3-color palette

# Box plot
bp<-ggplot(ToothGrowth, aes(x=factor(dose), y=len, fill=factor(dose))) +
  geom_boxplot()+theme_bw()
bp + scale_fill_manual(values=c("#999999", "#E69F00", "#56B4E9"))

# Scatter plot
sp<-ggplot(mtcars, aes(x=factor(wt), y=mpg, color=factor(cyl))) + geom_point(size=4)+theme_bw()
sp + scale_color_manual(values=c("#999999", "#E69F00", "#56B4E9"))

another 3-color palette

# Box plot
bp<-ggplot(ToothGrowth, aes(x=factor(dose), y=len, fill=factor(dose))) +
  geom_boxplot()+theme_bw()
bp + scale_fill_manual(values = c("#00AFBB", "#E7B800", "#FC4E07"))

# Scatter plot
sp<-ggplot(mtcars, aes(x=factor(wt), y=mpg, color=factor(cyl))) + geom_point(size=4)+theme_bw()
sp + scale_color_manual(values = c("#00AFBB", "#E7B800", "#FC4E07"))

colorblind-friendly palette

custom.col <- c("#FFDB6D", "#C4961A", "#F4EDCA", 
                "#D16103", "#C3D7A4", "#52854C", "#4E84C4", "#293352")
barplot(rep(1,length(custom.col)),col=custom.col)

# The palette with grey:
cbp1 <- c("#999999", "#E69F00", "#56B4E9", "#009E73",
          "#F0E442", "#0072B2", "#D55E00", "#CC79A7")
barplot(rep(1,length(cbp1)),col=cbp1)

# The palette with black:
cbp2 <- c("#000000", "#E69F00", "#56B4E9", "#009E73",
          "#F0E442", "#0072B2", "#D55E00", "#CC79A7")
barplot(rep(1,length(cbp2)),col=cbp2)

ggplot2 default color palette

refer to: https://stackoverflow.com/questions/8197559/emulate-ggplot2-default-color-palette

library(scales)
hue_pal()(4)

## [1] "#F8766D" "#7CAE00" "#00BFC4" "#C77CFF"

#[1] "#F8766D" "#7CAE00" "#00BFC4" "#C77CFF"
show_col(hue_pal()(4))

show_col(hue_pal()(3))

RColorBrewer package

refer to: https://rdrr.io/cran/RColorBrewer/man/ColorBrewer.html

library(RColorBrewer)
brewer.pal.info

##          maxcolors category colorblind
## BrBG            11      div       TRUE
## PiYG            11      div       TRUE
## PRGn            11      div       TRUE
## PuOr            11      div       TRUE
## RdBu            11      div       TRUE
## RdGy            11      div      FALSE
## RdYlBu          11      div       TRUE
## RdYlGn          11      div      FALSE
## Spectral        11      div      FALSE
## Accent           8     qual      FALSE
## Dark2            8     qual       TRUE
## Paired          12     qual       TRUE
## Pastel1          9     qual      FALSE
## Pastel2          8     qual      FALSE
## Set1             9     qual      FALSE
## Set2             8     qual       TRUE
## Set3            12     qual      FALSE
## Blues            9      seq       TRUE
## BuGn             9      seq       TRUE
## BuPu             9      seq       TRUE
## GnBu             9      seq       TRUE
## Greens           9      seq       TRUE
## Greys            9      seq       TRUE
## Oranges          9      seq       TRUE
## OrRd             9      seq       TRUE
## PuBu             9      seq       TRUE
## PuBuGn           9      seq       TRUE
## PuRd             9      seq       TRUE
## Purples          9      seq       TRUE
## RdPu             9      seq       TRUE
## Reds             9      seq       TRUE
## YlGn             9      seq       TRUE
## YlGnBu           9      seq       TRUE
## YlOrBr           9      seq       TRUE
## YlOrRd           9      seq       TRUE

#par(mar=c(3,4,2,2))
#display.brewer.all()
(mycol=brewer.pal(10,"Paired"))

##  [1] "#A6CEE3" "#1F78B4" "#B2DF8A" "#33A02C" "#FB9A99" "#E31A1C" "#FDBF6F"
##  [8] "#FF7F00" "#CAB2D6" "#6A3D9A"

barplot(rep(1,10),col=mycol)

(mycol=brewer.pal(8,"Dark2"))

## [1] "#1B9E77" "#D95F02" "#7570B3" "#E7298A" "#66A61E" "#E6AB02" "#A6761D"
## [8] "#666666"

barplot(rep(1,8),col=mycol)

scale_xxx_gradient()

frequently used in heatmaps refer to: http://www.sthda.com/english/wiki/ggplot2-colors-how-to-change-colors-automatically-and-manually#continuous-colors

The graph can be colored according to the values of a continuous variable using the functions :

• scale_color_gradient(), scale_fill_gradient() for sequential gradients between two colors
• scale_color_gradient2(), scale_fill_gradient2() for diverging gradients
• scale_color_gradientn(), scale_fill_gradientn() for gradient between n colors

# Color by qsec values
sp<-ggplot(mtcars, aes(x=wt, y=mpg, color=qsec)) + geom_point() +theme_bw()
#sp
summary(mtcars$qsec)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   14.50   16.89   17.71   17.85   18.90   22.90

sp+scale_color_gradient2(low="blue", mid = "white",high="red",
        midpoint = quantile(mtcars$qsec,0.25))

viridis package

useful refs:

• https://cran.r-project.org/web/packages/viridis/vignettes/intro-to-viridis.html
• https://www.thinkingondata.com/something-about-viridis-library/
• https://sjmgarnier.github.io/viridisLite/reference/viridis.html
• https://bookdown.org/hneth/ds4psy/D-4-apx-colors-pkgs.html

library(viridis)
ggplot(data.frame(x = rnorm(10000), y = rnorm(10000)), aes(x = x, y = y))+
  geom_hex() + coord_fixed() +
  scale_fill_viridis() + theme_bw()

It’s also easier to adjust continuous colors into discrete ones with the viridis package.

p <- ggplot(mtcars, aes(wt, mpg))+
    geom_point(size=4, aes(colour = factor(cyl))) +
    theme_bw()
p+scale_color_viridis(discrete=TRUE,option = 'viridis') 

p+scale_color_viridis(discrete=TRUE,option = 'magma') 

p+scale_color_viridis(discrete=TRUE,option = 'turbo') 

library(viridisLite)  # load package
library(unikn) #seecol function
vir_10 <- viridis(n = 10)
seecol(vir_10, col_brd = "white", lwd_brd = 4, 
       title = "Example of a viridis color palette (n = 10)",
       pal_names = paste0("viridis_", 1:10))

8-color palette

colorBlindBlack8  <- c("#000000", "#E69F00", "#56B4E9", "#009E73", 
                       "#F0E442", "#0072B2", "#D55E00", "#CC79A7")
pie(rep(1, 8), col = colorBlindBlack8)

colorBlindGrey8   <- c("#999999", "#E69F00", "#56B4E9", "#009E73", 
                       "#F0E442", "#0072B2", "#D55E00", "#CC79A7")
scales::show_col(colorBlindGrey8)

12-color palette

safe_colorblind_palette <- c("#88CCEE", "#CC6677", "#DDCC77", "#117733", "#332288", "#AA4499", 
                             "#44AA99", "#999933", "#882255", "#661100", "#6699CC", "#888888")
scales::show_col(safe_colorblind_palette)

RColorBrewer: display.brewer.all(colorblindFriendly = T)

refer to: colorblind-friendly-palettes

library(RColorBrewer)
display.brewer.all(colorblindFriendly = T)

#palette using grey
cbPalette <- c("#999999", "#E69F00", "#56B4E9", "#009E73", "#F0E442", "#0072B2", "#D55E00", "#CC79A7")
scales::show_col(cbPalette)
#palette using black
cbbPalette <- c("#000000", "#E69F00", "#56B4E9", "#009E73", "#F0E442", "#0072B2", "#D55E00", "#CC79A7")
scales::show_col(cbPalette)

make transparent colors in R

refer to: Make transparent colors in R

## Transparent colors
## Mark Gardener 2015
## www.dataanalytics.org.uk

t_col <- function(color, percent = 50, name = NULL) {
  #      color = color name
  #      percent = % transparency
  #      name = an optional name for the color
  
  ## Get RGB values for named color
  #rgb.val <- col2rgb(color)
  
  rgb.val=col2rgb(color)
  
  ## Make new color using input color as base and alpha set by transparency
  t.col <- rgb(rgb.val[1], rgb.val[2], rgb.val[3],
               max = 255,
               alpha = (100 - percent) * 255 / 100,
               names = name)
  
  ## Save the color
  #invisible(t.col)
  t.col
}
my.cols=c('black','orange','sky blue','yellow','blue');
my.cols

## [1] "black"    "orange"   "sky blue" "yellow"   "blue"

my.cols2=sapply(my.cols,function(i){t_col(i,percent=80)})
my.cols2

##       black      orange    sky blue      yellow        blue 
## "#00000033" "#FFA50033" "#87CEEB33" "#FFFF0033" "#0000FF33"

par(mfrow=c(2,1))
barplot(1:length(my.cols),col=my.cols)
barplot(1:length(my.cols),col=my.cols2)