GenIO: a phenotype-genotype analysis web server for clinical genomics of rare diseases

被引:14
作者
Koile, Daniel [1 ]
Cordoba, Marta [2 ,3 ]
de Sousa Serro, Maximiliano [1 ]
Andres Kauffman, Marcelo [2 ,3 ,4 ]
Yankilevich, Patricio [1 ]
机构
[1] Consejo Nacl Invest Cient & Tecn, Partner Inst Max Planck Soc, Inst Invest Biomed Buenos Aires IBioBA, Buenos Aires, DF, Argentina
[2] Ctr Univ Neurol, Consultorio Neurogenet, Buenos Aires, DF, Argentina
[3] UBA, Hosp JM Ramos Mejia, Fac Med, Div Neurol, Buenos Aires, DF, Argentina
[4] Univ Austral, CONICET, Inst Invest Med Traslac, Programa Med Precis & Genom,Fac Ciencias Biomed, Buenos Aires, DF, Argentina
来源
BMC BIOINFORMATICS | 2018年 / 19卷
关键词
Rare disease; Exome sequencing; Genome sequencing; Clinical informatics; Variant analysis; Bioinformatics; VARIANT PRIORITIZATION; GENETIC-VARIATION; ANNOTATION; GUIDELINES; DISCOVERY; DISORDERS; ANNOVAR;
D O I
10.1186/s12859-018-2027-3
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
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/.
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页数:6
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