--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/PCA_plot.R	Tue May 20 03:27:01 2014 -0400
@@ -0,0 +1,40 @@
+#Plottool makes a graph of Principal Components created with a Principal Component analysis. 
+#MB
+
+#commands extracting of commandline
+args <- commandArgs(TRUE)
+
+#input files and options
+input <- args[1]
+main_title <- args[2]
+x_title <- args[3]
+y_title <- args[4]
+x_column <- args[5]
+y_column <- args[6]
+names <- args [7] #name of every sample in one file
+#output file
+output <- args[8]
+
+suppressMessages(library("geomorph")) #package geomorph
+
+#reading of input files
+read <- read.csv(file <- input,header = TRUE)
+read2 <- scan(file <- names, what = "", quiet = TRUE)
+
+pca1 <- read[,as.integer(x_column)] #principal component
+pca2 <- read[,as.integer(y_column)] #principal component
+
+png(output) #output in png format
+
+#axis boundaries
+minpca1 = min(pca1) - max(pca1)
+maxpca1 = max(pca1) + max(pca1)
+minpca2 = min(pca2) - max(pca2)
+maxpca2 = max(pca2) + max(pca2)
+
+#creating the plot with principal components and titels
+suppressMessages(plot(pca1,pca2, main = main_title, xlab = x_title, ylab = y_title, pch=20,cex=0.6, xlim = c(minpca1,maxpca1), ylim=c(minpca2,maxpca2)))
+#add labels to data points
+text(pca1,pca2,labels = read2, pos = 2, cex = 0.7,col = heat.colors(35:40))
+
+graphics.off()