An integrative approach to predicting the functional effects of non-coding and coding sequence variation

2015733 citationsJournal Articlehybrid Open Access

Authors

Hashem A. Shihab · University of Bristol

Mark F. Rogers · University of Bristol

Julian Gough · University of Bristol

Matthew Mort · University of Bristol

D.N. Cooper · University of Bristol

Ian N.M. Day · University of Bristol

Tom R. Gaunt ·

Abstract

We show that our method outperforms current state-of-the-art algorithms, CADD and GWAVA, when predicting the functional consequences of non-coding variants. In addition, FATHMM-MKL is comparable to the best of these algorithms when predicting the impact of coding variants. The method includes a confidence measure to rank order predictions.

Topics & Keywords

Genomics and Phylogenetic Studies Genomics and Rare Diseases Genetic Associations and Epidemiology

UN Sustainable Development Goals

Partnerships for the goals

Publication Details

Published in: Bioinformatics

Volume 31, Issue 10, pp. 1536-1543

DOI: 10.1093/bioinformatics/btv009

Field-Weighted Citation Impact: 23.35