bio-chipseq-visualization
Visualize ChIP-seq data using deepTools, Gviz, and ChIPseeker. Create heatmaps, profile plots, and genome browser tracks. Visualize signal a…
Maintainer FreedomIntelligence · Last updated April 1, 2026
Hierarchical clustering heatmaps with ComplexHeatmap or seaborn.
Original source
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-data-visualization-heatmaps-clustering
Skill Snapshot
Source Doc
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')
library(ComplexHeatmap)
library(circlize)
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