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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 pheatmapj_loc <- paste(args[9],"pheatmap_j.R",sep="/")
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6
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7 library('latticeExtra')
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8 library('RColorBrewer')
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9 library('grid')
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10 library(reshape2)
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11 source(pheatmapj_loc)
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12
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13 data.file <- read.table("SC_data.txt", sep="\t", header=TRUE, row.names=1) ### import spectral count data
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14 data.file2 <- read.table("FDR_data.txt", sep="\t", header=TRUE, row.names=1) ### import FDR count data
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15 bait_l <- scan(args[4], what="") ### import bait list
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16 if(args[5] == 0) prey_l <- scan(args[6], what="") ### import prey list
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17 methd <- args[7]
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18 dist_methd <- args[8]
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19
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20 #setting parameters
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21
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22 Sfirst=as.numeric(args[1]) #first FDR cutoff
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23 Ssecond=as.numeric(args[2]) #second FDR cutoff
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24 maxp=as.integer(args[3]) #maximum value for a spectral count
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25
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26 #extract only needed data
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27
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28 if(args[5] == 0){
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29 remove <- vector()
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30 remove <- prey_l[prey_l %in% row.names(data.file)]
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31 prey_l <- prey_l[prey_l %in% remove]
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32 remove <- bait_l[bait_l %in% names(data.file)]
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33 bait_l <- bait_l[bait_l %in% remove]
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34 data.file <- data.file[prey_l, bait_l]
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35 data.file2 <- data.file2[prey_l, bait_l]
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36 } else{
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37 remove <- vector()
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38 remove <- bait_l[bait_l %in% names(data.file)]
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39 bait_l <- bait_l[bait_l %in% remove]
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40 data.file <- data.file[, bait_l]
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41 data.file2 <- data.file2[, bait_l]
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42 prey_keep = apply(data.file2, 1, function(x) sum(x<=Sfirst) >= 1)
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43 data.file <- data.file[prey_keep,]
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44 data.file2 <- data.file2[prey_keep,]
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45 }
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46
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47 #determine bait and prey ordering
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48
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49 y_ord=factor(names(data.file[1,]),levels=bait_l)
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50
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51 if(args[5] == 0){
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52 x_ord=factor(rownames(data.file),levels=prey_l)
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53 } else {
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54
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55 data.file <- data.file[which(rowSums(data.file) > 0),]
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56 dist_prey <- dist(as.matrix(data.file), method= dist_methd)
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57
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58 if(methd == "ward"){
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59 dist_prey <- dist_prey^2
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60 }
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61
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62 hc_prey <- hclust(dist_prey, method = methd)
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63
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64 data.file = data.file[hc_prey$order, , drop = FALSE]
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65 data.file2 = data.file2[hc_prey$order, , drop = FALSE]
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66
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67 x_ord=factor(row.names(data.file), levels=row.names(data.file))
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68 }
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69
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70 df<-data.frame(y=rep(y_ord, nrow(data.file))
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71 ,x=rep(x_ord, each=ncol(data.file))
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72 ,z1=as.vector(t(data.file)) # Circle color
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73 ,z2=as.vector(t(data.file/apply(data.file,1,max))) # Circle size
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74 ,z3=as.vector(t(data.file2)) # FDR
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75 )
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76
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77 df$z1[df$z1>maxp] <- maxp #maximum value for spectral count
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78 df$z2[df$z2==0] <- NA
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79 df$z3[df$z3>Ssecond] <- 0.05*maxp
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80 df$z3[df$z3<=Ssecond & df$z3>Sfirst] <- 0.5*maxp
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81 df$z3[df$z3<=Sfirst] <- 1*maxp
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82 df$z4 <- df$z1
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83 df$z4[df$z4==0] <- 0
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84 df$z4[df$z4>0] <- 2.5
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85
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86 # The labeling for the colorkey
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87
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88 labelat = c(0, maxp)
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89 labeltext = c(0, maxp)
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90
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91 # color scheme to use
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92
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93 nmb.colors<-maxp
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94 z.colors<-grey(rev(seq(0,0.9,0.9/nmb.colors))) #grayscale color scale
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95
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96 #plot dotplot
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97
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98 pl <- levelplot(z1~x*y, data=df
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99 ,col.regions =z.colors #terrain.colors(100)
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100 ,scales = list(x = list(rot = 90), y=list(cex=0.8), tck=0) # rotates X,Y labels and changes scale
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101 ,colorkey = FALSE
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102 #,colorkey = list(space="bottom", width=1.5, height=0.3, labels=list(at = labelat, labels = labeltext)) #put colorkey at top with my labeling scheme
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103 ,xlab="Prey", ylab="Bait"
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104 ,panel=function(x,y,z,...,col.regions){
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105 print(x)
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106 z.c<-df$z1[ (df$x %in% as.character(x)) & (df$y %in% y)]
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107 z.2<-df$z2[ (df$x %in% as.character(x)) & (df$y %in% y)]
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108 z.3<-df$z3
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109 z.4<-df$z4
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110 panel.xyplot(x,y
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111 ,as.table=TRUE
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112 ,pch=21 # point type to use (circles in this case)
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113 ,cex=((z.2-min(z.2,na.rm=TRUE))/(max(z.2,na.rm=TRUE)-min(z.2,na.rm=TRUE)))*3 #circle size
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114 ,fill=z.colors[floor((z.c-min(z.c,na.rm=TRUE))*nmb.colors/(max(z.c,na.rm=TRUE)-min(z.c,na.rm=TRUE)))+1] # circle colors
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115 ,col=z.colors[1+z.3] # border colors
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116 ,lex=z.4 #border thickness
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117 )
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118 }
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119 #,main="Fold change" # graph main title
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120 )
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121 if(ncol(data.file) > 4) ht=3.5+(0.36*((ncol(data.file)-1)-4)) else ht=3.5
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122 if(nrow(data.file) > 20) wd=8.25+(0.29*(nrow(data.file)-20)) else wd=5.7+(0.28*(nrow(data.file)-10))
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123 pdf("dotplot.pdf", onefile = FALSE, paper = "special", height = ht, width = wd, pointsize = 2)
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124 print(pl)
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125 dev.off()
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126
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127 #plot heatmap
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128
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129 heat_df <- acast(df, y~x, value.var="z1")
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130 heat_df <- apply(heat_df, 2, rev)
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131
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132 if(ncol(data.file) > 4) ht=3.5+(0.1*((ncol(data.file)-1)-4)) else ht=3.5
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133 if(nrow(data.file) > 20) wd=8.25+(0.1*(nrow(data.file)-20)) else wd=5+(0.1*(nrow(data.file)-10))
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134 pdf("heatmap_borders.pdf", onefile = FALSE, paper = "special", height = ht, width = wd, pointsize = 2)
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135 pheatmap_j(heat_df, scale="none", border_color="black", border_width = 0.1, cluster_rows=FALSE, cluster_cols=FALSE, col=colorRampPalette(c("#FFFFFF", brewer.pal(9,"Blues")))(100))
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136 dev.off()
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137
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138 pdf("heatmap_no_borders.pdf", onefile = FALSE, paper = "special", height = ht, width = wd, pointsize = 2)
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139 pheatmap_j(heat_df, scale="none", border_color=NA, cluster_rows=FALSE, cluster_cols=FALSE, col=colorRampPalette(c("#FFFFFF", brewer.pal(9,"Blues")))(100))
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140 dev.off()
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