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. The web-based tool Genomes Management Application is used in 15 different countries and provides easy to use yet powerful and fast analysis over hundreds of exomes.
| Original language | English |
|---|---|
| Pages (from-to) | 842-846 |
| Number of pages | 5 |
| Journal | Human Mutation |
| Volume | 34 |
| Issue number | 6 |
| DOIs | |
| State | Published - Jun 1 2013 |
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Keywords
- Exome sequencing
- Next-generation sequencing
- Next-generation sequencing analysis
ASJC Scopus subject areas
- Genetics
- Genetics(clinical)
Cite this
GEnomes Management Application (GEM.app) : A New Software Tool for Large-Scale Collaborative Genome Analysis. / Gonzalez, Michael A.; Lebrigio, Rafael F Acosta; Van Booven, Derek; Ulloa, Rick H.; Powell, Eric; Speziani, Fiorella; Tekin, Mustafa; Schüle, Rebecca; Zuchner, Stephan L.
In: Human Mutation, Vol. 34, No. 6, 01.06.2013, p. 842-846.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - GEnomes Management Application (GEM.app)
T2 - A New Software Tool for Large-Scale Collaborative Genome Analysis
AU - Gonzalez, Michael A.
AU - Lebrigio, Rafael F Acosta
AU - Van Booven, Derek
AU - Ulloa, Rick H.
AU - Powell, Eric
AU - Speziani, Fiorella
AU - Tekin, Mustafa
AU - Schüle, Rebecca
AU - Zuchner, Stephan L
PY - 2013/6/1
Y1 - 2013/6/1
N2 - 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. The web-based tool Genomes Management Application is used in 15 different countries and provides easy to use yet powerful and fast analysis over hundreds of exomes.
AB - 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. The web-based tool Genomes Management Application is used in 15 different countries and provides easy to use yet powerful and fast analysis over hundreds of exomes.
KW - Exome sequencing
KW - Next-generation sequencing
KW - Next-generation sequencing analysis
UR - http://www.scopus.com/inward/record.url?scp=84878150143&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84878150143&partnerID=8YFLogxK
U2 - 10.1002/humu.22305
DO - 10.1002/humu.22305
M3 - Article
C2 - 23463597
AN - SCOPUS:84878150143
VL - 34
SP - 842
EP - 846
JO - Human Mutation
JF - Human Mutation
SN - 1059-7794
IS - 6
ER -