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1 #!/usr/bin/env Rscript
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2
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3 args = commandArgs(TRUE)
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4 countDataPath = args[1]
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5 statsDataPath = args[2]
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6 logFC = args[3]
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7 logCPM = args[4]
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8 pValue = args[5]
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9 fdr = args[6]
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10
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11 require(preprocessCore)
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12 require(gplots)
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13
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14 #prepare counts data --------------------------------------------------------
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15 countData = read.table(countDataPath, comment = "",
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16 sep = "\t")
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17
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18 groups = sapply(as.character(countData[1, -1]), strsplit, ":")
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19 groups = as.vector(t(countData[1, -1]))
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20
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21 names = as.vector(t(countData[2, -1]))
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22
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23 countData = countData[-c(1,2), ]
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24 rownames(countData) = countData[, 1]
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25 countData = countData[, -1]
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26 colnames(countData) = names
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27
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28 countData = countData[, order(groups, names)]
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29
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30 # prepare stats data ------------------------------------------------------
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31
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32 statsData = read.table(statsDataPath, sep = "\t",
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33 header = T)
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34
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35 colnames(statsData)[-1] = sapply(colnames(statsData)[-1], function(x){
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36 unlist(strsplit(x, ".", fixed = T))[3]
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37 })
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38
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39 wh = which(abs(statsData$logFC) >= logFC & statsData$logCPM >= logCPM & statsData$PValue <= pValue & statsData$FDR <= fdr)
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40
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41 for(i in 1:ncol(countData)){
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42 countData[,i] = as.numeric(countData[,i])
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43 }
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44
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45 countDataNorm = normalize.quantiles(as.matrix(countData), copy = T)
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46 countDataNormLog = log(countDataNorm + 1, 2)
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47
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48 colnames(countDataNormLog) = colnames(countData)
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49 rownames(countDataNormLog) = rownames(countData)
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50
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51 #svg("heatmap.svg", width = 3+length(names), height = 1/2*length(wh))
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52 pdf("heatmap.pdf")
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53
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54 heatmap.2(
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55 countDataNormLog[wh, ],
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56 density.info=c("none"),
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57 hclustfun = function(x) hclust(x, method = "average"),
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58 distfun = function(x) as.dist(1-cor(t(x))),
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59 col = bluered(50),
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60 scale = 'row',
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61 trace = "none", #lwid = c(1, length(names)), lhei = c(1,1/3*length(wh)),
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62 # Rowv=NA,
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63 Colv = NA,
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64 margins = c(7, 8)
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65 )
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66
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67 dev.off()
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68
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