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hic-visualization

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Renders Hi-C contact matrices honestly and reproducibly with matplotlib, cooltools, HiCExplorer, pyGenomeTracks, FAN-C, CoolBox, and plotgardener. Covers the raw/ICE-balanced/observed-over-expected transform choice, LogNorm vs symmetric-diverging colormaps with vmax/percentile clipping, resolution-to-feature matching (compartments 100-500kb, TADs 10-40kb, loops 5-10kb), square vs rotated-triangle track-stacking, NaN/white-stripe handling, virtual 4C, APA/saddle/on-diagonal pileups, two-condition side-by-side and log2-ratio maps, and interactive (HiGlass) vs scripted-static publication figures. Use when plotting a contact matrix, choosing a normalization or color scale, building a multi-track Hi-C figure, making a virtual 4C profile, piling up loops/boundaries, or comparing two conditions.

When to use

• plotting a contact matrix
• choosing a normalization or color scale
• building a multi-track Hi-C figure
• making a virtual 4C profile
• piling up loops/boundaries
• comparing two conditions
• rendering square or rotated-triangle maps
• handling NaN/white-stripe artifacts

When not to use

• interactive exploration without reproducible figures
• raw counts for science figures
• claims of no compartments/loops on balanced maps

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