ViVa

ViVa visualizes natural genetic variation from publicly available genome datasets to support analysis of variation at gene, gene-family, and gene-network levels for hypothesis generation and testing.

Key Features:

• Data Accessibility: Leverages publicly available genomic datasets, including the Arabidopsis thaliana 1001 Genomes Project, to enable exploration of natural variation.
• Multi-level Analysis: Enables analysis of variation at the gene, gene-family, and gene-network levels.
• Extensibility: Supports integration with interspecific genetic variation databases such as the 3,000 Rice Genomes Project and ClinVar.
• Pathway- and Network-focused Analysis: Facilitates focused exploration of specific pathways or networks, for example the nuclear auxin signaling pathway.

Scientific Applications:

• Hypothesis Generation and Testing: Facilitates generation and testing of hypotheses by analyzing natural variation to confirm known biology and suggest novel hypotheses.
• Pathway Validation: Applied to well-studied pathways, such as the nuclear auxin signaling pathway in Arabidopsis thaliana, to corroborate existing functional insights.
• Comparative and Cross-species Analysis: Enables comparative studies across species and databases by integrating datasets from projects like the 3,000 Rice Genomes Project and ClinVar.
• Investigation of Less-characterized Gene Families and Networks: Supports discovery-driven analyses of poorly characterized gene families and networks using natural variation data.

Methodology:

Collaborative analyses focusing on specific pathways or networks to explore how natural variation influences biological functions.