Palettes included in biopalette

Browse all palettes

Use list_palettes() for a compact inventory:

list_palettes()[c("name", "type", "n_color")]
#>                  name        type n_color
#> 1        bcell_atlas2   diverging       5
#> 2        walter_white   diverging       5
#> 3       walter_white3   diverging       5
#> 4            gene_red qualitative       2
#> 5          heat_light qualitative       2
#> 6          three_body qualitative       3
#> 7       lactate_steps qualitative       5
#> 8       walter_white2 qualitative       5
#> 9          tam_pastel qualitative       6
#> 10        bcell_atlas qualitative       7
#> 11      cancer_mosaic qualitative      15
#> 12     bcell_clusters qualitative      20
#> 13              babel qualitative      21
#> 14   mitonuclear_blue  sequential       6
#> 15 mitonuclear_orange  sequential       6

Use palette_gallery() when choosing visually in an interactive R session:

palette_gallery()

The complete collection is summarized below. “Source record” opens the full English curation record in this repository; “Tessera” opens the corresponding visual page in the companion Tessera collection.

Qualitative palettes

Qualitative palettes distinguish unordered categories. The first n colors are returned when a smaller set is requested, because every stored color is a curated category color rather than a stop on a continuous ramp.

pages <- palette_gallery(type = "qualitative", verbose = FALSE)
pages[["qualitative_page1"]]

Choose the palette size to match the real number of groups:

• gene_red and heat_light provide restrained two-group contrasts;
• three_body provides three strongly separated colors;
• walter_white2, lactate_steps, and tam_pastel cover common medium-sized groupings;
• cancer_mosaic and babel support unusually large categorical displays.

Large qualitative palettes require help from position, direct labels, shape, faceting, or annotation. Twenty-one categories cannot be made effortless by color alone.

get_palette("babel", n = 5)
#> [1] "#1688A7" "#7673AE" "#B3DE69" "#D195F6" "#7E285E"

Sequential palettes

mitonuclear_blue and mitonuclear_orange represent one-direction change. Both run from a quiet light end to a darker visual anchor.

pages <- palette_gallery(type = "sequential", verbose = FALSE)
pages[["sequential_page1"]]

For sequential palettes, n samples the complete ramp in Lab color space. It does not take only the first n pale stops:

get_palette("mitonuclear_blue", n = 3)
#> [1] "#EEF4FB" "#A7C2E3" "#155289"
get_palette("mitonuclear_orange", n = 8)
#> [1] "#F8E7E3" "#EAD7D5" "#EEC9B5" "#F4BA8C" "#E89E6B" "#C28968" "#A1745E"
#> [8] "#925A44"

Use the light-to-dark direction for increasing values unless the scientific meaning requires the reverse. On white backgrounds, boundaries or grid lines help the lightest colors remain visible.

Diverging palettes

walter_white and walter_white3 represent two directions around a pale center.

pages <- palette_gallery(type = "diverging", verbose = FALSE)
pages[["diverging_page1"]]

Use a diverging palette only when the center has a meaningful interpretation, such as zero fold change, a clinical threshold, or a reference estimate. walter_white is the safer general-purpose option. The rose-to-green ends of walter_white3 can be difficult for common red-green color-vision deficiencies.

get_palette("walter_white", n = 7)
#> [1] "#1991A9" "#80B3BB" "#BAD1CF" "#E7E9E4" "#BEC7A6" "#889669" "#495A2E"

Source labels and new mappings

Some source records associate colors with cell types, cancer types, workflow stages, or objects in a screen image. Those labels document where the colors came from; they do not force the same labels in a new dataset.

When remapping a palette:

1. preserve a stable mapping throughout the project;
2. explain the mapping in the figure legend;
3. do not imply that biological meaning transfers with a HEX value;
4. retain non-color cues when categories are numerous or close in appearance.

Use the selected palette

Once selected, the palette name is the complete handoff to plotting code:

# Unordered categories
scale_color_biopalette("three_body")
scale_fill_biopalette("tam_pastel")

# Ordered continuous values
scale_fill_biopalette_gradient("mitonuclear_blue")

# Signed values around zero
scale_color_biopalette_gradient("walter_white", midpoint = 0)

Use reverse = TRUE when the direction should be flipped. Palette names in the bundled collection are unique, so type normally does not need to be specified.

Explore further

• Browse the complete GitHub source records for original images, extraction notes, reference labels, and limitations.
• Open Tessera palettes for a visual, reader-oriented view of the same named palettes.
• Use Palette Lab to switch the palettes across a consistent set of graphical displays.
• Read vignette("tessera", package = "biopalette") to continue from palette discovery to data, R recipes, and complete figures.

Propose a palette

New palettes enter the public collection through review. A proposal should include the source image, source attribution, palette JSON, preview, intended type, use cases, and known limitations—not only an attractive vector of HEX values.

See the contribution guide before opening a pull request.