README.md
In caleblareau/BuenColors: Plotting utils and colors for Buenrostrolab

BuenColors

A package that facilitates nice colors created for the Buenrostro Lab. The base of the package including some divergent color schemes were taken from the wesanderson package. This README provides a quick overview of how to use the color schemes with ggplot2 and which palettes are available.

devtools::install_github("caleblareau/BuenColors")

library(BuenColors)

With the library loaded, just type this to get either the continuous or discrete (by default) palette printed in your plot console.

jdb_palette("FantasticFox")

jdb_palette("aqua_brick", type = "continuous")

#>   [1] "algae_earth"    "aqua_brick"     "aqua_tan"       "berry"         
#>   [5] "blue_cyan"      "BottleRocket"   "BottleRocket2"  "brewer_blue"   
#>   [9] "brewer_celsius" "brewer_fire"    "brewer_green"   "brewer_heat"   
#>  [13] "brewer_jamaica" "brewer_marine"  "brewer_orange"  "brewer_purple" 
#>  [17] "brewer_red"     "brewer_spectra" "brewer_violet"  "brewer_yes"    
#>  [21] "calma_azules"   "calma_bosque"   "calma_manudo"   "calma_marino"  
#>  [25] "calma_morado"   "calma_musgos"   "Cavalcanti"     "Chevalier"     
#>  [29] "china_basics"   "china_dragon"   "china_novice"   "china_ranges"  
#>  [33] "china_sunset"   "china_theory"   "china_weirdo"   "citric"        
#>  [37] "citric_yellow"  "citrus"         "corona"         "cyan_brick"    
#>  [41] "cyan_green"     "cyan_pink"      "cyan_purple"    "cyan_tan"      
#>  [45] "cyan_violet"    "Darjeeling"     "Darjeeling2"    "dark_blue"     
#>  [49] "dark_citrus"    "dark_cyan"      "dark_violet"    "dusk_dawn"     
#>  [53] "FantasticFox"   "flame_artic"    "flame_blind"    "flame_flame"   
#>  [57] "flame_light"    "flame_macaw"    "flame_polar"    "flame_volts"   
#>  [61] "flame_watts"    "flame_weird"    "flame_wings"    "forest"        
#>  [65] "forest_citric"  "forest_yellow"  "GrandBudapest"  "GrandBudapest2"
#>  [69] "horizon"        "horizon_extra"  "lawhoops"       "Moonrise1"     
#>  [73] "Moonrise2"      "Moonrise3"      "ocean_aqua"     "ocean_brick"   
#>  [77] "ocean_citrus"   "ocean_earth"    "ocean_green"    "ocean_pink"    
#>  [81] "ocean_red"      "ocean_teal"     "purple_baby"    "purple_pink"   
#>  [85] "Royal1"         "Royal2"         "Rushmore"       "samba_color"   
#>  [89] "samba_light"    "samba_night"    "solar_basic"    "solar_blues"   
#>  [93] "solar_extra"    "solar_flare"    "solar_glare"    "solar_rojos"   
#>  [97] "teal_orange"    "teal_violet"    "white_grove"    "white_jungle"  
#> [101] "white_mango"    "white_orange"   "white_tango"    "wolfgang_basic"
#> [105] "wolfgang_extra" "Zissou"

To keep consistent color designations, one can use the color_map function to link features to their specific hex color annoations. For example,

jdb_color_map(c("HSC"))
#> [1] "#00441B"

returns the hex code associated with HSC in the Buenrostro Lab paradigm. This function may be applied over multiple features--

jdb_color_map(c("HSC", "CMP", "HSC"))
#> [1] "#00441B" "#FFC179" "#00441B"

and will error out when a feature is not recognized--

jdb_color_map(c("WHAT"))
#>  Error: all(name %in% names(jdb_color_maps)) is not TRUE

#>  [1] "B"     "CD4"   "CD8"   "CLP"   "CMP"   "Ery"   "GMP"   "GMP-A" "GMP-B"
#> [10] "GMP-C" "HSC"   "LMPP"  "MEP"   "mono"  "MPP"   "NK"    "pDC"

To coordinate a ggplot feature (e.g. data point in a scatter plot) with a particular color, this post was a life-saver. Specifically, we'll use a named vector to coordinate the discrete values. Here's an example--

xy <- 1:7
cell <- c("GMP-A", "Ery", "CD4", "Ery", "LMPP", "ERY", "MEP")

df <- data.frame(
  xy = xy,
  cell = cell, stringsAsFactors = FALSE
)

ggplot(df, aes(x = xy, y = xy, color = cell)) +
  geom_point(size = 10) + pretty_plot() +
  scale_color_manual(values = jdb_color_maps)
#> Warning: Removed 1 rows containing missing values (geom_point).

P.S.-- this call will return a blank color for features that are not found in the color map ("ERY" in this example).

The above ggplot command works because jdb_color_maps (with an 's') exists as a named vector in the BuenColors NAMESPACE. The provided function (jdb_color_map) does not have an 's' by the way. This same syntax of supplying a named vector should work for all discrete color scale functionalities in ggplot.

Discrete colors

The trick here is to use scale_color_manual like it is shown here--

library(ggplot2)
ggplot(iris, aes(Sepal.Length, Sepal.Width, color = Species)) + 
  geom_point() + pretty_plot() + 
  scale_color_manual(values = jdb_palette("brewer_spectra"))

Continuous fill

The trick here is to use scale_color_gradientn like it is shown here--

df <- data.frame(x = rnorm(1000), y = 0)
ggplot(df, aes(x=x, y=y, colour=x)) + geom_point() + 
  scale_color_gradientn(colors = jdb_palette("flame_light")) +
  pretty_plot()

Density Plot

Best way that I've found to make the density color function represented in the points. Thanks to Kamil Slowikowski for figuring this out.

dat <- data.frame(
  x = c(
    rnorm(1e4, mean = 0, sd = 0.1),
    rnorm(1e3, mean = 0, sd = 0.1)
  ),
  y = c(
    rnorm(1e4, mean = 0, sd = 0.1),
    rnorm(1e3, mean = 0.1, sd = 0.2)
  )
)
dat$density <- get_density(dat$x, dat$y)
ggplot2::ggplot(dat) + geom_point(aes(x, y, color = density)) + 
  scale_color_gradientn(colors = jdb_palette("solar_extra")) +
  pretty_plot()

Shuffle Plot Order

Quick wrapper using shuf to change the order of plotting points (to a random presentation) to avoid hiding effects.

tdf<-paste(system.file('rds',package='BuenColors'),'basicTSNE.rds',sep='/')
df <- readRDS(tdf)
ggplot(shuf(df)) + geom_point(aes(X1, X2, color = counts)) + 
  scale_color_gradientn(colors = jdb_palette("solar_extra")) +
  pretty_plot()

Here's what each palette looks like on a continuous scale.

Here are the discrete color units that go into each scale. If n is small and discrete, note that the colors that are selected are read from left to right.