Joseph A. Marsh

Combining MAVEs and computational predictors improves variant classification across ancestries in hereditary cancer genes

Many commonly used computational tools for variant effect prediction exhibit ancestry-related bias because they are trained on clinical or population datasets that under-represent global diversity, leading to uneven and sometimes unfair variant classification across ancestries. M...

Why variant effect predictors and multiplexed assays agree and disagree

Abstract Computational variant effect predictors (VEPs) and multiplexed assays of variant effect (MAVEs) are two key tools for assessing the functional consequences of genetic variants. While their outputs are often concordant, there are also many differences. Here, we analyse mi...