1. VPOT: A Customizable Variant Prioritization Ordering Tool for Annotated Variants
- Author
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Gavin Chapman, David S. Winlaw, Eleni Giannoulatou, Sally L. Dunwoodie, and Eddie Ip
- Subjects
Heart Diseases ,Computer science ,computer.software_genre ,Biochemistry ,Customizable ranking ,Ranking (information retrieval) ,03 medical and health sciences ,Annotation ,User-Computer Interface ,0302 clinical medicine ,Documentation ,Application Note ,Databases, Genetic ,Exome Sequencing ,Genetics ,Humans ,3-Hydroxyanthranilate 3,4-Dioxygenase ,Molecular Biology ,lcsh:QH301-705.5 ,030304 developmental biology ,computer.programming_language ,0303 health sciences ,Polymorphism, Genetic ,Variant prioritization ,Python (programming language) ,Weighting ,Computational Mathematics ,Identification (information) ,lcsh:Biology (General) ,Scalability ,Next-generation sequencing ,Data mining ,Genomic annotation ,Pathogenicity predictions ,computer ,030217 neurology & neurosurgery ,Algorithms ,Test data - Abstract
Next-generation sequencing (NGS) technologies generate thousands to millions of genetic variants per sample. Identification of potential disease-causal variants is labor intensive as it relies on filtering using various annotation metrics and consideration of multiple pathogenicity prediction scores. We have developed VPOT (variant prioritization ordering tool), a python-based command line tool that allows researchers to create a single fully customizable pathogenicity ranking score from any number of annotation values, each with a user-defined weighting. The use of VPOT can be informative when analyzing entire cohorts, as variants in a cohort can be prioritized. VPOT also provides additional functions to allow variant filtering based on a candidate gene list or by affected status in a family pedigree. VPOT outperforms similar tools in terms of efficacy, flexibility, scalability, and computational performance. VPOT is freely available for public use at GitHub (https://github.com/VCCRI/VPOT/). Documentation for installation along with a user tutorial, a default parameter file, and test data are provided. Keywords: Next-generation sequencing, Pathogenicity predictions, Variant prioritization, Customizable ranking, Genomic annotation
- Published
- 2019