A new score classifying dominant disease-causing mutations has found that just over half act via loss of function, with gain-of-function and dominant-negative mechanisms making up the rest.

Provides a function to calibrate variant effect scores against evidence strength categories defined by the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) guidelines. The method computes likelihood ratios of pathogenicity via kernel density estimation of pathogenic and benign score distributions, and derives score intervals corresponding to ACMG/AMP evidence levels. This enables researchers and clinical geneticists to interpret functional and computational variant scores in a reproducible and standardised manner. For details, see Badonyi and Marsh (2025) &lt;<a href="https://doi.org/10.1093%2Fbioinformatics%2Fbtaf503" target="_top">doi:10.1093/bioinformatics/btaf503</a>&gt;.

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...