My eyes were finally opened and I understood nature.

I learned at the same time to love it.

— Claude Monet

ggsci offers a collection of high-quality color palettes inspired by colors used in scientific journals, data visualization libraries, science fiction movies, and TV shows. The color palettes in ggsci are available as ggplot2 scales. For all the color palettes, the corresponding scales are named as:

  • scale_color_palname()
  • scale_fill_palname()

We also provided aliases, such as scale_colour_palname() for scale_color_palname(). All available color palettes are summarized in the table below.

Name Scales Palette Types Palette Generator
NPG scale_color_npg() scale_fill_npg() "nrc" pal_npg()
AAAS scale_color_aaas() scale_fill_aaas() "default" pal_aaas()
NEJM scale_color_nejm() scale_fill_nejm() "default" pal_nejm()
Lancet scale_color_lancet() scale_fill_lancet() "lanonc" pal_lancet()
JAMA scale_color_jama() scale_fill_jama() "default" pal_jama()
JCO scale_color_jco() scale_fill_jco() "default" pal_jco()
UCSCGB scale_color_ucscgb() scale_fill_ucscgb() "default" pal_ucscgb()
D3 scale_color_d3()
"category10" "category20" "category20b" "category20c" pal_d3()
LocusZoom scale_color_locuszoom() scale_fill_locuszoom() "default" pal_locuszoom()
IGV scale_color_igv() scale_fill_igv() "default"
COSMIC scale_color_cosmic() scale_fill_cosmic() "hallmarks_light"
UChicago scale_color_uchicago() scale_fill_uchicago() "default"
Star Trek scale_color_startrek() scale_fill_startrek() "uniform" pal_startrek()
Tron Legacy scale_color_tron() scale_fill_tron() "legacy" pal_tron()
Futurama scale_color_futurama() scale_fill_futurama() "planetexpress" pal_futurama()
Rick and Morty scale_color_rickandmorty() scale_fill_rickandmorty() "schwifty" pal_rickandmorty()
The Simpsons scale_color_simpsons() scale_fill_simpsons() "springfield" pal_simpsons()
GSEA scale_color_gsea() scale_fill_gsea() "default" pal_gsea()
Material Design scale_color_material() scale_fill_material() "red" "pink"
"purple" "deep-purple"
"indigo" "blue"
"light-blue" "cyan"
"teal" "green"
"light-green" "lime"
"yellow" "amber"
"orange" "deep-orange"
"brown" "grey"

Discrete Color Palettes

We will use scatterplots with smooth curves, and bar plots to demonstrate the discrete color palettes in ggsci.



p1 <- ggplot(
  subset(diamonds, carat >= 2.2),
  aes(x = table, y = price, colour = cut)
) +
  geom_point(alpha = 0.7) +
  geom_smooth(method = "loess", alpha = 0.05, size = 1, span = 1) +

p2 <- ggplot(
  subset(diamonds, carat > 2.2 & depth > 55 & depth < 70),
  aes(x = depth, fill = cut)
) +
  geom_histogram(colour = "black", binwidth = 1, position = "dodge") +


The NPG palette is inspired by the plots in the journals published by Nature Publishing Group:

p1_npg <- p1 + scale_color_npg()
p2_npg <- p2 + scale_fill_npg()
grid.arrange(p1_npg, p2_npg, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'


The AAAS palette is inspired by the plots in the journals published by American Association for the Advancement of Science:

p1_aaas <- p1 + scale_color_aaas()
p2_aaas <- p2 + scale_fill_aaas()
grid.arrange(p1_aaas, p2_aaas, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'


The NEJM palette is inspired by the plots in The New England Journal of Medicine:

p1_nejm <- p1 + scale_color_nejm()
p2_nejm <- p2 + scale_fill_nejm()
grid.arrange(p1_nejm, p2_nejm, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'


The Lancet palette is inspired by the plots in Lancet journals, such as Lancet Oncology:

p1_lancet <- p1 + scale_color_lancet()
p2_lancet <- p2 + scale_fill_lancet()
grid.arrange(p1_lancet, p2_lancet, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'


The JAMA palette is inspired by the plots in The Journal of the American Medical Association:

p1_jama <- p1 + scale_color_jama()
p2_jama <- p2 + scale_fill_jama()
grid.arrange(p1_jama, p2_jama, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'


The JCO palette is inspired by the the plots in Journal of Clinical Oncology:

p1_jco <- p1 + scale_color_jco()
p2_jco <- p2 + scale_fill_jco()
grid.arrange(p1_jco, p2_jco, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'


The UCSCGB palette is from the colors used by UCSC Genome Browser for representing chromosomes. This palette (interpolated, with alpha) is intensively used in visualizations generated by Circos.

p1_ucscgb <- p1 + scale_color_ucscgb()
p2_ucscgb <- p2 + scale_fill_ucscgb()
grid.arrange(p1_ucscgb, p2_ucscgb, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'


The D3 palette is from the categorical colors used by D3.js (version 3.x and before). There are four palette types (category10, category20, category20b, category20c) available.

p1_d3 <- p1 + scale_color_d3()
p2_d3 <- p2 + scale_fill_d3()
grid.arrange(p1_d3, p2_d3, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'


The LocusZoom palette is based on the colors used by LocusZoom.

p1_locuszoom <- p1 + scale_color_locuszoom()
p2_locuszoom <- p2 + scale_fill_locuszoom()
grid.arrange(p1_locuszoom, p2_locuszoom, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'


The IGV palette is from the colors used by Integrative Genomics Viewer for representing chromosomes. There are two palette types (default, alternating) available.

p1_igv_default <- p1 + scale_color_igv()
p2_igv_default <- p2 + scale_fill_igv()
grid.arrange(p1_igv_default, p2_igv_default, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'


Color palettes inspired by the colors used in projects from the Catalogue Of Somatic Mutations in Cancers (COSMIC).

p1_cosmic_hallmarks_light <- p1 + scale_color_cosmic("hallmarks_light")
p2_cosmic_hallmarks_light <- p2 + scale_fill_cosmic("hallmarks_light")
grid.arrange(p1_cosmic_hallmarks_light, p2_cosmic_hallmarks_light, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'

p1_cosmic_hallmarks_dark <- p1 + scale_color_cosmic("hallmarks_dark")
p2_cosmic_hallmarks_dark <- p2 + scale_fill_cosmic("hallmarks_dark")
grid.arrange(p1_cosmic_hallmarks_dark, p2_cosmic_hallmarks_dark, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'

p1_cosmic_signature <- p1 + scale_color_cosmic("signature_substitutions")
p2_cosmic_signature <- p2 + scale_fill_cosmic("signature_substitutions")
grid.arrange(p1_cosmic_signature, p2_cosmic_signature, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'


The UChicago palette is based on the colors used by the University of Chicago. There are three palette types (default, light, dark) available.

p1_uchicago <- p1 + scale_color_uchicago()
p2_uchicago <- p2 + scale_fill_uchicago()
grid.arrange(p1_uchicago, p2_uchicago, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'

Star Trek

This palette is inspired by the (uniform) colors in Star Trek:

p1_startrek <- p1 + scale_color_startrek()
p2_startrek <- p2 + scale_fill_startrek()
grid.arrange(p1_startrek, p2_startrek, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'

Tron Legacy

This palette is inspired by the colors used in Tron Legacy. It is suitable for displaying data when using a dark theme:

p1_tron <- p1 + theme_dark() + theme(
  panel.background = element_rect(fill = "#2D2D2D"),
  legend.key = element_rect(fill = "#2D2D2D")
) +
p2_tron <- p2 + theme_dark() + theme(
  panel.background = element_rect(fill = "#2D2D2D")
) +
grid.arrange(p1_tron, p2_tron, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'


This palette is inspired by the colors used in the TV show Futurama:

p1_futurama <- p1 + scale_color_futurama()
p2_futurama <- p2 + scale_fill_futurama()
grid.arrange(p1_futurama, p2_futurama, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'

Rick and Morty

This palette is inspired by the colors used in the TV show Rick and Morty:

p1_rickandmorty <- p1 + scale_color_rickandmorty()
p2_rickandmorty <- p2 + scale_fill_rickandmorty()
grid.arrange(p1_rickandmorty, p2_rickandmorty, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'

The Simpsons

This palette is inspired by the colors used in the TV show The Simpsons:

p1_simpsons <- p1 + scale_color_simpsons()
p2_simpsons <- p2 + scale_fill_simpsons()
grid.arrange(p1_simpsons, p2_simpsons, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'

Continuous Color Palettes

We will use a correlation matrix visualization (a special type of heatmap) to demonstrate the continuous color palettes in ggsci.


cor <- cor(unname(cbind(mtcars, mtcars, mtcars, mtcars)))
cor_melt <- melt(cor)

p3 <- ggplot(
  aes(x = Var1, y = Var2, fill = value)
) +
  geom_tile(colour = "black", size = 0.3) +
  theme_bw() +
    axis.title.x = element_blank(),
    axis.title.y = element_blank()


The GSEA palette (continuous) is inspired by the heatmaps generated by GSEA GenePattern.

p3_gsea <- p3 + scale_fill_gsea()
p3_gsea_inv <- p3 + scale_fill_gsea(reverse = TRUE)
grid.arrange(p3_gsea, p3_gsea_inv, ncol = 2)

Material Design

The Material Design color palettes are from the material design color guidelines.

We generate a random matrix first:


k <- 9
x <- diag(k)
x[upper.tri(x)] <- runif(sum(1:(k - 1)), 0, 1)
x_melt <- melt(x)

p4 <- ggplot(x_melt, aes(x = Var1, y = Var2, fill = value)) +
  geom_tile(colour = "black", size = 0.3) +
  scale_x_continuous(expand = c(0, 0)) +
  scale_y_continuous(expand = c(0, 0)) +
  theme_bw() + theme(
    legend.position = "none", plot.background = element_blank(),
    axis.line = element_blank(), axis.ticks = element_blank(),
    axis.text.x = element_blank(), axis.text.y = element_blank(),
    axis.title.x = element_blank(), axis.title.y = element_blank(),
    panel.background = element_blank(), panel.border = element_blank(),
    panel.grid.major = element_blank(), panel.grid.minor = element_blank()

Plot the matrix with the 19 material design color palettes:

  p4 + scale_fill_material("red"), p4 + scale_fill_material("pink"),
  p4 + scale_fill_material("purple"), p4 + scale_fill_material("deep-purple"),
  p4 + scale_fill_material("indigo"), p4 + scale_fill_material("blue"),
  p4 + scale_fill_material("light-blue"), p4 + scale_fill_material("cyan"),
  p4 + scale_fill_material("teal"), p4 + scale_fill_material("green"),
  p4 + scale_fill_material("light-green"), p4 + scale_fill_material("lime"),
  p4 + scale_fill_material("yellow"), p4 + scale_fill_material("amber"),
  p4 + scale_fill_material("orange"), p4 + scale_fill_material("deep-orange"),
  p4 + scale_fill_material("brown"), p4 + scale_fill_material("grey"),
  p4 + scale_fill_material("blue-grey"),
  ncol = 6

From the figure above, we can see that even though an identical matrix was visualized by all plots, some palettes are more preferrable than the others because our eyes are more sensitive to the changes of their saturation levels.

Non-ggplot2 Graphics

To apply the color palettes in ggsci to other graphics systems (such as base graphics and lattice graphics), simply use the palette generator functions in the table above. For example:

mypal <- pal_npg("nrc", alpha = 0.7)(9)
## [1] "#E64B35B2" "#4DBBD5B2" "#00A087B2" "#3C5488B2" "#F39B7FB2" "#8491B4B2"
## [7] "#91D1C2B2" "#DC0000B2" "#7E6148B2"

You will be able to use the generated hex color codes for such graphics systems accordingly. The transparent level of the entire palette is easily adjustable via the argument "alpha" in every generator or scale function.


Please note some of the palettes might not be the best choice for certain purposes, such as color-blind safe, photocopy safe, or print friendly. If you do have such considerations, you might want to check out color palettes like ColorBrewer and viridis.

The color palettes in this package are solely created for research purposes. The authors are not responsible for the usage of such palettes.