bioinformatics-plot-generator

To generate publication-quality bioinformatics plots, you provide a plot-type request such as volcano or heatmap, and the router delegates to a specialized sub-skill to produce a ready-to-publish figure with extensive parameter configuration.

For differential expression analysis, you can create publication-ready volcano plots and MA plots by routing to dedicated sub-skills that apply specialized parameters for visualizing gene expression fold changes and statistical significance.

Yes, you can generate customizable heatmaps and correlation matrices for multi-omics workflows by routing to specialized sub-skills that leverage matplotlib and scipy to deliver publication-ready images with full parameter surfaces.

The best way to plot scatter and bubble charts for large genomic datasets is using this routing system, which delegates to self-contained sub-skills powered by pandas and numpy to handle data processing and produce publication-quality visualizations.

Yes, the plotting router supports box and violin plots by dispatching to a dedicated sub-skill, enabling you to compare sample groups with parameter-rich, publication-quality figures.

To start using the bioinformatics plot generator, simply provide a plot-type request like volcano, heatmap, or scatter, and the router will dispatch to the matching sub-skill to automatically generate your publication-ready figure.