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A Whole-Genome Analysis Framework for Effective Identification of Pathogenic Regulatory Variants in Mendelian Disease.

Authors :
Smedley D
Schubach M
Jacobsen JOB
Köhler S
Zemojtel T
Spielmann M
Jäger M
Hochheiser H
Washington NL
McMurry JA
Haendel MA
Mungall CJ
Lewis SE
Groza T
Valentini G
Robinson PN
Source :
American journal of human genetics [Am J Hum Genet] 2016 Sep 01; Vol. 99 (3), pp. 595-606. Date of Electronic Publication: 2016 Aug 25.
Publication Year :
2016

Abstract

The interpretation of non-coding variants still constitutes a major challenge in the application of whole-genome sequencing in Mendelian disease, especially for single-nucleotide and other small non-coding variants. Here we present Genomiser, an analysis framework that is able not only to score the relevance of variation in the non-coding genome, but also to associate regulatory variants to specific Mendelian diseases. Genomiser scores variants through either existing methods such as CADD or a bespoke machine learning method and combines these with allele frequency, regulatory sequences, chromosomal topological domains, and phenotypic relevance to discover variants associated to specific Mendelian disorders. Overall, Genomiser is able to identify causal regulatory variants as the top candidate in 77% of simulated whole genomes, allowing effective detection and discovery of regulatory variants in Mendelian disease.<br /> (Copyright © 2016 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Details

Language :
English
ISSN :
1537-6605
Volume :
99
Issue :
3
Database :
MEDLINE
Journal :
American journal of human genetics
Publication Type :
Academic Journal
Accession number :
27569544
Full Text :
https://doi.org/10.1016/j.ajhg.2016.07.005