biopalette

Image-Inspired Color Palettes for Biomedical Visualization

📚 Documentation • 💬 Issues • 🎨 Tessera • 🧪 Palette Lab

Languages: English | 简体中文

Overview

biopalette is an R package providing image-inspired color palettes for biomedical visualization.

Every palette begins with a real image — a film still, a scientific figure, an artwork — and is translated into a reproducible color system. The source is always documented: where the colors came from, what they mean, and when to use them.

library(biopalette)

get_palette("babel", n = 5)
get_palette("three_body")
get_palette("walter_white", type = "diverging")

preview_palette("gene_red")
palette_gallery()

# Discrete and continuous ggplot2 scales
scale_color_biopalette("three_body")
scale_fill_biopalette_gradient("mitonuclear_blue")

Installation

# Development version
devtools::install_github("evanbio/biopalette")

Palettes

Each name links to its source page — source image, color table, and intended use.

Name	Type	Colors	Recommended use	Source
`gene_red`	Qualitative	2	Emphasized signal versus a dark or neutral counterpart	Better Call Saul — Gene Takavic’s red coat
`walter_white`	Diverging	5	Signed continuous values around a neutral center	Breaking Bad — desert to sky
`walter_white2`	Qualitative	5	Up to five unordered groups	Breaking Bad — muted earth tones
`walter_white3`	Diverging	5	Warm-register signed continuous values	Breaking Bad — warm counterpart
`babel`	Qualitative	21	Many categorical groups with labels or position support	Pan-cancer myeloid atlas (Cell, 2021) — 22 cell types, 21 voices
`bcell_atlas`	Qualitative	7	Four-to-seven categorical groups with direct labels or position support	Pan-cancer B-cell atlas (Cell, 2024) — graphical abstract
`bcell_atlas2`	Diverging	5	Signed change between warm and cool biological states	Pan-cancer B-cell atlas (Cell, 2024) — IgA to IgG shift
`bcell_clusters`	Qualitative	20	Many labeled categorical groups with position or faceting support	Pan-cancer B-cell atlas (Cell, 2024) — Figure 1B cluster legend
`three_body`	Qualitative	3	Three groups, lineages, or trajectories	Pan-cancer myeloid atlas (Cell, 2021) — three DC trajectories
`mitonuclear_blue`	Sequential	6	Cool low-to-high continuous values	Mito-nuclear communication in aging (TIBS, 2022) — young blue
`mitonuclear_orange`	Sequential	6	Warm low-to-high continuous values	Mito-nuclear communication in aging (TIBS, 2022) — aged orange
`heat_light`	Qualitative	2	Paired categories or experimental conditions	Bond ampholysis (Nature, 2024) — heat and light turn radicals into an ion pair
`tam_pastel`	Qualitative	6	Four-to-six categorical groups on light backgrounds	Pan-cancer myeloid atlas (Cell, 2021) — soft TAM states
`cancer_mosaic`	Qualitative	15	Ten-to-fifteen categories with labels or position support	Pan-cancer myeloid atlas (Cell, 2021) — cancer-type mosaic
`lactate_steps`	Qualitative	5	Five discrete workflow stages or study groups	Lactate metabolism and immunotherapy (JECCR, 2024) — five study stages

Name

Type

Colors

Recommended use

Source

gene_red

Qualitative

Emphasized signal versus a dark or neutral counterpart

Better Call Saul — Gene Takavic’s red coat

walter_white

Diverging

Signed continuous values around a neutral center

Breaking Bad — desert to sky

walter_white2

Qualitative

Up to five unordered groups

Breaking Bad — muted earth tones

walter_white3

Diverging

Warm-register signed continuous values

Breaking Bad — warm counterpart

babel

Qualitative

Many categorical groups with labels or position support

Pan-cancer myeloid atlas (Cell, 2021) — 22 cell types, 21 voices

bcell_atlas

Qualitative

Four-to-seven categorical groups with direct labels or position support

Pan-cancer B-cell atlas (Cell, 2024) — graphical abstract

bcell_atlas2

Diverging

Signed change between warm and cool biological states

Pan-cancer B-cell atlas (Cell, 2024) — IgA to IgG shift

bcell_clusters

Qualitative

Many labeled categorical groups with position or faceting support

Pan-cancer B-cell atlas (Cell, 2024) — Figure 1B cluster legend

three_body

Qualitative

Three groups, lineages, or trajectories

Pan-cancer myeloid atlas (Cell, 2021) — three DC trajectories

mitonuclear_blue

Sequential

Cool low-to-high continuous values

Mito-nuclear communication in aging (TIBS, 2022) — young blue

mitonuclear_orange

Sequential

Warm low-to-high continuous values

Mito-nuclear communication in aging (TIBS, 2022) — aged orange

heat_light

Qualitative

Paired categories or experimental conditions

Bond ampholysis (Nature, 2024) — heat and light turn radicals into an ion pair

tam_pastel

Qualitative

Four-to-six categorical groups on light backgrounds

Pan-cancer myeloid atlas (Cell, 2021) — soft TAM states

cancer_mosaic

Qualitative

Ten-to-fifteen categories with labels or position support

Pan-cancer myeloid atlas (Cell, 2021) — cancer-type mosaic

lactate_steps

Qualitative

Five discrete workflow stages or study groups

Lactate metabolism and immunotherapy (JECCR, 2024) — five study stages

From Palette to Figure

biopalette provides the R interface for retrieving and applying image-inspired palettes. Tessera documents their source images, example data, and reproducible R figure recipes. Palette Lab keeps the data and graphical structure fixed while comparing palette behavior across 17 graphical contexts. The overview and panels below are rendered from Palette Lab; Tessera links provide the corresponding figure recipes and data context.

The same palette can behave differently as points, lines, filled regions, heatmap cells, set overlaps, survival curves, or genome-wide signals. These examples show the kinds of figures available through the Tessera recipes and the corresponding palette comparisons in Palette Lab.

Function Reference

🎨 Palette Access (4)

get_palette() — retrieve colors by name, type, and size
palette_info() — metadata for one named palette
list_palettes() — data frame of all available palettes
palette_gallery() — paged visual gallery of all palettes

🔧 Palette Management (3)

create_palette() — write a new palette to JSON
remove_palette() — remove a palette by name
preview_palette() — render color swatches to a plot

📊 ggplot2 Scales (6)

scale_color_biopalette() / scale_colour_biopalette() — discrete color scales
scale_fill_biopalette() — discrete fill scales
scale_color_biopalette_gradient() / scale_colour_biopalette_gradient() — continuous color gradients
scale_fill_biopalette_gradient() — continuous fill gradients

🔵 Color Utilities (2)

hex2rgb() — convert HEX to RGB
rgb2hex() — convert RGB to HEX

_{Grouped scatter · babel}	_{Multi-line comparison · walter_white2}
_{Correlation heatmap · walter_white}	_{Eye color composition by hair color · lactate_steps}
_{Kaplan–Meier survival curve · heat_light}	_{Manhattan plot · cancer_mosaic}

biopalette

Image-Inspired Color Palettes for Biomedical Visualization

Overview

Installation

Palettes

From Palette to Figure

Function Reference

License