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GENOMIC VISUALIZATION · R / GGPLOT2

Reveal the structure. Follow the connections.

Compose chord comparisons, collinear views and dense plasmid maps. Build reproducible genomic figures from real sequences, alignments and annotations.

Choose your visualization

Chord · Four genomes, one connected view

Four-genome chord comparison with mixed backbone curvature and measured identity
Four-genome chord comparison with mixed backbone curvature and measured identity · Click to enlarge

The original ggchord view, refined with signed curvature, varying radii, optimized display direction, local ribbon clearance and individually labelled selected features from real records. Data, complete code and interpretation →

Collinear · Four rows, many layers

Four-genome collinearity: strand-separated features and routed cross-row links
Four-genome collinearity: strand-separated features and routed cross-row links · Click to enlarge

A linear expression of the chord grammar, reusing real sequences, observed alignments and the identity palette. Features separate by strand; long cross-row links route to the right. The tutorial demonstrates coordinate-only conversion and explains current circular-only parameter limits. Complete workflow and the meaning of each layer →

Plasmid · A richly annotated pETDuet-1

Dense pETDuet-1 map: features, reference primers and grouped restriction sites
Dense pETDuet-1 map: features, reference primers and grouped restriction sites · Click to enlarge

A double backbone, layered features, five reference primers and restriction-enzyme names grouped by shared cut position. The input includes 58 cut positions and 20 features; labels are laid out for the actual export size. From a first circular view to complete plasmid annotation →

Continue from where you are

Examples prefer dplyr, purrr, tidyr and the native |> pipe, with ggplot2 layer composition. Updating older code? Read themigration guide.