Data & ReproScientific VisualizationFreedomIntelligence/OpenClaw-Medical-SkillsData & Reproduction
BI

bio-data-visualization-heatmaps-clustering

Maintainer FreedomIntelligence · Last updated April 1, 2026

Hierarchical clustering heatmaps with ComplexHeatmap or seaborn.

OpenClawNanoClawAnalysisWritingbio-data-visualization-heatmaps-clustering🧠 bioos extended suitebioos extended bioinformatics suitehierarchical

Original source

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-data-visualization-heatmaps-clustering

Maintainer
FreedomIntelligence
License
MIT
Last updated
April 1, 2026

Skill Snapshot

Key Details From SKILL.md

2 min

Key Notes

  • pheatmap(mat, scale = 'row', cluster_rows = TRUE, cluster_cols = TRUE).
  • annotation_col <- data.frame( Condition = metadata$condition, Batch = metadata$batch, row.names = colnames(mat) ).
  • annotation_row <- data.frame( Pathway = gene_info$pathway, row.names = rownames(mat) ).
  • pheatmap(mat, scale = 'row', annotation_col = annotation_col, annotation_row = annotation_row, color = colorRampPalette(rev(brewer.pal(9, 'RdBu')))(100), show_rownames = FALSE, fontsize = 8).

Source Doc

Excerpt From SKILL.md

pheatmap (R) - Quick Heatmaps

library(pheatmap)
library(RColorBrewer)

## Custom annotation colors

ann_colors <- list(
    Condition = c(Control = '#4DBBD5', Treatment = '#E64B35'),
    Batch = c(A = '#00A087', B = '#3C5488', C = '#F39B7F'),
    Pathway = c(Metabolism = '#8491B4', Signaling = '#91D1C2')
)

pheatmap(mat, scale = 'row',
         annotation_col = annotation_col,
         annotation_colors = ann_colors,
         clustering_distance_rows = 'correlation',
         clustering_distance_cols = 'euclidean',
         clustering_method = 'ward.D2',
         cutree_rows = 4,
         cutree_cols = 2,
         gaps_col = c(5, 10),
         border_color = NA,
         main = 'Gene Expression Heatmap')

ComplexHeatmap (R) - Advanced

library(ComplexHeatmap)
library(circlize)

Use cases

  • Use bio-data-visualization-heatmaps-clustering to prepare publication-quality figures.
  • Apply bio-data-visualization-heatmaps-clustering when results need clear visual communication.

Not for

  • Do not rely on this catalog entry alone for installation or maintenance details.

Upstream Related Skills

  • data-visualization/ggplot2-fundamentals - General plotting
  • data-visualization/color-palettes - Color selection
  • differential-expression/de-visualization - Expression heatmaps

Related skills

Related skills

Back to directory
BI
Data & ReproScientific Visualization

bio-chipseq-visualization

Visualize ChIP-seq data using deepTools, Gviz, and ChIPseeker. Create heatmaps, profile plots, and genome browser tracks. Visualize signal a…

OpenClawNanoClawAnalysis
FreedomIntelligence/OpenClaw-Medical-SkillsView
BI
Data & ReproScientific Visualization

bio-consensus-sequences

Generate consensus FASTA sequences by applying VCF variants to a reference using bcftools consensus. Use when creating sample-specific refer…

OpenClawNanoClawAnalysis
FreedomIntelligence/OpenClaw-Medical-SkillsView
BI
Data & ReproScientific Visualization

bio-copy-number-cnv-visualization

Visualize copy number profiles, segments, and compare across samples. Create publication-quality plots of CNV data from CNVkit, GATK, or oth…

OpenClawNanoClawAnalysis
FreedomIntelligence/OpenClaw-Medical-SkillsView
BI
Data & ReproScientific Visualization

bio-data-visualization-circos-plots

Circular genome visualization with Circos or pycirclize.

OpenClawNanoClawAnalysis
FreedomIntelligence/OpenClaw-Medical-SkillsView