| Session Information |
|---|
| Session Title: Bioinformatics and Genomic Technology Session Type: Poster |
| Session Location: Exhibit Hall, Lower Level South, Moscone Center Session Time: Wed 10:00AM-4:30PM |
| Abstract Information |
| Program Number: 3538W Presentation Time: Wed, Nov 7, 2012, 3:15PM-4:15PM |
| Keywords: Bioinformatics and Genomic Technology, KW008 - bioinformatics, KW031 - computational tools, KW102 - massively parallel sequencing |
| Abstract Content |
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EVA: Exome Variation Analyzer, a tool for filtering strategies in medical genomics. S. Coutant1,2, C. Cabot2, A. Lefebvre2, M. Léonard2, E. Prieur-Gaston2, D. Campion1, T. Lecroq2, T. Frebourg1,3, H. Dauchel2
1) Inserm U1079, Institute for Research and Innovation in
Biomedicine, (IRIB), University of Rouen, Normandy, France; 2) LITIS EA
4108 Computer science, Information processing and systems laboratory,
IRIB, University of Rouen, Normandy, France; 3) Department of Genetics,
University Hospital, Rouen, Normandy, France. Exome-scale sequencing is a revolution in medical genetics, impacting both fundamental research and diagnostic. However, the challenge remains in efficient filtering strategies to find causing disease variant(s) among ~20,000 per individual exome. For this purpose, analytical procedures with various filtering strategies are required. With this aim, in parternship with and for medical geneticists, we developed EVA (Exome Variation Analyzer) a user-friendly web interfaced sofware dedicated to filtering strategies for medical projects. EVA allows managing data through different modules. Among them, the first is an offline Variation Integration module. It takes as input standard Variant Calling Format files and annotates the variations thanks to ANNOVAR and the Variation Effect Predictor Ensembl API. Annotated variations are then stored in a database. On the web interface, the Variation Statistics module displays basic count of SNV and indel for all the variations corresponding to a project or a selection of individuals, chromosomes, regions or genes. The filtering module proposes to combine multiple filters to drastically narrow down the variations number. It compares data to international catalogues of variations (dbSNP, 1000 genomes, ESP Cohort) and sorts out variations depending on their: a) functional categories (synonymous, missense, nonsense, frameshift...) b) genic region (UTR, exons, introns, splice sites) and c) quality. Finally, the major strength of EVA is the implementation of inheritance filters that considers intersection or differential exome strategies: a) recurrence strategy for dominant or recessive non-familial cases; b) intra-familial strategy with filters for homozygous or heterozygous composite; c) differential exomes strategy for de novo sporadic cases (trio). EVA offers export files and cross-links to external relevant databases and softwares for further inspection of the small subset of sorted candidate variations and genes. EVA is developed to be a user-friendly, versatile, and efficient-filtering assisting software. Thereby, it provides a response to new needs at the expanding era of medical genomics for both fundamental research and clinical diagnostics. EVA will be soon available for free downloads. You may contact the first author (during and after the meeting) at: sophie DOT coutant AT inserm DOT fr |