Additional Supporting Information may be found in the online version of this article.
GEnomes Management Application (GEM.app): A New Software Tool for Large-Scale Collaborative Genome Analysis
Article first published online: 3 APR 2013
© 2013 Wiley Periodicals, Inc.
Volume 34, Issue 6, pages 842–846, June 2013
How to Cite
Gonzalez, M. A., Lebrigio, R. F. A., Van Booven, D., Ulloa, R. H., Powell, E., Speziani, F., Tekin, M., Schüle, R. and Züchner, S. (2013), GEnomes Management Application (GEM.app): A New Software Tool for Large-Scale Collaborative Genome Analysis. Hum. Mutat., 34: 842–846. doi: 10.1002/humu.22305
Communicated by Madhuri Hegde
- Issue published online: 20 MAY 2013
- Article first published online: 3 APR 2013
- Accepted manuscript online: 5 MAR 2013 10:26AM EST
- Manuscript Accepted: 17 FEB 2013
- Manuscript Received: 8 JAN 2013
- NINDS. Grant Numbers: 1R01NS075764, 5R01NS052767
- NIH. Grant Number: 1R01NS072248–02S2
- next-generation sequencing;
- exome sequencing;
- next-generation sequencing analysis
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.