In-class Ex5c: Heat Maps

Heat Maps

Installing and launching R packages, and loading data

pacman::p_load(seriation, dendextend, heatmaply, tidyverse)
wh <- read_csv("data/WHData-2018.csv") 

Static Heatmaps

Preparing the data using by changing the rows by country name instead of row number

row.names(wh) <- wh$Country

Transforming the data frame into a matrix to be able to create heat maps

wh1 <- dplyr::select(wh, c(3, 7:12))
wh_matrix <- data.matrix(wh)

Plot default cluster heatmap using heatmap() of base R Stats package

wh_heatmap <- heatmap(wh_matrix)

Use the arguments Rowv=NA and Colv=NA to switch off the option of plotting the row and column dendrograms.

wh_heatmap <- heatmap(wh_matrix,
                      Rowv=NA, Colv=NA)

To normalize the matrix using scale argument for a more informative visual. Also note that margins argument is used to ensure that the entire x-axis labels are displayed completely and, cexRow and cexCol arguments are used to define the font size used for y-axis and x-axis labels respectively.

wh_heatmap <- heatmap(wh_matrix,
                      scale="column",
                      cexRow = 0.6, 
                      cexCol = 0.8,
                      margins = c(10, 4))

Interactive Heatmaps

Using heatmaply package

heatmaply(wh_matrix[, -c(1, 2, 4, 5)])

Scaling method when assume to be normal distribution

heatmaply(wh_matrix[, -c(1, 2, 4, 5)],
          scale = "column")

Normalization method when assume to be different or non-normal distributions so that it is easily comparable on the same scale

heatmaply(normalize(wh_matrix[, -c(1, 2, 4, 5)]))

Percentizing method

heatmaply(percentize(wh_matrix[, -c(1, 2, 4, 5)]))

OLO - optimal leaf ordering, GW - Gruvaeus and Wainer

heatmaply(normalize(wh_matrix[, -c(1, 2, 4, 5)]),
          seriate = "OLO")

heatmaply(normalize(wh_matrix[, -c(1, 2, 4, 5)]),
          seriate = "GW")

Other plotting features to ensure cartographic quality heatmap can be produced

• colors is used to change the colour palette

• k_row is used to produce 5 groups.

• margins is used to change the top margin to 60 and row margin to 200.

• fontsizw_row and fontsize_col are used to change the font size for row and column labels

• main is used to write the main title of the plot.

• xlab and ylab are used to write the x-axis and y-axis labels respectively.

heatmaply(normalize(wh_matrix[, -c(1, 2, 4, 5)]),
          Colv=NA,
          seriate = "none",
          colors = Blues,
          k_row = 5,
          margins = c(NA,200,60,NA),
          fontsize_row = 4,
          fontsize_col = 5,
          main="World Happiness Score and Variables by Country, 2018 \nDataTransformation using Normalise Method",
          xlab = "World Happiness Indicators",
          ylab = "World Countries"
          )