Mercurial > repos > bornea > dotplot_runner

comparison Dotplot_Release/R_dotPlot_nc.R @ 0:dfa3436beb67 draft

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author bornea
date Fri, 29 Jan 2016 09:56:02 -0500
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-1:000000000000 0:dfa3436beb67
1 #!/usr/bin/env Rscript
2
3 args <- commandArgs(trailingOnly = TRUE)
4
5 pheatmapj_loc <- paste(args[9],"pheatmap_j.R",sep="/")
6
7 library('latticeExtra')
8 library('RColorBrewer')
9 library('grid')
10 library(reshape2)
11 source(pheatmapj_loc)
12
13 data.file <- read.table("SC_data.txt", sep="\t", header=TRUE, row.names=1) ### import spectral count data
14 data.file2 <- read.table("FDR_data.txt", sep="\t", header=TRUE, row.names=1) ### import FDR count data
15 bait_l <- scan(args[4], what="") ### import bait list
16 if(args[5] == 0) prey_l <- scan(args[6], what="") ### import prey list
17 methd <- args[7]
18 dist_methd <- args[8]
19
20 #setting parameters
21
22 Sfirst=as.numeric(args[1]) #first FDR cutoff
23 Ssecond=as.numeric(args[2]) #second FDR cutoff
24 maxp=as.integer(args[3]) #maximum value for a spectral count
25
26 #extract only needed data
27
28 if(args[5] == 0){
29 remove <- vector()
30 remove <- prey_l[prey_l %in% row.names(data.file)]
31 prey_l <- prey_l[prey_l %in% remove]
32 remove <- bait_l[bait_l %in% names(data.file)]
33 bait_l <- bait_l[bait_l %in% remove]
34 data.file <- data.file[prey_l, bait_l]
35 data.file2 <- data.file2[prey_l, bait_l]
36 } else{
37 remove <- vector()
38 remove <- bait_l[bait_l %in% names(data.file)]
39 bait_l <- bait_l[bait_l %in% remove]
40 data.file <- data.file[, bait_l]
41 data.file2 <- data.file2[, bait_l]
42 prey_keep = apply(data.file2, 1, function(x) sum(x<=Sfirst) >= 1)
43 data.file <- data.file[prey_keep,]
44 data.file2 <- data.file2[prey_keep,]
45 }
46
47 #determine bait and prey ordering
48
49 y_ord=factor(names(data.file[1,]),levels=bait_l)
50
51 if(args[5] == 0){
52 x_ord=factor(rownames(data.file),levels=prey_l)
53 } else {
54
55 data.file <- data.file[which(rowSums(data.file) > 0),]
56 dist_prey <- dist(as.matrix(data.file), method= dist_methd)
57
58 if(methd == "ward"){
59 dist_prey <- dist_prey^2
60 }
61
62 hc_prey <- hclust(dist_prey, method = methd)
63
64 data.file = data.file[hc_prey$order, , drop = FALSE]
65 data.file2 = data.file2[hc_prey$order, , drop = FALSE]
66
67 x_ord=factor(row.names(data.file), levels=row.names(data.file))
68 }
69
70 df<-data.frame(y=rep(y_ord, nrow(data.file))
71 ,x=rep(x_ord, each=ncol(data.file))
72 ,z1=as.vector(t(data.file)) # Circle color
73 ,z2=as.vector(t(data.file/apply(data.file,1,max))) # Circle size
74 ,z3=as.vector(t(data.file2)) # FDR
75 )
76
77 df$z1[df$z1>maxp] <- maxp #maximum value for spectral count
78 df$z2[df$z2==0] <- NA
79 df$z3[df$z3>Ssecond] <- 0.05*maxp
80 df$z3[df$z3<=Ssecond & df$z3>Sfirst] <- 0.5*maxp
81 df$z3[df$z3<=Sfirst] <- 1*maxp
82 df$z4 <- df$z1
83 df$z4[df$z4==0] <- 0
84 df$z4[df$z4>0] <- 2.5
85
86 # The labeling for the colorkey
87
88 labelat = c(0, maxp)
89 labeltext = c(0, maxp)
90
91 # color scheme to use
92
93 nmb.colors<-maxp
94 z.colors<-grey(rev(seq(0,0.9,0.9/nmb.colors))) #grayscale color scale
95
96 #plot dotplot
97
98 pl <- levelplot(z1~x*y, data=df
99 ,col.regions =z.colors #terrain.colors(100)
100 ,scales = list(x = list(rot = 90), y=list(cex=0.8), tck=0) # rotates X,Y labels and changes scale
101 ,colorkey = FALSE
102 #,colorkey = list(space="bottom", width=1.5, height=0.3, labels=list(at = labelat, labels = labeltext)) #put colorkey at top with my labeling scheme
103 ,xlab="Prey", ylab="Bait"
104 ,panel=function(x,y,z,...,col.regions){
105 print(x)
106 z.c<-df$z1[ (df$x %in% as.character(x)) & (df$y %in% y)]
107 z.2<-df$z2[ (df$x %in% as.character(x)) & (df$y %in% y)]
108 z.3<-df$z3
109 z.4<-df$z4
110 panel.xyplot(x,y
111 ,as.table=TRUE
112 ,pch=21 # point type to use (circles in this case)
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
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
115 ,col=z.colors[1+z.3] # border colors
116 ,lex=z.4 #border thickness
117 )
118 }
119 #,main="Fold change" # graph main title
120 )
121 if(ncol(data.file) > 4) ht=3.5+(0.36*((ncol(data.file)-1)-4)) else ht=3.5
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))
123 pdf("dotplot.pdf", onefile = FALSE, paper = "special", height = ht, width = wd, pointsize = 2)
124 print(pl)
125 dev.off()
126
127 #plot heatmap
128
129 heat_df <- acast(df, y~x, value.var="z1")
130 heat_df <- apply(heat_df, 2, rev)
131
132 if(ncol(data.file) > 4) ht=3.5+(0.1*((ncol(data.file)-1)-4)) else ht=3.5
133 if(nrow(data.file) > 20) wd=8.25+(0.1*(nrow(data.file)-20)) else wd=5+(0.1*(nrow(data.file)-10))
134 pdf("heatmap_borders.pdf", onefile = FALSE, paper = "special", height = ht, width = wd, pointsize = 2)
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))
136 dev.off()
137
138 pdf("heatmap_no_borders.pdf", onefile = FALSE, paper = "special", height = ht, width = wd, pointsize = 2)
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))
140 dev.off()