area under the receiver operating characteristic [ROC] curve [AUC] from 0.83 to 0.90). In UK Biobank patients with rare missense variants in BRCA1, LDLR, or TP53, FUSE improves the classification accuracy of associated phenotypes. FUSE can also impute variant effects for substitutions not experimentally screened. This approach improves accuracy and broadens the utility of data from functional screening.

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