Rhapsody: predicting the pathogenicity of human missense variants.

ABSTRACT:

Motivation

The biological effects of human missense variants have been studied experimentally for decades but predicting their effects in clinical molecular diagnostics remains challenging. Available computational tools are usually based on the analysis of sequence conservation and structural properties of the mutant protein. We recently introduced a new machine learning method that demonstrated for the first time the significance of protein dynamics in determining the pathogenicity of missense variants.

Results

Here, we present a new interface (Rhapsody) that enables fully automated assessment of pathogenicity, incorporating both sequence coevolution data and structure- and dynamics-based features. Benchmarked against a dataset of about 20 000 annotated variants, the method

SUBMITTER: Ponzoni L 

PROVIDER: S-EPMC7214033 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature