deg-and-marker-gene-heatmap-with-viridis-col-clustering
Generates a publication-ready heatmap for differentially expressed genes (DEGs) or marker genes using viridis colormap, column-only hierarchical clustering, and Arial font — applicable to any normalized gene expression matrix with genes as rows and samples/subclusters as columns.
npx skills add ECNU-ICALK/AutoSkill --skill deg-and-marker-gene-heatmap-with-viridis-col-clustering --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.
# deg-and-marker-gene-heatmap-with-viridis-col-clustering Generates a publication-ready heatmap for differentially expressed genes (DEGs) or marker genes using viridis colormap, column-only hierarchical clustering, and Arial font — applicable to any normalized gene expression matrix with genes as rows and samples/subclusters as columns. ## Prompt # Goal Generate a seaborn-based heatmap for differentially expressed or marker genes, accepting a pandas DataFrame with genes as rows and samples/subclusters as columns. # Constraints & Style - Use `cmap="viridis"` exclusively; do not use RdBu_r, center, or any other colormap or symmetry setting. - Enable only column-wise hierarchical clustering: set `col_cluster=True` and `row_cluster=False`. - Use Arial font for all text elements (title, axis labels, tick labels, colorbar label); enforce via `plt.rcParams["font.sans-serif"] = ["Arial", "DejaVu Sans", "Liberation Sans"]` and `plt.rcParams["axes.unicode_minus"] = False`; explicitly annotate plot elements if seaborn does not inherit font settings. - Apply row-wise z-score normalization (per gene) before plotting: `df.T.apply(lambda x: (x - x.mean()) / x.std(ddof=0)).T`. - Use `robust=True`
- Prompt
- Triggers
What does the deg-and-marker-gene-heatmap-with-viridis-col-clustering skill do?
Generates a publication-ready heatmap for differentially expressed genes (DEGs) or marker genes using viridis colormap, column-only hierarchical clustering, and Arial font — applicable to any normalized gene expression matrix with genes as rows and samples/subclusters as columns.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill deg-and-marker-gene-heatmap-with-viridis-col-clustering --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 ECNU-ICALK/AutoSkill, a repository with 539 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.