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Am J Hum Genet. 2016 Sep 1;99(3):595-606. doi: 10.1016/j.ajhg.2016.07.005. Epub 2016 Aug 25.

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

Author information

1
Queen Mary University of London, London E1 4NS, UK; Genomics England Ltd., London EC1M 6BQ, UK.
2
Institute for Medical and Human Genetics, Charité-Universitätsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Germany.
3
Skarnes Faculty Group, Wellcome Trust Sanger Institute, Hinxton CB10 1SA, UK.
4
Institute for Medical and Human Genetics, Charité-Universitätsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Germany; Institute of Bioorganic Chemistry, Polish Academy of Sciences, 61-704 Poznan, Poland.
5
Institute for Medical and Human Genetics, Charité-Universitätsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Germany; Max Planck Institute for Molecular Genetics, Ihnestr. 63-73, 14195 Berlin, Germany.
6
Institute for Medical and Human Genetics, Charité-Universitätsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Germany; Berlin-Brandenburg Center for Regenerative Therapies (BCRT), Charité-Universitätsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Germany.
7
Department of Biomedical Informatics and Intelligent Systems Program, University of Pittsburgh, Pittsburgh, PA 15206, USA.
8
Division of Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.
9
Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR 97239, USA.
10
Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Darlinghurst, NSW 2010, Australia; St Vincent's Clinical School, Faculty of Medicine University of New South Wales, Darlinghurst, NSW 2010, Australia.
11
Anacleto Lab Department of Computer Science, University of Milan, Via Comelico, 20135 Milan, Italy.
12
Institute for Medical and Human Genetics, Charité-Universitätsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Germany; Max Planck Institute for Molecular Genetics, Ihnestr. 63-73, 14195 Berlin, Germany; Berlin-Brandenburg Center for Regenerative Therapies (BCRT), Charité-Universitätsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Germany; Institute for Bioinformatics, Department of Mathematics and Computer Science, Freie Universität Berlin, Takustrasse, 14195 Berlin, Germany. Electronic address: peter.robinson@jax.org.

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.

PMID:
27569544
PMCID:
PMC5011059
[Available on 2017-03-01]
DOI:
10.1016/j.ajhg.2016.07.005
[Indexed for MEDLINE]
Free PMC Article

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