Color Maps • NGCHMR

In Getting Started, the NGCHM R package generated colors automatically because no colors were specified. This vignette demonstrates how to explicitly choose colors for the matrix and covariate data by using color maps. The full code block and fully interactive NG-CHM are shown in Resulting NG-CHM.

These examples build on the setup from Getting Started.

Matrix Data Color Map

The function chmNewColorMap() creates a new color map. For a continuous color map, the first argument is a list of breakpoints. Breakpoints must be unique numbers in ascending numerical order. For the TCGA BRCA Expression demo data, reasonable breakpoints are 6.4, 10, and 14. The second argument is a corresponding list of colors for those breakpoints. The colors can be specified by name for standard colors, or by hexadecimal code.

colorMap <- chmNewColorMap(c(6.4, 10, 14), c("steelblue", "antiquewhite", "firebrick"))
# or with equivalent hexadecimal codes:
colorMap <- chmNewColorMap(c(6.4, 10, 14), c("#4682B4", "#FAEBD7", "#B22222"))

In order to use this color map for matrix data in an NG-CHM, a data layer is created with chmNewDataLayer(), and then used in chmNew() as shown below:

dataLayer <- chmNewDataLayer("TCGA BRCA Expression", matrix_data, colorMap)
hm <- chmNew("TCGA BRCA Expression", dataLayer)

Covariate Bar Color Map

The same chmNewColorMap() function also creates discrete color maps. The first argument is a list of the unique values in the data, and the second argument is a list of colors. Standard color names or hexadecimal codes can be used.

mutationColorMap <- chmNewColorMap(c("WT", "MUT"), c("lightsteelblue3", "khaki3"))
## or with equivalent hexadecimal codes:
mutationColorMap <- chmNewColorMap(c("WT", "MUT"), c("#A2B5CD", "#CDC673"))

In the chmNewCovariate() function, an optional third argument is a color map:

covariateBar <- chmNewCovariate("TP53 Mutation (other colors)", covariate_vector, mutationColorMap)

Resulting NG-CHM

Here is the complete code block for this example, followed by the resulting NG-CHM:

library(NGCHMDemoData)
library(NGCHMSupportFiles)
library(NGCHM)
matrix_data_file <- system.file("extdata", "TCGA.BRCA.Expression.csv", package = "NGCHMDemoData")
matrix_data <- as.matrix(read.csv(matrix_data_file, header = TRUE, row.names = 1, check.names = FALSE, stringsAsFactors = FALSE))
covariate_data_file <- system.file("extdata", "TCGA.BRCA.TP53Mutation.csv", package = "NGCHMDemoData")
covariate_data <- as.matrix(read.csv(covariate_data_file, row.names = 1, check.names = FALSE, stringsAsFactors = FALSE))
covariate_vector <- as.vector(covariate_data) # create vector of mutation data
names(covariate_vector) <- rownames(covariate_data) # set the names
colorMap <- chmNewColorMap(c(6.4, 10, 14), c("steelblue", "antiquewhite", "firebrick"))
dataLayer <- chmNewDataLayer("TCGA BRCA Expression", matrix_data, colorMap)
hm <- chmNew("TCGA BRCA Expression Heatmap", dataLayer)
mutationColorMap <- chmNewColorMap(c("WT", "MUT"), c("lightsteelblue3", "khaki3"))
covariateBar <- chmNewCovariate("TP53 Mutation", covariate_vector, mutationColorMap)
hm <- chmAddCovariateBar(hm, "column", covariateBar)
chmExportToHTML(hm, "colormap.html", overwrite = TRUE)
htmltools::tags$iframe(src = "colormap.html", width = "100%", height = 700)