Protocol

Genomic variant annotation and prioritization with ANNOVAR and wANNOVAR

  • Nature Protocols volume 10, pages 15561566 (2015)
  • doi:10.1038/nprot.2015.105
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Abstract

Recent developments in sequencing techniques have enabled rapid and high-throughput generation of sequence data, democratizing the ability to compile information on large amounts of genetic variations in individual laboratories. However, there is a growing gap between the generation of raw sequencing data and the extraction of meaningful biological information. Here, we describe a protocol to use the ANNOVAR (ANNOtate VARiation) software to facilitate fast and easy variant annotations, including gene-based, region-based and filter-based annotations on a variant call format (VCF) file generated from human genomes. We further describe a protocol for gene-based annotation of a newly sequenced nonhuman species. Finally, we describe how to use a user-friendly and easily accessible web server called wANNOVAR to prioritize candidate genes for a Mendelian disease. The variant annotation protocols take 5–30 min of computer time, depending on the size of the variant file, and 5–10 min of hands-on time. In summary, through the command-line tool and the web server, these protocols provide a convenient means to analyze genetic variants generated in humans and other species.

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Acknowledgements

Development of the ANNOVAR/wANNOVAR tool is supported by US National Institutes of Health (NIH) grant R01 HG006465. We thank X. Chang for the initial development of the wANNOVAR server. We thank all ANNOVAR and wANNOVAR users for their helpful suggestions, comments and bug reports to improve the software tools and web servers.

Author information

Affiliations

  1. Zilkha Neurogenetic Institute, University of Southern California, Los Angeles, California, USA.

    • Hui Yang
    •  & Kai Wang
  2. Neuroscience Graduate Program, University of Southern California, Los Angeles, California, USA.

    • Hui Yang
  3. Department of Psychiatry, University of Southern California, Los Angeles, California, USA.

    • Kai Wang
  4. Department of Preventive Medicine, Division of Bioinformatics, University of Southern California, Los Angeles, California, USA.

    • Kai Wang

Authors

  1. Search for Hui Yang in:

  2. Search for Kai Wang in:

Contributions

H.Y. and K.W. drafted and revised this manuscript.

Competing interests

K.W. is a shareholder and board member of Tute Genomics.

Corresponding author

Correspondence to Kai Wang.

Integrated supplementary information

Supplementary information

PDF files

  1. 1.

    Supplementary Text and Figures

    Supplementary Figures 1 and 2, Supplementary Tables 1–3

Excel files

  1. 1.

    Supplementary Data

    ANNOVAR and VEP comparison results

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