Livesey Benjamin J, Badonyi Mihaly, Dias Mafalda, Frazer Jonathan, Kumar Sushant, Lindorff-Larsen Kresten, McCandlish David M, Orenbuch Rose, Shearer Courtney A, Muffley Lara, Foreman Julia, Glazer Andrew M, Lehner Ben, Marks Debora S, Roth Frederick P, Rubin Alan F, Starita Lea M, Marsh Joseph A
MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain.
Genome Biol. 2025 Apr 15;26(1):97. doi: 10.1186/s13059-025-03572-z.
Computational methods for assessing the likely impacts of mutations, known as variant effect predictors (VEPs), are widely used in the assessment and interpretation of human genetic variation, as well as in other applications like protein engineering. Many different VEPs have been released, and there is tremendous variability in their underlying algorithms, outputs, and the ways in which the methodologies and predictions are shared. This leads to considerable difficulties for users trying to navigate the selection and application of VEPs. Here, to address these issues, we provide guidelines and recommendations for the release of novel VEPs.
用于评估突变可能影响的计算方法,即变异效应预测器(VEP),广泛应用于人类遗传变异的评估和解读,以及蛋白质工程等其他应用中。已经发布了许多不同的VEP,其基础算法、输出结果以及方法和预测的共享方式存在巨大差异。这给试图选择和应用VEP的用户带来了相当大的困难。在此,为解决这些问题,我们为新型VEP的发布提供指导方针和建议。