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dc.contributor.author
Koile, Daniel Isaac  
dc.contributor.author
Córdoba, Marta  
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de Sousa Serro, Maximiliano Guillermo  
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Kauffman, Marcelo Andres  
dc.contributor.author
Yankilevich, Patricio  
dc.date.available
2019-12-03T20:05:37Z  
dc.date.issued
2018-01  
dc.identifier.citation
Koile, Daniel Isaac; Córdoba, Marta; de Sousa Serro, Maximiliano Guillermo; Kauffman, Marcelo Andres; Yankilevich, Patricio; GenIO: A phenotype-genotype analysis web server for clinical genomics of rare diseases; BioMed Central; BMC Bioinformatics; 19; 1; 1-2018  
dc.identifier.issn
1471-2105  
dc.identifier.uri
http://hdl.handle.net/11336/91268  
dc.description.abstract
Background: GenIO is a novel web-server, designed to assist clinical genomics researchers and medical doctors in the diagnostic process of rare genetic diseases. The tool identifies the most probable variants causing a rare disease, using the genomic and clinical information provided by a medical practitioner. Variants identified in a whole-genome, whole-exome or target sequencing studies are annotated, classified and filtered by clinical significance. Candidate genes associated with the patient's symptoms, suspected disease and complementary findings are identified to obtain a small manageable number of the most probable recessive and dominant candidate gene variants associated with the rare disease case. Additionally, following the American College of Medical Genetics and Genomics and the Association of Molecular Pathology (ACMG-AMP) guidelines and recommendations, all potentially pathogenic variants that might be contributing to disease and secondary findings are identified. Results: A retrospective study was performed on 40 patients with a diagnostic rate of 40%. All the known genes that were previously considered as disease causing were correctly identified in the final inherit model output lists. In previously undiagnosed cases, we had no additional yield. Conclusion: This unique, intuitive and user-friendly tool to assists medical doctors in the clinical genomics diagnostic process is openly available at https://bioinformatics.ibioba-mpsp-conicet.gov.ar/GenIO/.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
BioMed Central  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
BIOINFORMATICS  
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CLINICAL INFORMATICS  
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EXOME SEQUENCING  
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GENOME SEQUENCING  
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RARE DISEASE  
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VARIANT ANALYSIS  
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Ciencias de la Computación  
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Ciencias de la Computación e Información  
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CIENCIAS NATURALES Y EXACTAS  
dc.title
GenIO: A phenotype-genotype analysis web server for clinical genomics of rare diseases  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2019-10-22T17:31:42Z  
dc.journal.volume
19  
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1  
dc.journal.pais
Reino Unido  
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Londres  
dc.description.fil
Fil: Koile, Daniel Isaac. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigación en Biomedicina de Buenos Aires - Instituto Partner de la Sociedad Max Planck; Argentina  
dc.description.fil
Fil: Córdoba, Marta. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos "Ramos Mejía"; Argentina. Universidad Austral. Facultad de Ciencias Biomédicas. Instituto de Investigaciones en Medicina Traslacional. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones en Medicina Traslacional; Argentina  
dc.description.fil
Fil: de Sousa Serro, Maximiliano Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigación en Biomedicina de Buenos Aires - Instituto Partner de la Sociedad Max Planck; Argentina  
dc.description.fil
Fil: Kauffman, Marcelo Andres. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos "Ramos Mejía"; Argentina. Universidad Austral. Facultad de Ciencias Biomédicas. Instituto de Investigaciones en Medicina Traslacional. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones en Medicina Traslacional; Argentina  
dc.description.fil
Fil: Yankilevich, Patricio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigación en Biomedicina de Buenos Aires - Instituto Partner de la Sociedad Max Planck; Argentina  
dc.journal.title
BMC Bioinformatics  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-018-2027-3  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1186/s12859-018-2027-3