In ZellW/LearnPlotting:

Part 2

Getting ready

Download the script 5644OS_02_01.r and the data sets gene_expression.txt, runners.csv, and apple_stocks.xlsx from your account at http://www.packtpub.com and save them to your hard drive.

How to do it...

Note: I have commented some code out because I will not install JAVA requires to support the XLSX pacakge.

# if you are running the script from a different location
# than the location of the data sets, uncomment the
# next line and point setwd() to the data set location
# setwd("/home/username/Datasets")

### loading packages
if (!require("gplots")) {
install.packages("gplots", dependencies = TRUE)
library(gplots)
}
if (!require("lattice")) {
install.packages("lattice", dependencies = TRUE)
library(lattice)
}
# if (!require("xlsx")) {
# install.packages("xlsx", dependencies = TRUE)
# library(xlsx)
# }

pdf("readingData.pdf")

### loading data and drawing heat maps

# 1) gene_expression.txt
gene_data <- read.table("../data/gene_expression.txt",
  comment.char = "/", 
  blank.lines.skip = TRUE,
  header = TRUE,  
  sep = "\t", 
  nrows = 20)
gene_data <- data.matrix(gene_data)
gene_ratio <- outer(gene_data[,"Treatment"],
  gene_data[,"Control"], 
  FUN = "/")
heatmap.2(gene_ratio, 
  xlab = "Control", 
  ylab = "Treatment", 
  trace = "none",
  main = "gene_expression.txt")

# 2) runners.csv
runner_data <- read.csv("../data/runners.csv")
rownames(runner_data) <- runner_data[,1]
runner_data <- data.matrix(runner_data[,2:ncol(runner_data)])
colnames(runner_data) <- c(2003:2012)
runner_data[runner_data == 0.00] <- NA
heatmap.2(runner_data, 
  dendrogram = "none", 
  Colv = NA,
  Rowv = NA,
  trace = "none", 
  na.color = "gray",
  main = "runners.csv",
  margin = c(8,10))

# # 3) apple_stocks.xlsx
# stocks_table <- read.xlsx("../data/apple_stocks.xlsx", 
#   sheetIndex = 1, 
#   rowIndex = c(1:28), 
#   colIndex = c(1:5,7))
# row_names <- (stocks_table[,1])
# stocks_matrix <- data.matrix(
#   stocks_table[2:ncol(stocks_table)])
# rownames(stocks_matrix) <- as.character(row_names)
# stocks_data = t(stocks_matrix)
# print(levelplot(stocks_data, 
#   col.regions = heat.colors, 
#   margin = c(10,10),  
#   scales = list(x = list(rot = 90)), 
#   main = "apple_stocks.xlsx",
#   ylab = NULL,
#   xlab = NULL))

dev.off()