Generate publication-grade heatmaps, scatter plots, stripcharts, boxplots, and density plots in R and Python.
npx skills add https://github.com/ppavlidis/skillz --skill plotting-ppavlidis
Please help me install this Agent Skill. Skill: plotting Source: https://github.com/ppavlidis/skillz/tree/main/skills/plotting Command: npx skills add https://github.com/ppavlidis/skillz --skill plotting-ppavlidis
High-intent search queries and answers about installing and using this skill.
Call pavlab_heatmap with your matrix; it wraps seaborn.heatmap in Python and pheatmap in R. Expression mode row-standardizes to Z-scores clipped at ±3, correlation mode blanks the diagonal, and raw mode picks a sequential palette when all values are non-negative.
Use pavlab_scatter with log_x="log2" and log_y="log2"; the data is pre-transformed with a pseudocount of 1 and axis labels gain a log suffix automatically. If data spans more than 100× without a transform, a warning suggests the appropriate log scale.
Strip applies uniform random horizontal jitter and suits small-to-medium groups up to roughly 200 points. Swarm packs points non-overlappingly so distribution shape stays legible, but becomes expensive above a few thousand points per group, where a density plot is preferable.
The R version accepts cluster_rows and cluster_cols passed through to pheatmap, but both default to FALSE by lab convention. The Python version raises NotImplementedError for clustering and directs you to seaborn's clustermap instead.
Avoid them for exploratory clustering-driven heatmap analysis, interactive visualization (use plotly or heatmaply), and annotated multi-track heatmaps (use ComplexHeatmap in R). The helpers encode fixed publication defaults rather than exploratory flexibility.
NA cells are hardcoded to grey (grey80 in R, #cccccc in Python) so missing data is never confused with a near-zero value in the divergent palette, whose midpoint is black. This is a deliberate design contract of the skill.
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ya-wayA data analysis tool that generates a clustered heatmap from a matrix of expression values, with optional row/column annotations and multiple output formats.
