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

Shihab, H. A., Rogers, M. F., Gough, J., Mort, Matthew, Cooper, David Neil, Day, I. N. M., Gaunt, T. R. and Campbell, C. 2015. An integrative approach to predicting the functional effects of non-coding and coding sequence variation. Bioinformatics 31 (10) , pp. 1536-1543. 10.1093/bioinformatics/btv009

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Abstract

Motivation: Technological advances have enabled the identification of an increasingly large spectrum of single nucleotide variants within the human genome, many of which may be associated with monogenic disease or complex traits. Here, we propose an integrative approach, named FATHMM-MKL, to predict the functional consequences of both coding and non-coding sequence variants. Our method utilizes various genomic annotations, which have recently become available, and learns to weight the significance of each component annotation source. Results: 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.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Medicine
Subjects: Q Science > QH Natural history > QH426 Genetics
Publisher: Oxford University Press
ISSN: 1367-4803
Date of First Compliant Deposit: 30 March 2016
Date of Acceptance: 5 January 2015
Last Modified: 21 Jun 2019 20:56
URI: http://orca.cf.ac.uk/id/eprint/84066

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