bio-data-visualization-interactive-visualization

Interactive omics plots are generated using Plotly and Bokeh to render zoomable, hoverable visuals like PCA and volcano plots for exploratory data analysis. The skill applies Python and R code patterns to transform datasets into these interactive visualizations.

Interactive Bokeh and Plotly dashboards can be exported as standalone HTML files for web-based sharing with collaborators. This allows researchers to distribute interactive omics visualizations without requiring recipients to run any code themselves.

Linked brushing dashboards for multi-dimensional omics data exploration are supported through Bokeh and Plotly. This functionality enables dynamic filtering across multiple linked plots, such as PCA plots and heatmaps, to explore complex datasets interactively.

The best way to visualize differential gene expression results is by generating interactive volcano plots using Plotly or Bokeh. These interactive plots allow users to hover over data points to inspect specific gene metrics and zoom into regions of interest for exploratory analysis.

Python and R code patterns are both referenced within the skill to build interactive omics visualizations, but you do not strictly need both to generate outputs. The skill requires Plotly and Bokeh to render the interactive visuals, accommodating either language environment.

You can generate PCA plots, volcano plots, heatmaps, and linked brushing dashboards for web-based dashboards. These interactive omics visualizations are designed for multi-dimensional data exploration and can be embedded in notebooks or exported as HTML files.