An automated visualization tool for generating gene expression bubble plots categorized by cell type and disease state.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install bubble-plot
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install bubble-plot using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Bubble Plot Generator?
The Bubble Plot Generator is a specialized data visualization component within Openclaw Skills designed for bioinformatics and genomic research. It simplifies the creation of dot plots from gene expression matrices, which are essential for interpreting single-cell RNA-seq and spatial transcriptomics data. The skill automatically handles the complex mapping of gene expression levels and the percentage of positive cells across various clusters and tissue types.
By utilizing this skill, researchers can transform raw TSV or CSV datasets into high-quality, publication-ready visualizations. It streamlines the workflow of comparing gene expression patterns between normal and tumor tissues, providing a clear visual representation of biological variance without requiring manual data manipulation.
Bubble Plot Generator Use Cases
- Visualizing gene expression across single-cell RNA-seq clusters.
- Comparing molecular markers between Tumor and Normal tissue samples in spatial transcriptomics.
- Generating high-resolution dot plots for academic publications and research reports.
- Batch processing multiple gene lists to identify expression patterns across different cancer types.
How Bubble Plot Generator Works
- The skill detects and validates the input genomic data file (TSV or CSV) in the workspace.
- It performs automatic metadata detection to identify columns for cell types, tissue conditions, and cancer classifications.
- The data is filtered based on specific gene lists provided by the user or automatically identified numerical columns.
- A Python-based processing engine calculates the normalized average expression and the proportion of cells expressing each gene.
- The system renders the visualization using the RdBu_r color spectrum and generates output in both PNG and PDF formats.
Bubble Plot Generator Setup
To use this feature within Openclaw Skills, ensure your environment has Python 3 and the necessary data science libraries installed. Use the following command to set up the dependencies:
pip3 install --break-system-packages pandas matplotlib
You can then run the generator using the following CLI structure:
python3 skills/bubble-plot/bubble_plot.py <your_data.tsv> --genes GENE_NAME_1 GENE_NAME_2
Bubble Plot Generator Data Schema & Taxonomy
The skill intelligently maps your dataset by identifying specific keywords in your column headers. Below is the expected taxonomy:
| Data Role | Identification Keywords | Example Column Names |
|---|---|---|
| Cell Type | majorCluster, cell_type, cluster | majorCluster, CellType |
| Tissue Type | tissue, class, condition, group | tissue, class |
| Cancer Type | cancerType, cancer_type, disease | cancerType, Disease |
| Expression | Numerical non-metadata columns | FOLR1, TACSTD2, MET |
Output files are organized in a bubble_plots/ directory with standardized naming conventions: {Gene}_dotplot_{TissueType}.png.
Bubble Plot Generator Advanced Features
- Automatic tissue label normalization (e.g., mapping 'Adjacent' samples to 'Normal').
- Configurable DPI settings for ultra-high-resolution image exports suitable for large-format printing.
- Support for both split-tissue views and unified visualization via the --no-split-tissue flag.
- Multi-format export providing PNGs for quick previews and vector-based PDFs for professional editing.
SKILL.md
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