Use colorblind-friendly palette for visualization

Color packages

library(here)
library(tidyverse)
library(patchwork)
library(ggsci)
library(Seurat)
library(RColorBrewer)
library(viridis)
library(paletteer)
library(cols4all)
library(RImagePalette)
library(scales)

Basic colors

# gray colors
cbp <- c("gray", "lightgray", "darkgray", "black")
barplot(1:4, col = cbp)

# 4 colors
cbp <- c(
  "#b8b8b8", "#02ff00", "#f9a506", "#ff3c31"
)
barplot(1:4, col = cbp)

# 6 colors
cbp <- c(
  "#4C72B0", "#55A868", "#C44E52", "#8172B2", "#CCB974", "#64B5CD"
)
barplot(1:6, col = cbp)

# 8 colors
cbp <- c(
  "#999999", "#E69F00", "#56B4E9", "#009E73", "#F0E442", "#0072B2", 
  "#D55E00", "#CC79A7"
)
barplot(1:8, col = cbp)

# 9 colors
cbp <- c(
    "#000000", "#999999", "#E69F00", "#56B4E9", "#009E73", "#F0E442", 
    "#0072B2", "#D55E00", "#CC79A7"
)
barplot(1:9, col = cbp)

Color()

load(here("projects", "2023_scRNA_Seurat", "pbmc_tutorial.RData"))
# 657 colors
length(colors())
## [1] 657
show_col(colors()[1:50])

cbp <-c(
  "#80d7e1","#e4cbf2","#ffb7ba","#bf5046","#b781d2","#ece7a3",          "#f5cbe1","#e6e5e3","#d2b5ab","#d9e3f5","#f29432","#9c9895"
)
show_col(cbp)

## Single cell plot
p1 <- DimPlot(pbmc, reduction = "umap",label = T) + NoLegend()
p2 <- DimPlot(pbmc, reduction = "umap",cols = cbp,label = T)+ NoLegend()
p1 + p2

RColorBrewer

library(RColorBrewer)
display.brewer.all()

col <- brewer.pal(9, "Set1")
b1 <- brewer.pal(9, "Set1")
b2 <- brewer.pal(8, "Set2")
mycolor <- c(b1,b2)

ggsci

library(ggsci)
# vignette("ggsci")
DimPlot(pbmc, reduction = "umap", label = TRUE) + 
  scale_color_nejm() +
  NoLegend()

mycolor <- pal_nejm("default", alpha = 0.5)(8)

paletteer

library(paletteer)  
paletteer_c("scico::berlin", n = 10)
## <colors>
## #9EB0FFFF #5AA3DAFF #2D7597FF #194155FF #11181DFF #270C01FF #501802FF #8A3F2AFF #C37469FF #FFACACFF
paletteer_d("RColorBrewer::Paired",n=12)
## <colors>
## #A6CEE3FF #1F78B4FF #B2DF8AFF #33A02CFF #FB9A99FF #E31A1CFF #FDBF6FFF #FF7F00FF #CAB2D6FF #6A3D9AFF #FFFF99FF #B15928FF
paletteer_dynamic("cartography::green.pal", 20)
## <colors>
## #E5F0DAFF #D9E8CEFF #CDE1C2FF #C1D9B6FF #B5D2AAFF #A9CB9FFF #9DC393FF #91BC87FF #85B47BFF #75AA6BFF #65A15CFF #55974CFF #458D3DFF #35832DFF #287721FF #22651DFF #1C5319FF #164116FF #102F12FF #0A1E0FFF

cols4all

# remotes::install_github("mtennekes/cols4all")
library(cols4all)
# c4a_gui()
mycolor <-c4a("light24", 9)

# Color from：Nat Med. 2019 Aug;25(8):1251-1259. 
cbp <-c(
    "#80d7e1","#e4cbf2","#ffb7ba","#bf5046","#b781d2","#ece7a3",
    "#f5cbe1","#e6e5e3","#d2b5ab","#d9e3f5","#f29432","#9c9895"
)
show_col(cbp, labels = TRUE)

DimPlot(pbmc, reduction = "umap", group.by='seurat_clusters', label = T) +
  scale_color_manual(values = cbp)+
  NoLegend()


# Color from：Immunity. 2020 May 19;52(5):808-824.e7.
cbp <- c(
   "#e41e25","#307eb9","#4cb049","#974e9e","#f57f21","#f4ed35",
  "#a65527","#9bc7e0","#b11f2b","#f6b293"
)
show_col(cbp, labels = TRUE)

DimPlot(pbmc, reduction = "umap", group.by='seurat_clusters', label=T) + 
  scale_color_manual(values = cbp)+
  NoLegend()


# Color from：Cell. 2019 Oct 31;179(4):829-845.e20.
cbp <- c(
  "#b38a8f","#bba6a6","#d5b3a5","#e69db8","#c5ae8d","#87b2d4",
  "#babb72","#4975a5","#499994","#8e8786","#93a95d","#f19538",
  "#fcba75","#8ec872","#ad9f35","#8ec872","#d07794","#ff9796",
  "#b178a3","#e56464","#6cb25e","#ca9abe","#d6b54c"
)
show_col(cbp, labels = TRUE)

DimPlot(pbmc, reduction = "umap", group.by='seurat_clusters', label = T) + 
  scale_color_manual(values = cbp) +
  NoLegend()

Pick color from images

# devtools::install_github("joelcarlson/RImagePalette")
library(RImagePalette)
lifeAquatic <- jpeg::readJPEG("color.jpg")
display_image(lifeAquatic)
mycolor <- image_palette(lifeAquatic, n=16) 
show_col(mycolor)

--- title: "Use colorblind-friendly palette for visualization" date: 2023-12-01 date-modified: last-modified categories: - colors - ggplot2 image: colorblind_palette.jpg description: Use ggplot2 to make nice coordinate, colors, and size with friendly colors. --- ```{r setup, include=FALSE} knitr::opts_chunk$set( fig.align = "center", # fig.retina = 3, out.width = "100%", warning = FALSE, # evaluate = FALSE, collapse = TRUE ) ``` ## Color packages ![](colorblind_palette.jpg) ```{r} #| warning: false #| message: false library(here) library(tidyverse) library(patchwork) library(ggsci) library(Seurat) library(RColorBrewer) library(viridis) library(paletteer) library(cols4all) library(RImagePalette) library(scales) ``` ## Basic colors ```{r} # gray colors cbp <- c("gray", "lightgray", "darkgray", "black") barplot(1:4, col = cbp) # 4 colors cbp <- c( "#b8b8b8", "#02ff00", "#f9a506", "#ff3c31" ) barplot(1:4, col = cbp) # 6 colors cbp <- c( "#4C72B0", "#55A868", "#C44E52", "#8172B2", "#CCB974", "#64B5CD" ) barplot(1:6, col = cbp) ``` ```{r} # 8 colors cbp <- c( "#999999", "#E69F00", "#56B4E9", "#009E73", "#F0E442", "#0072B2", "#D55E00", "#CC79A7" ) barplot(1:8, col = cbp) # 9 colors cbp <- c( "#000000", "#999999", "#E69F00", "#56B4E9", "#009E73", "#F0E442", "#0072B2", "#D55E00", "#CC79A7" ) barplot(1:9, col = cbp) ``` ## Color() ```{r} load(here("projects", "2023_scRNA_Seurat", "pbmc_tutorial.RData")) # 657 colors length(colors()) show_col(colors()[1:50]) cbp <-c( "#80d7e1","#e4cbf2","#ffb7ba","#bf5046","#b781d2","#ece7a3", "#f5cbe1","#e6e5e3","#d2b5ab","#d9e3f5","#f29432","#9c9895" ) show_col(cbp) ## Single cell plot p1 <- DimPlot(pbmc, reduction = "umap",label = T) + NoLegend() p2 <- DimPlot(pbmc, reduction = "umap",cols = cbp,label = T)+ NoLegend() p1 + p2 ``` ## RColorBrewer ```{r} library(RColorBrewer) display.brewer.all() col <- brewer.pal(9, "Set1") b1 <- brewer.pal(9, "Set1") b2 <- brewer.pal(8, "Set2") mycolor <- c(b1,b2) ``` ## ggsci ```{r} library(ggsci) # vignette("ggsci") DimPlot(pbmc, reduction = "umap", label = TRUE) + scale_color_nejm() + NoLegend() mycolor <- pal_nejm("default", alpha = 0.5)(8) ``` ## paletteer ```{r} library(paletteer) paletteer_c("scico::berlin", n = 10) paletteer_d("RColorBrewer::Paired",n=12) paletteer_dynamic("cartography::green.pal", 20) ``` ## cols4all ```{r} # remotes::install_github("mtennekes/cols4all") library(cols4all) # c4a_gui() mycolor <-c4a("light24", 9) ``` ```{r} # Color from：Nat Med. 2019 Aug;25(8):1251-1259. cbp <-c( "#80d7e1","#e4cbf2","#ffb7ba","#bf5046","#b781d2","#ece7a3", "#f5cbe1","#e6e5e3","#d2b5ab","#d9e3f5","#f29432","#9c9895" ) show_col(cbp, labels = TRUE) DimPlot(pbmc, reduction = "umap", group.by='seurat_clusters', label = T) + scale_color_manual(values = cbp)+ NoLegend() # Color from：Immunity. 2020 May 19;52(5):808-824.e7. cbp <- c( "#e41e25","#307eb9","#4cb049","#974e9e","#f57f21","#f4ed35", "#a65527","#9bc7e0","#b11f2b","#f6b293" ) show_col(cbp, labels = TRUE) DimPlot(pbmc, reduction = "umap", group.by='seurat_clusters', label=T) + scale_color_manual(values = cbp)+ NoLegend() # Color from：Cell. 2019 Oct 31;179(4):829-845.e20. cbp <- c( "#b38a8f","#bba6a6","#d5b3a5","#e69db8","#c5ae8d","#87b2d4", "#babb72","#4975a5","#499994","#8e8786","#93a95d","#f19538", "#fcba75","#8ec872","#ad9f35","#8ec872","#d07794","#ff9796", "#b178a3","#e56464","#6cb25e","#ca9abe","#d6b54c" ) show_col(cbp, labels = TRUE) DimPlot(pbmc, reduction = "umap", group.by='seurat_clusters', label = T) + scale_color_manual(values = cbp) + NoLegend() ``` ## Pick color from images ```{r} #| eval: false # devtools::install_github("joelcarlson/RImagePalette") library(RImagePalette) lifeAquatic <- jpeg::readJPEG("color.jpg") display_image(lifeAquatic) mycolor <- image_palette(lifeAquatic, n=16) show_col(mycolor) ```