#!/usr/bin/env Rscript

#this programs normalizes a saint input file based on the spectral counts of "signficant" preys
# that is, preys with an FDR <= the secondary cutoff as supplied to the dotplot script

args <- commandArgs(trailingOnly = TRUE)

d = read.delim(args[1], header=T, as.is=T)
d <- d[d$BFDR <= as.numeric(args[2]),]

baitn = 1
curr_bait <- d$Bait[1]
s <- vector()
s[1] = 0
for(i in 1:length(d$Bait)){
	if(curr_bait != d$Bait[i]){
		baitn <- baitn + 1
		curr_bait <- d$Bait[i]
		s[baitn] <- d$AvgSpec[i]
	}
	else{
		s[baitn] <- s[baitn] + d$AvgSpec[i]
	}
}

med.s = median(s)
s = s / med.s

d_n <- d
baitn = 1
curr_bait <- d_n$Bait[1]
for(i in 1:length(d_n$Bait)){
	if(curr_bait != d_n$Bait[i]){
		baitn <- baitn + 1
		curr_bait <- d_n$Bait[i]
		d_n$AvgSpec[i] <- d_n$AvgSpec[i]/s[baitn]
	}
	else{
		d_n$AvgSpec[i] <- d_n$AvgSpec[i]/s[baitn]
	}
}

#print normalized data to file

write.table(d_n, file = "norm_saint.txt", sep="\t", quote=F, row.names=F)