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3
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1 #!/usr/bin/env Rscript
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2
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3 args <- commandArgs(trailingOnly = TRUE)
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4
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5 d = read.delim(args[1], header=T, as.is=T)
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6
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7 d2 = d
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8 d2s = d
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9
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10 ss_cutoff <- as.numeric(args[2])
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11 ### Here I'm only going to take the preys which appeared in at least 2 baits with >args[2] counts
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12 id = apply(d, 1, function(x) sum(x>ss_cutoff) >= 2)
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13 id2 = apply(d, 1, function(x) sum(x>ss_cutoff) < 2)
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14 d2 = d2[id, ]
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15 d2s = d2s[id2, 0]
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16 max.d2 = max(as.numeric(as.matrix(d2)))
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17 d2 = d2 / max.d2 * 10
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18
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19 d3 = data.frame(PROT = rownames(d2), d2)
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20
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21 outfile <- paste(c(args[3]), "dat", sep=".")
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22
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23 ### The following file is the outcome of running this step.
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24 write.table(d3, outfile, sep="\t", quote=F, row.names=F)
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25 ### This is the final input file for nested cluster algorithm
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26
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27 write.table(d2s, "singletons.txt", quote=F)
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28
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