Data. Genes. Insights.
All in one interactive dashboard.
Explore patterns in Campylobacter jejuni and Campylobacter coli through clear, data-driven storytelling.
What You Can Do
Our platform helps you analyze and visualize virulence data intuitively.
Campylobacter jejuni and Campylobacter coli are leading causes of bacterial gastroenteritis worldwide and are commonly studied for their virulence-associated genes. These genes play roles in bacterial survival, host interaction, and environmental persistence.
Understanding how such genes vary across species and hosts is important for identifying broader patterns rather than individual biological outcomes. This dashboard focuses on visualizing those patterns in a clear and interactive way.
Visual Storylines
Explore key questions about virulence genes through interactive data narratives.
Virulence Gene Prevalence Across Hosts
Compare human vs multi-host prevalence and hover to see gene roles and prevalence gaps.
This chart shows the prevalence of key virulence genes across different host environments, revealing which genes are conserved across hosts versus those that are host-specific. Bars represent prevalence percentages, allowing you to quickly identify patterns of gene distribution.
Presence and Absence of Virulence Genes Across Species
This table shows whether selected virulence-associated genes are present or absent in Campylobacter jejuni compared with Campylobacter coli, based on the project dataset.
Virulence Genes Grouped by Biological Function
This section organizes virulence-associated genes by their annotated functional roles in the project dataset. Expand each category to view the genes included.
Gene Prevalence Heatmap
Prevalence shows what percentage of bacterial isolates from each host contain a specific gene. Each row represents a gene, each column represents a host association (Poultry, Cattle, Swine, Human, etc.). The color intensity indicates the prevalence percentage, with brighter colors meaning higher prevalence (the gene appears in more isolates), while darker colors mean lower or absent prevalence. This helps identify conserved (core) genes versus host-specific genes. Click on a gene cell to view its details.
Gene Prevalence Variability (Stability)
This visualization shows how stable or variable each virulence gene's prevalence is across hosts and species. Low variability (small error bars) indicates core, conserved virulence genes that are consistently present. High variability (large error bars) indicates host- or species-specific genes that are adaptive. Dots represent mean prevalence, error bars show the min-max range, and colors indicate functional categories.
Gene Co-Occurrence Network
This network visualization shows which virulence genes tend to appear together in the same bacterial isolates. Each circle (node) represents a gene. Larger circles mean the gene appears more frequently. Lines (links) connect genes that co-occur. Thicker lines mean those genes are found together more often. Genes are color-coded by function: red (toxin), blue (adhesion), green (invasion), orange (motility). Hover over nodes to see details, or click to explore specific genes.
Species-Specific Gene Distribution
Comparison of gene counts/percentages between C. jejuni and C. coli for the top 20 genes. Shows absolute counts or percentages for each species.
Gene Function Distribution
Distribution of genes by functional category (Adhesion, Invasion, Toxin, Motility, Iron uptake, Stress response, Other). Hover to see counts and percentages.
Hierarchical View: Species → Host → Gene Count
Sunburst diagram showing the hierarchy from all isolates, down to species (C. jejuni, C. coli), then hosts (Poultry, Human, etc.), with gene counts at each level.
Host to Gene Flow
Sankey diagram showing the flow from host categories to the top 20 genes. Link thickness represents the number of isolates containing each gene for that host.
About This Project
Turning complex virulence gene data into simple insights.
Virulence Insights is a student-led data storytelling project that visualizes patterns in *Campylobacter jejuni* and *Campylobacter coli* virulence factors. Built with Next.js, it integrates interactive visualizations for exploration.
Our Team
Developed by a group of research enthusiasts exploring data-driven biology.
Gerald Shimo
Full-Stack Developer
Hawulethu Ndlovu
Product Manager and Data Analyst
Praise Fabiyi
BioInformatics Engineer
Dr. Raj
Faculty Advisor