|
5
|
1 #The Csize tool creates a plot with a Principal Component
|
|
|
2 #and the centroid size (created with a procrustes analysis)
|
|
|
3 #MB
|
|
|
4
|
|
|
5
|
|
|
6 #commandline arguments
|
|
|
7 args <- commandArgs(TRUE)
|
|
|
8
|
|
|
9 #inputs
|
|
|
10 input_PCA <- args[1]
|
|
|
11 input_Csize <- args[2]
|
|
|
12 main_title <- args[3]
|
|
|
13 x_title <- args[4]
|
|
|
14 y_title <- args[5]
|
|
|
15 x_column <- args[6]
|
|
|
16 names <- args [7] #sample names in one file
|
|
|
17 output <- args[8]
|
|
|
18
|
|
|
19 #library geomorph
|
|
|
20 suppressMessages(library("geomorph"))
|
|
|
21 #reading of the input files
|
|
|
22 read <- read.csv(file <- input_PCA, header = TRUE) #principal components
|
|
|
23 read2 <- read.csv(file <- input_Csize, header = TRUE) #centroid size
|
|
|
24 read3 <- scan(file <- names, what = "", quiet = TRUE)
|
|
|
25 pca1 <- read[,as.integer(x_column)] #principal component
|
|
|
26 read2 <- read2[,1] #centroid size
|
|
|
27
|
|
|
28 #output
|
|
|
29 png(output)
|
|
|
30
|
|
|
31 #creating plot with pca and centroid size
|
|
|
32 suppressMessages(plot(pca1,read2, main = main_title, xlab = x_title, ylab = y_title, pch=20,cex=0.6))
|
|
|
33 #adding labels to datapoints
|
|
|
34 text(pca1,read2,labels = read3, pos = 3, cex = 0.6, col = 'red')
|
|
|
35
|
|
|
36 graphics.off()
|
