Mercurial > repos > bornea > dotplot_runner
view Dotplot_Release/R_dotPlot_nc.R @ 1:7e98f893e9ae draft
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author | bornea |
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date | Fri, 29 Jan 2016 09:57:31 -0500 |
parents | dfa3436beb67 |
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#!/usr/bin/env Rscript args <- commandArgs(trailingOnly = TRUE) pheatmapj_loc <- paste(args[9],"pheatmap_j.R",sep="/") library('latticeExtra') library('RColorBrewer') library('grid') library(reshape2) source(pheatmapj_loc) data.file <- read.table("SC_data.txt", sep="\t", header=TRUE, row.names=1) ### import spectral count data data.file2 <- read.table("FDR_data.txt", sep="\t", header=TRUE, row.names=1) ### import FDR count data bait_l <- scan(args[4], what="") ### import bait list if(args[5] == 0) prey_l <- scan(args[6], what="") ### import prey list methd <- args[7] dist_methd <- args[8] #setting parameters Sfirst=as.numeric(args[1]) #first FDR cutoff Ssecond=as.numeric(args[2]) #second FDR cutoff maxp=as.integer(args[3]) #maximum value for a spectral count #extract only needed data if(args[5] == 0){ remove <- vector() remove <- prey_l[prey_l %in% row.names(data.file)] prey_l <- prey_l[prey_l %in% remove] remove <- bait_l[bait_l %in% names(data.file)] bait_l <- bait_l[bait_l %in% remove] data.file <- data.file[prey_l, bait_l] data.file2 <- data.file2[prey_l, bait_l] } else{ remove <- vector() remove <- bait_l[bait_l %in% names(data.file)] bait_l <- bait_l[bait_l %in% remove] data.file <- data.file[, bait_l] data.file2 <- data.file2[, bait_l] prey_keep = apply(data.file2, 1, function(x) sum(x<=Sfirst) >= 1) data.file <- data.file[prey_keep,] data.file2 <- data.file2[prey_keep,] } #determine bait and prey ordering y_ord=factor(names(data.file[1,]),levels=bait_l) if(args[5] == 0){ x_ord=factor(rownames(data.file),levels=prey_l) } else { data.file <- data.file[which(rowSums(data.file) > 0),] dist_prey <- dist(as.matrix(data.file), method= dist_methd) if(methd == "ward"){ dist_prey <- dist_prey^2 } hc_prey <- hclust(dist_prey, method = methd) data.file = data.file[hc_prey$order, , drop = FALSE] data.file2 = data.file2[hc_prey$order, , drop = FALSE] x_ord=factor(row.names(data.file), levels=row.names(data.file)) } df<-data.frame(y=rep(y_ord, nrow(data.file)) ,x=rep(x_ord, each=ncol(data.file)) ,z1=as.vector(t(data.file)) # Circle color ,z2=as.vector(t(data.file/apply(data.file,1,max))) # Circle size ,z3=as.vector(t(data.file2)) # FDR ) df$z1[df$z1>maxp] <- maxp #maximum value for spectral count df$z2[df$z2==0] <- NA df$z3[df$z3>Ssecond] <- 0.05*maxp df$z3[df$z3<=Ssecond & df$z3>Sfirst] <- 0.5*maxp df$z3[df$z3<=Sfirst] <- 1*maxp df$z4 <- df$z1 df$z4[df$z4==0] <- 0 df$z4[df$z4>0] <- 2.5 # The labeling for the colorkey labelat = c(0, maxp) labeltext = c(0, maxp) # color scheme to use nmb.colors<-maxp z.colors<-grey(rev(seq(0,0.9,0.9/nmb.colors))) #grayscale color scale #plot dotplot pl <- levelplot(z1~x*y, data=df ,col.regions =z.colors #terrain.colors(100) ,scales = list(x = list(rot = 90), y=list(cex=0.8), tck=0) # rotates X,Y labels and changes scale ,colorkey = FALSE #,colorkey = list(space="bottom", width=1.5, height=0.3, labels=list(at = labelat, labels = labeltext)) #put colorkey at top with my labeling scheme ,xlab="Prey", ylab="Bait" ,panel=function(x,y,z,...,col.regions){ print(x) z.c<-df$z1[ (df$x %in% as.character(x)) & (df$y %in% y)] z.2<-df$z2[ (df$x %in% as.character(x)) & (df$y %in% y)] z.3<-df$z3 z.4<-df$z4 panel.xyplot(x,y ,as.table=TRUE ,pch=21 # point type to use (circles in this case) ,cex=((z.2-min(z.2,na.rm=TRUE))/(max(z.2,na.rm=TRUE)-min(z.2,na.rm=TRUE)))*3 #circle size ,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 ,col=z.colors[1+z.3] # border colors ,lex=z.4 #border thickness ) } #,main="Fold change" # graph main title ) if(ncol(data.file) > 4) ht=3.5+(0.36*((ncol(data.file)-1)-4)) else ht=3.5 if(nrow(data.file) > 20) wd=8.25+(0.29*(nrow(data.file)-20)) else wd=5.7+(0.28*(nrow(data.file)-10)) pdf("dotplot.pdf", onefile = FALSE, paper = "special", height = ht, width = wd, pointsize = 2) print(pl) dev.off() #plot heatmap heat_df <- acast(df, y~x, value.var="z1") heat_df <- apply(heat_df, 2, rev) if(ncol(data.file) > 4) ht=3.5+(0.1*((ncol(data.file)-1)-4)) else ht=3.5 if(nrow(data.file) > 20) wd=8.25+(0.1*(nrow(data.file)-20)) else wd=5+(0.1*(nrow(data.file)-10)) pdf("heatmap_borders.pdf", onefile = FALSE, paper = "special", height = ht, width = wd, pointsize = 2) 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)) dev.off() pdf("heatmap_no_borders.pdf", onefile = FALSE, paper = "special", height = ht, width = wd, pointsize = 2) pheatmap_j(heat_df, scale="none", border_color=NA, cluster_rows=FALSE, cluster_cols=FALSE, col=colorRampPalette(c("#FFFFFF", brewer.pal(9,"Blues")))(100)) dev.off()