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