An intelligent router skill that delegates bioinformatic data visualization requests to highly customizable, publication-ready sub-skills including volcano, heatmap, violin, and scatter plots.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install bioinformatics-plot-generator
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 bioinformatics-plot-generator 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 Bioinformatics Plot Generator?
The Bioinformatics Plot Generator is a specialized routing interface designed for AI agents and developer workflows, acting as the centralized hub for visualizing complex biological datasets. Utilizing Openclaw Skills, it intelligently interprets user plotting requests (ranging from differential expression and genomic screens to correlation analyses) and automatically delegates tasks to the corresponding visualization sub-skill. Each script is heavily customizable, generating standard dual-format (300 DPI PNG and vector SVG) outputs perfect for peer-reviewed academic publications.
By unifying several dedicated plotting libraries under a single routing mechanism, developers and AI agents can seamlessly generate sophisticated visualizations without manual parameter tuning or scripting from scratch. Whether you need a clustered gene expression heatmap, statistical comparison raincloud plots, or annotated volcano plots, this skill streamlines scientific visualization pipelines.
Bioinformatics Plot Generator Use Cases
- Visualizing differential gene expression, CRISPR screen hits, or GWAS results with automated text label collision avoidance.
- Generating clustered gene expression matrices or protein abundance heatmaps with row and column annotations.
- Comparing distribution groups with statistical significance bracket overlays using raincloud or violin plots.
- Producing correlation matrices, regression lines, and MA plots for quality control and exploratory bioinformatics data analysis.
- Integrating robust, automated visualization steps into bioinformatics analysis workflows powered by Openclaw Skills.
How Bioinformatics Plot Generator Works
- Analyze the user's data visualization prompt and target dataset columns to determine the appropriate plot type.
- Route the request within Openclaw Skills to the specific sub-skill (such as
plot-volcano,plot-heatmap,plot-box-violin, orplot-scatter-bar) according to the routing guide. - Parse the input tabular data (TSV/CSV) to locate required index, fold-change, p-value, or value columns.
- Configure style parameters, thresholds, and annotations based on standard defaults or advanced user overrides.
- Execute the underlying Python plotting script to render high-resolution 300 DPI PNG and vector-based SVG graphics.
- Output the final visualization paths along with any secondary annotated output tables for downstream analysis.
Bioinformatics Plot Generator Setup
Ensure you have the target packages installed in your environment before utilizing these Openclaw Skills. The scripts rely on standard scientific Python libraries such as numpy, pandas, matplotlib, seaborn, adjustText, and scipy.
Minimal Setup & Executing Sub-skills
To run a volcano plot generation:
python plot-volcano/scripts/plot_volcano.py \\
--input results.tsv \\
--feature-col gene \\
--x-col log2FoldChange \\
--p-col padj \\
--output volcano.png
To generate an expression heatmap:
python plot-heatmap/scripts/plot_heatmap.py \\
--input expression_matrix.tsv \\
--index-col gene \\
--output heatmap.png
To create a distribution violin plot with statistical tests:
python plot-box-violin/scripts/plot_box_violin.py \\
--input data.tsv \\
--value-col expression \\
--group-col condition \\
--plot-type violin \\
--output violin.png
Bioinformatics Plot Generator Data Schema & Taxonomy
The bioinformatics plot generator expects tabular data (TSV, CSV, or numeric matrices) and organizes output visual assets. Common properties across sub-skills are defined below:
Input Data Specifications
| Sub-skill | Input Format | Required Columns / Dimensions |
|---|---|---|
plot-volcano |
Tabular (TSV/CSV) | Feature ID, Log Fold-Change, p-value or adjusted p-value |
plot-heatmap |
Numeric Matrix | Row indexes (genes/proteins) and column headers (samples) |
plot-box-violin |
Tabular (TSV/CSV) | Numeric values, discrete grouping/condition column |
plot-scatter-bar |
Tabular (TSV/CSV) | Numeric coordinates, size-scaling, or category markers |
Output Files and Artifacts
- Primary Image: 300 DPI high-resolution PNG for rapid viewing and document embed.
- Vector Output: Optional SVG graphic companion (
--output-svg) for infinite scaling in Adobe Illustrator or Inkscape. - Annotated Tables: For volcano plots, an annotated TSV with assigned differential groups (up/down/ns) is saved.
Bioinformatics Plot Generator Advanced Features
- Quadrant counts dynamic calculation and rendering directly on volcano plot corners.
- Advanced adjustText collision avoidance for automated, non-overlapping label placement of top-N features.
- Hierarchical clustering with scipy linkage methods (ward, complete, average, single) integrated into heatmap generation.
- Variance-based row filtering to automatically keep only the top N most variable features in large matrices.
- Multi-group non-parametric statistical testing (Mann-Whitney U, Welch t-test, Dunn's test) with automatic Bonferroni or Benjamini-Hochberg correction adjustments.
- LOESS smoothing using an optimized pure NumPy implementation for MA plots.
- Modular routing system within Openclaw Skills to seamlessly hand off scientific visualization requests.
SKILL.md
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