VIVA
VIVA visualizes and analyzes genomic variation from Variant Call Format (VCF) files to support quality control and exploratory analysis of high-throughput sequencing data.
Key Features:
- VCF support: Processes Variant Call Format (VCF) files as the primary input for variant data.
- Variant visualization: Produces visual representations of genomic variation to facilitate assessment of variant calls.
- Quality control and exploratory analysis: Provides visualization outputs suited for quality control, exploratory analysis, and data interpretation of high-throughput sequencing variant datasets.
- Publication-quality graphics: Generates high-quality graphical outputs intended for scientific presentation and publication.
- Consolidation of existing tool functionality: Consolidates functionalities from multiple existing variant visualization tools.
- High-dimensional data handling: Designed to handle high-dimensional genomic variant data typical of large sequencing studies.
- Implementation library: Implements visualization and analysis routines using the VariantVisualization.jl Julia package.
Scientific Applications:
- Quality control of sequencing data: Visualize variant data for quality assessment of high-throughput sequencing experiments.
- Exploratory variant analysis: Investigate patterns and distributions of genomic variants across samples or genomic regions.
- Data interpretation and dissemination: Produce figures and visual summaries to support interpretation and communication of variant analysis results.
Methodology:
Processes Variant Call Format (VCF) files and implements visualization and analysis routines using the VariantVisualization.jl Julia package to generate graphical outputs.
Topics
Details
- Added:
- 11/14/2019
- Last Updated:
- 1/3/2021
Operations
Publications
Tollefson GA, Schuster J, Gelin F, Agudelo A, Ragavendran A, Restrepo I, Stey P, Padbury J, Uzun A. VIVA (VIsualization of VAriants): A VCF File Visualization Tool. Scientific Reports. 2019;9(1). doi:10.1038/s41598-019-49114-z. PMID:31477778. PMCID:PMC6718772.