bio-de-visualization
Visualize differential expression results using DESeq2/edgeR built-in functions. Covers plotMA, plotDispEsts, plotCounts, plotBCV, sample distance heatmaps, and p-value histograms. Use when visualizing differential expression results.
npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-de-visualization --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
## Version Compatibility Reference examples tested with: DESeq2 1.42+, edgeR 4.0+, ggplot2 3.5+, limma 3.58+, matplotlib 3.8+ Before using code patterns, verify installed versions match. If versions differ: - R: `packageVersion('<pkg>')` then `?function_name` to verify parameters If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. # DE Visualization Create visualizations for differential expression analysis using DESeq2 and edgeR built-in plotting functions. ## Scope This skill covers **DE-specific built-in functions**: - DESeq2: `plotMA()`, `plotPCA()`, `plotDispEsts()`, `plotCounts()` - edgeR: `plotMD()`, `plotBCV()`, `plotMDS()` - Sample distance heatmaps and p-value distributions **For custom ggplot2/matplotlib implementations** of volcano, MA, and PCA plots, see `data-visualization/specialized-omics-plots`. ## Required Libraries ```r library(DESeq2) library(ggplot2) library(pheatmap) library(RColorBrewer) library(ggrepel) # For labeled points ``` ## Installation ```r install.packages(c('ggplot2', 'pheatmap', 'RColorBrewer', 'ggrepel')) # Optional: Enhanced volcano plots B
- Version Compatibility
- Scope
- Required Libraries
- Installation
- MA Plot
- DESeq2 MA Plot
- Custom ggplot2 MA Plot
- edgeR MA Plot
- Volcano Plot
- Basic Volcano Plot
- Volcano with Gene Labels
- EnhancedVolcano
- PCA Plot
- DESeq2 PCA
What does the bio-de-visualization skill do?
Visualize differential expression results using DESeq2/edgeR built-in functions. Covers plotMA, plotDispEsts, plotCounts, plotBCV, sample distance heatmaps, and p-value histograms. Use when visualizing differential expression results.
How do I install it?
Run `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-de-visualization --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From FreedomIntelligence/OpenClaw-Medical-Skills, a repository with 2,909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.