Benjamin J Livesey, Mihaly Badonyi, Mafalda Dias, Jonathan Frazer, Sushant Kumar, Kresten Lindorff-Larsen, David M McCandlish, Rose Orenbuch, Courtney A Shearer, Lara Muffley, Julia Foreman, Andrew M Glazer, Ben Lehner, Debora S Marks, Frederick P Roth, Alan F Rubin, Lea M Starita, Joseph A Marsh
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 to date, and there is tremendous variability in their underlying algorithms and outputs, and in the ways in which the methodologies and predictions are shared. This leads to considerable challenges for end users in knowing which VEPs to use and how to use them...
April 16, 2024: ArXiv