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

Damian Smedley, Julius O.B. Jacobsen, Marten Jäger, Sebastian Köhler, Manuel Holtgrewe, Max Schubach, Enrico Siragusa, Tomasz Zemojtel, Orion J. Buske, Nicole L. Washington, William P. Bone, Melissa A. Haendel, Peter N. Robinson

Research output: Contribution to journalArticle

85 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)2004-2015
Number of pages12
JournalNature protocols
Volume10
Issue number12
DOIs
StatePublished - Dec 1 2015

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)

Fingerprint Dive into the research topics of 'Next-generation diagnostics and disease-gene discovery with the Exomiser'. Together they form a unique fingerprint.

  • Cite this

    Smedley, D., Jacobsen, J. O. B., Jäger, M., Köhler, S., Holtgrewe, M., Schubach, M., Siragusa, E., Zemojtel, T., Buske, O. J., Washington, N. L., Bone, W. P., Haendel, M. A., & Robinson, P. N. (2015). Next-generation diagnostics and disease-gene discovery with the Exomiser. Nature protocols, 10(12), 2004-2015. https://doi.org/10.1038/nprot.2015.124