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

Nature Protocols volume 10, pages 2004–2015 (2015)Cite this article

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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.

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Figure 1: Overview of the processing steps of Exomiser.
Figure 2: Choice of Exomiser prioritization method.
Figure 3: Screenshot of Exomiser output.

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Acknowledgements

This project was supported by the Bundesministerium für Bildung und Forschung (BMBF; project no. 0313911), the European Community's Seventh Framework Programme (grant agreement no. 602300; SYBIL) and NIH grant no. 5R24OD011883 (Monarch Initiative).

Author information

Author notes

  1. Damian Smedley and Julius O B Jacobsen: These authors jointly directed this work.

Authors and Affiliations

  1. Skarnes Faculty Group, Wellcome Trust Sanger Institute, Hinxton, UK

    Damian Smedley & Julius O B Jacobsen

  2. Institute for Medical and Human Genetics, Charité-Universitätsmedizin Berlin, Berlin, Germany

    Marten Jäger, Sebastian Köhler, Manuel Holtgrewe, Max Schubach, Enrico Siragusa, Tomasz Zemojtel & Peter N Robinson

  3. Berlin Brandenburg Center for Regenerative Therapies (BCRT), Charité-Universitätsmedizin Berlin, Berlin, Germany

    Marten Jäger & Peter N Robinson

  4. Berlin Institute for Health, Berlin, Germany

    Manuel Holtgrewe & Enrico Siragusa

  5. Max Planck Institute for Molecular Genetics, Berlin, Germany

    Enrico Siragusa & Peter N Robinson

  6. Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, Poland

    Tomasz Zemojtel

  7. Labor Berlin - Charité Vivantes, Humangenetik, Berlin, Germany

    Tomasz Zemojtel

  8. Department of Computer Science, University of Toronto, Toronto, Ontario, Canada

    Orion J Buske

  9. Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada

    Orion J Buske

  10. Division of Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, California, USA

    Nicole L Washington

  11. The National Institutes of Health (NIH) Undiagnosed Diseases Program, Common Fund, Office of the Director, NIH, Bethesda, Maryland, USA

    William P Bone

  12. Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, Oregon, USA

    Melissa A Haendel

  13. Department of Mathematics and Computer Science, Institute for Bioinformatics, Freie Universität Berlin, Berlin, Germany

    Peter N Robinson

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  1. Damian Smedley
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Contributions

P.N.R. and D.S. conceived of the project, programmed the prototype code, and wrote the manuscript. J.O.B.J., M.J., S.K., M.S., N.L.W. and E.S. developed software. T.Z., O.J.B. and W.P.B. tested code and contributed to the development of analysis strategies. S.K., M.A.H. and P.N.R. developed the phenotype analysis framework. M.A.H. helped develop the ontologies and the HPO curation standard. All authors reviewed and approved of the manuscript.

Corresponding author

Correspondence to Peter N Robinson.

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Competing interests

S.K. and P.N.R. are holders of a patent for an ontology-based search methodology.

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Smedley, D., Jacobsen, J., Jäger, M. et al. Next-generation diagnostics and disease-gene discovery with the Exomiser. Nat Protoc 10, 2004–2015 (2015). https://doi.org/10.1038/nprot.2015.124

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