GEnomes Management Application (GEM.app): A New Software Tool for Large-Scale Collaborative Genome Analysis

Authors

  • Michael A. Gonzalez,

    1. Dr. John T. Macdonald Foundation Department of Human Genetics and John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, Florida
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  • Rafael F. Acosta Lebrigio,

    1. Dr. John T. Macdonald Foundation Department of Human Genetics and John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, Florida
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  • Derek Van Booven,

    1. Dr. John T. Macdonald Foundation Department of Human Genetics and John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, Florida
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  • Rick H. Ulloa,

    1. Dr. John T. Macdonald Foundation Department of Human Genetics and John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, Florida
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  • Eric Powell,

    1. Dr. John T. Macdonald Foundation Department of Human Genetics and John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, Florida
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  • Fiorella Speziani,

    1. Dr. John T. Macdonald Foundation Department of Human Genetics and John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, Florida
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  • Mustafa Tekin,

    1. Dr. John T. Macdonald Foundation Department of Human Genetics and John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, Florida
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  • Rebecca Schüle,

    1. Department of Neurodegenerative Disease, Hertie-Institute for Clinical Brain Research and Center for Neurology, Tübingen, Germany
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  • Stephan Züchner

    Corresponding author
    • Dr. John T. Macdonald Foundation Department of Human Genetics and John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, Florida
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  • Additional Supporting Information may be found in the online version of this article.

  • Communicated by Madhuri Hegde

Correspondence to: Stephan Züchner, University of Miami Miller School of Medicine Biomedical Research Building (BRB) Room 523, LC: M-860, 1501 NW 10th Avenue, Miami, FL 33136. E-mail: szuchner@med.miami.edu

ABSTRACT

Novel genes are now identified at a rapid pace for many Mendelian disorders, and increasingly, for genetically complex phenotypes. However, new challenges have also become evident: (1) effectively managing larger exome and/or genome datasets, especially for smaller labs; (2) direct hands-on analysis and contextual interpretation of variant data in large genomic datasets; and (3) many small and medium-sized clinical and research-based investigative teams around the world are generating data that, if combined and shared, will significantly increase the opportunities for the entire community to identify new genes. To address these challenges, we have developed GEnomes Management Application (GEM.app), a software tool to annotate, manage, visualize, and analyze large genomic datasets (https://genomics.med.miami.edu/">https://genomics.med.miami.edu/">https://genomics.med.miami.edu/). GEM.app currently contains ∼1,600 whole exomes from 50 different phenotypes studied by 40 principal investigators from 15 different countries. The focus of GEM.app is on user-friendly analysis for nonbioinformaticians to make next-generation sequencing data directly accessible. Yet, GEM.app provides powerful and flexible filter options, including single family filtering, across family/phenotype queries, nested filtering, and evaluation of segregation in families. In addition, the system is fast, obtaining results within 4 sec across ∼1,200 exomes. We believe that this system will further enhance identification of genetic causes of human disease.

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