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Nat Protoc. 2015 Dec;10(12):2004-15. doi: 10.1038/nprot.2015.124. Epub 2015 Nov 12.

Next-generation diagnostics and disease-gene discovery with the Exomiser.

Author information

1
Skarnes Faculty Group, Wellcome Trust Sanger Institute, Hinxton, UK.
2
Institute for Medical and Human Genetics, Charité-Universitätsmedizin Berlin, Berlin, Germany.
3
Berlin Brandenburg Center for Regenerative Therapies (BCRT), Charité-Universitätsmedizin Berlin, Berlin, Germany.
4
Berlin Institute for Health, Berlin, Germany.
5
Max Planck Institute for Molecular Genetics, Berlin, Germany.
6
Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, Poland.
7
Labor Berlin - Charité Vivantes, Humangenetik, Berlin, Germany.
8
Department of Computer Science, University of Toronto, Toronto, Ontario, Canada.
9
Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada.
10
Division of Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, California, USA.
11
The National Institutes of Health (NIH) Undiagnosed Diseases Program, Common Fund, Office of the Director, NIH, Bethesda, Maryland, USA.
12
Department of Medical Informatics and Clinical Epidemiology, Oregon Health &Science University, Portland, Oregon, USA.
13
Department of Mathematics and Computer Science, Institute for Bioinformatics, Freie Universität Berlin, Berlin, Germany.

Abstract

Exomiser is an application that prioritizes genes and variants in next-generation sequencing (NGS) projects for novel disease-gene discovery or differential diagnostics of Mendelian disease. Exomiser comprises a suite of algorithms for prioritizing exome sequences using random-walk analysis of protein interaction networks, clinical relevance and cross-species phenotype comparisons, as well as a wide range of other computational filters for variant frequency, predicted pathogenicity and pedigree analysis. In this protocol, we provide a detailed explanation of how to install Exomiser and use it to prioritize exome sequences in a number of scenarios. Exomiser requires ∼3 GB of RAM and roughly 15-90 s of computing time on a standard desktop computer to analyze a variant call format (VCF) file. Exomiser is freely available for academic use from http://www.sanger.ac.uk/science/tools/exomiser.

PMID:
26562621
PMCID:
PMC5467691
DOI:
10.1038/nprot.2015.124
[Indexed for MEDLINE]
Free PMC Article

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