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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 library('latticeExtra')
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6 library('colorRamps')
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7
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8 data.file <- read.table("SC_data.txt", sep="\t", header=TRUE, row.names=1) ### import spectral count data
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9 data.file2 <- read.table("FDR_data.txt", sep="\t", header=TRUE, row.names=1) ### import FDR count data
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10 data.file3 <- read.table("clustered_matrix.txt", sep="\t", header=TRUE, row.names=1) ### import clustered matrix
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11 data.file4 <- scan("singletons.txt", what="", sep="\n", strip.white=T) ### import singleton data
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12
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13 #setting parameters
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14
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15 Sfirst=as.numeric(args[1]) #first FDR cutoff
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16 Ssecond=as.numeric(args[2]) #second FDR cutoff
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17 maxp=as.integer(args[3]) #maximum value for a spectral count
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18
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19 #calculate column and row lengths
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20
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21 #determine bait and prey ordering
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22
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23 bait_levels=names(data.file3)
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24 prey_levels=c(rownames(data.file3),data.file4)
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25
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26 x_ord=factor(row.names(data.file),levels=prey_levels)
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27 y_ord=factor(names(data.file),levels=bait_levels)
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28
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29 df<-data.frame(y=rep(y_ord,nrow(data.file))
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30 ,x=rep(x_ord, each=ncol(data.file))
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31 ,z1=as.vector(t(data.file)) # Circle color
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32 ,z2=as.vector(t(data.file/apply(data.file,1,max))) # Circle size
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33 ,z3=as.vector(t(data.file2)) # FDR
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34 )
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35
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36 df$z1[df$z1>maxp] <- maxp #maximum value for spectral count
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37 df$z2[df$z2==0] <- NA
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38 df$z3[df$z3>Ssecond] <- 0.05*maxp
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39 df$z3[df$z3<=Ssecond & df$z3>Sfirst] <- 0.5*maxp
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40 df$z3[df$z3<=Sfirst] <- 1*maxp
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41 df$z4 <- df$z1
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42 df$z4[df$z4==0] <- 0
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43 df$z4[df$z4>0] <- 2.5
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44
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45 # The labeling for the colorkey
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46
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47 labelat = c(0, maxp)
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48 labeltext = c(0, maxp)
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49
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50 # color scheme to use
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51
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52 nmb.colors<-maxp
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53 z.colors<-grey(rev(seq(0,0.9,0.9/nmb.colors))) #grayscale color scale
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54
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55 #plot
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56
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57 pl <- levelplot(z1~x*y, data=df
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58 ,col.regions =z.colors #terrain.colors(100)
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59 ,scales = list(x = list(rot = 90), y=list(cex=0.8), tck=0) # rotates X,Y labels and changes scale
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60 ,colorkey = FALSE
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61 ,xlab="Prey", ylab="Bait"
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62 ,panel=function(x,y,z,...,col.regions){
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63 print(x)
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64 z.c<-df$z1[ (df$x %in% as.character(x)) & (df$y %in% y)]
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65 z.2<-df$z2[ (df$x %in% as.character(x)) & (df$y %in% y)]
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66 z.3<-df$z3
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67 z.4<-df$z4
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68 panel.xyplot(x,y
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69 ,as.table=TRUE
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70 ,pch=21 # point type to use (circles in this case)
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71 ,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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72 ,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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73 ,col=z.colors[1+z.3] # border colors
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74 ,lex=z.4 #border thickness
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75 )
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76 }
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77 #,main="Fold change" # graph main title
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78 )
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79 if(ncol(data.file) > 4) ht=3.5+(0.36*((ncol(data.file)-1)-4)) else ht=3.5
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80 if(nrow(data.file) > 20) wd=8.25+(0.29*(nrow(data.file)-20)) else wd=5+(0.28*(nrow(data.file)-10))
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81 pdf("dotplot.pdf", onefile = FALSE, paper = "special", height = ht, width = wd, pointsize = 2)
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82 print(pl)
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83 dev.off()
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