DrivR-Base: a feature extraction toolkit for variant effect prediction
Understanding which genetic variants are likely to be functional (and which are probably benign) is a cornerstone of modern human genetics. Over the last decade, variant-effect predictors have become increasingly sophisticated — but behind every model sits the same practical headache: assembling a sensible set of features (annotations) for millions of variants from dozens of databases.
In a 2024 Bioinformatics paper led by Amy Francis, we introduce DrivR-Base, a reproducible, Dockerised toolkit that turns this feature-extraction step into something you can run and re-run with far less pain.