Computational validation demonstrates superior accuracy of VINYL for variant prioritization across genomic datasets, highlighting its utility in clinical genomics.
MOTIVATION: Clinical applications of genome re-sequencing technologies typically generate large amounts of data that need to be carefully annotated and interpreted to identify genetic variants potentially associated with pathological conditions. In this context, accurate and reproducible methods for the functional annotation and prioritization of genetic variants are of fundamental importance. RESULTS: In this article, we present VINYL, a flexible and fully automated system for the functional annotation and prioritization of genetic variants. Extensive analyses of both real and simulated datasets suggest that VINYL can identify clinically relevant genetic variants in a more accurate manner compared to equivalent state of the art methods, allowing a more rapid and effective prioritization of genetic variants in different experimental settings. As such we believe that VINYL can establish itself as a valuable tool to assist healthcare operators and researchers in clinical genomics investigations. AVAILABILITY AND IMPLEMENTATION: VINYL is available at http://beaconlab.it/VINYL and https://github.com/matteo14c/VINYL. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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