Mercurial > repos > pjbriggs > ceas
diff test-data/ceas_out1.log @ 0:f411ce97a351 draft
Uploaded initial version 1.0.2-2
author | pjbriggs |
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date | Tue, 30 Jun 2015 07:08:05 -0400 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/ceas_out1.log Tue Jun 30 07:08:05 2015 -0400 @@ -0,0 +1,184 @@ +ceas -- 0.9.9.7 (package version 1.0.2) +INFO @ Tue, 23 Jun 2015 09:12:22: +# ARGUMENTS: +# name = ceas +# gene annotation table = galGal3.refGene +# BED file = ceas_in.bed +# WIG file = None +# extra BED file = None +# ChIP annotation = On +# gene-centered annotation = On +# average profiling = Off +# dump profiles = Off +# re-annotation for genome background (ChIP region annotation) = False +# promoter sizes (ChIP region annotation) = 1000,2000,3000 bp +# downstream sizes (ChIP region annotation) = 1000,2000,3000 bp +# bidrectional promoter sizes (ChIP region annotation) = 2500,5000 bp +# span size (gene-centered annotation) = 3000 bp +INFO @ Tue, 23 Jun 2015 09:12:22: #1 read the gene table... +INFO @ Tue, 23 Jun 2015 09:12:22: #2 read the bed file of ChIP regions... +INFO @ Tue, 23 Jun 2015 09:12:22: #3 perform gene-centered annotation... +INFO @ Tue, 23 Jun 2015 09:12:22: #4 See ceas.xls for gene-centered annotation! +INFO @ Tue, 23 Jun 2015 09:12:22: #5 read the pre-computed genome bg annotation... +INFO @ Tue, 23 Jun 2015 09:12:22: #6 perform ChIP region annotation... +INFO @ Tue, 23 Jun 2015 09:12:22: #7 write a R script of ChIP region annotation... + +R version 3.1.2 (2014-10-31) -- "Pumpkin Helmet" +Copyright (C) 2014 The R Foundation for Statistical Computing +Platform: x86_64-redhat-linux-gnu (64-bit) + +R is free software and comes with ABSOLUTELY NO WARRANTY. +You are welcome to redistribute it under certain conditions. +Type 'license()' or 'licence()' for distribution details. + + Natural language support but running in an English locale + +R is a collaborative project with many contributors. +Type 'contributors()' for more information and +'citation()' on how to cite R or R packages in publications. + +Type 'demo()' for some demos, 'help()' for on-line help, or +'help.start()' for an HTML browser interface to help. +Type 'q()' to quit R. + +> # ARGUMENTS: +> # name = ceas +> # gene annotation table = galGal3.refGene +> # BED file = ceas_in.bed +> # WIG file = None +> # extra BED file = None +> # ChIP annotation = On +> # gene-centered annotation = On +> # average profiling = Off +> # dump profiles = Off +> # re-annotation for genome background (ChIP region annotation) = False +> # promoter sizes (ChIP region annotation) = 1000,2000,3000 bp +> # downstream sizes (ChIP region annotation) = 1000,2000,3000 bp +> # bidrectional promoter sizes (ChIP region annotation) = 2500,5000 bp +> # span size (gene-centered annotation) = 3000 bp +> pdf("ceas.pdf",height=11.5,width=8.5) +> +> # 09:12:22 Tue, 23 Jun 2015 +> # +> # ChIP annotation +> # +> +> +> # +> # Chromosomal Distribution +> # +> +> par(mar=c(4, 4, 5, 3.8),oma=c(4, 2, 4, 2)) +> r0<-c(100.0) +> r1<-c(100.0) +> height<-rbind(r0,r1) +> names=c("26") +> mp<-barplot(height=height,names=names,beside=TRUE,horiz=TRUE,col=c("#5FA1C1","#EB9D86"),main="Chromosomal Distribution of ChIP Regions",xlab="Percentage %",ylab="Chromosome",border=FALSE,xlim=c(0.000000,183.333333),cex.names=1) +> text(x=c(100.0),y=mp[1,],label=c("100.0 %"),pos=4,offset=0.2,cex=0.9) +> text(x=c(100.0),y=mp[2,],label=c("100.0 % (<=4.9e-324)"),pos=4,offset=0.2,cex=0.9) +> legend("right",legend=c("Genome","ChIP (p-value)"),col=c("#5FA1C1","#EB9D86"),pch=15,bty="n") +> +> # +> # Promoter,Bipromoter,Downstream, Gene and Regions of interest +> # +> +> par(mfrow=c(4, 1),mar=c(4, 4, 5, 3.8),oma=c(4, 2, 4, 2)) +> r0<-c(1.8532425688606797, 3.616851183410451, 5.322318854623416) +> r1<-c(0.0, 0.0, 0.0) +> height<-rbind(r0,r1) +> names=c("<=1000 bp","<=2000 bp","<=3000 bp") +> mp<-barplot(height=height,names=names,beside=TRUE,horiz=FALSE,col=c("#5FA1C1","#EB9D86"),main="Promoter",ylab="Percentage %",border=FALSE,ylim=c(0.000000,9.757585),cex.names=1) +> text(x=mp[1,],y=c(1.8532425688606797, 3.616851183410451, 5.322318854623416),label=c("1.9 %","3.6 %","5.3 %"),pos=3,offset=0.2) +> text(x=mp[2,],y=c(0.0, 0.0, 0.0),label=c("0.000 % ++ (0.981)","0.000 % ++ (0.964)","0.000 % ++ (0.947)"),pos=3,offset=0.2) +> legend("topleft",legend=c("Genome","ChIP (p-value)"),col=c("#5FA1C1","#EB9D86"),pch=15,bty="n") +> r0<-c(0.03876062889120376, 0.03876062889120376) +> r1<-c(0.0, 0.0) +> height<-rbind(r0,r1) +> names=c("<=2500 bp","<=5000 bp") +> mp<-barplot(height=height,names=names,beside=TRUE,horiz=FALSE,col=c("#5FA1C1","#EB9D86"),main="Bidirectional Promoter",ylab="Percentage %",border=FALSE,ylim=c(0.000000,0.071061),cex.names=1) +> text(x=mp[1,],y=c(0.03876062889120376, 0.03876062889120376),label=c("0.04 %","0.04 %"),pos=3,offset=0.2) +> text(x=mp[2,],y=c(0.0, 0.0),label=c("0.000 % ++ (1.000)","0.000 % ++ (1.000)"),pos=3,offset=0.2) +> legend("topleft",legend=c("Genome","ChIP (p-value)"),col=c("#5FA1C1","#EB9D86"),pch=15,bty="n") +> r0<-c(1.8290171758036773, 3.4690762857627364, 4.980740812519683) +> r1<-c(0.0, 0.0, 0.0) +> height<-rbind(r0,r1) +> names=c("<=1000 bp","<=2000 bp","<=3000 bp") +> mp<-barplot(height=height,names=names,beside=TRUE,horiz=FALSE,col=c("#5FA1C1","#EB9D86"),main="Downstream",ylab="Percentage %",border=FALSE,ylim=c(0.000000,9.131358),cex.names=1) +> text(x=mp[1,],y=c(1.8290171758036773, 3.4690762857627364, 4.980740812519683),label=c("1.8 %","3.5 %","5.0 %"),pos=3,offset=0.2) +> text(x=mp[2,],y=c(0.0, 0.0, 0.0),label=c("0.000 % ++ (0.982)","0.000 % ++ (0.965)","0.000 % ++ (0.950)"),pos=3,offset=0.2) +> legend("topleft",legend=c("Genome","ChIP (p-value)"),col=c("#5FA1C1","#EB9D86"),pch=15,bty="n") +> r0<-c(0.2034933016788197, 1.3978051793890356, 2.359553283752029, 19.734005184234114, 23.694856949054) +> r1<-c(0.0, 0.0, 0.0, 0.0, 0.0) +> height<-rbind(r0,r1) +> names=c("5'UTR","3'UTR","Coding Exon","Intron","All") +> mp<-barplot(height=height,names=names,beside=TRUE,horiz=FALSE,col=c("#5FA1C1","#EB9D86"),main="Gene",ylab="Percentage %",border=FALSE,ylim=c(0.000000,43.440571),cex.names=1) +> text(x=mp[1,],y=c(0.2034933016788197, 1.3978051793890356, 2.359553283752029, 19.734005184234114, 23.694856949054),label=c("0.2 %","1.4 %","2.4 %","19.7 %","23.7 %"),pos=3,offset=0.2) +> text(x=mp[2,],y=c(0.0, 0.0, 0.0, 0.0, 0.0),label=c("0.000 % ++ (0.998)","0.000 % ++ (0.986)","0.000 % ++ (0.976)","0.000 % ++ (0.803)","0.000 % ++ (0.763)"),pos=3,offset=0.2) +> legend("topleft",legend=c("Genome","ChIP (p-value)"),col=c("#5FA1C1","#EB9D86"),pch=15,bty="n") +> +> # +> # Distribution of Genome and ChIP regions over cis-regulatory element +> # Note that the x may be modified for better graphics in case a value is too small +> # Thus, look at the labels of the pie chart to get the real percentage values +> # +> +> par(mfcol=c(2, 2),mar=c(3, 3, 4, 2.8),oma=c(4, 2, 4, 2)) +> x<-c(0.018532,0.017055,0.016037,0.017830,0.015092,0.014051,0.010000,0.013833,0.023014,0.192592,0.670292) +> pie(x=x,labels=c("1.9 %","1.7 %","1.6 %","1.8 %","1.5 %","1.4 %","0.2 %","1.4 %","2.3 %","19.3 %","67.0 %"),main="Genome",col=c("#445FA2","#EB9D86","#799F7A","#6C527F","#5FA1C1","#E8BB77","#A8C5EF","#FDCDB9","#C6E6B5","#F1D5EE","#B4E1F6"),clockwise=TRUE,border=FALSE,radius=0.9,cex=0.8,init.angle=90,density=100) +> x<-c(0.000000,1.000000) +> y<-c(0.000000,1.000000) +> plot(x, y,type="n",main="",xlab="",ylab="",frame=FALSE,axes=FALSE,xaxt="s",yaxt="s") +> legend("top",legend=c("Promoter (<=1000 bp): 1.9 %","Promoter (1000-2000 bp): 1.7 %","Promoter (2000-3000 bp): 1.6 %","Downstream (<=1000 bp): 1.8 %","Downstream (1000-2000 bp): 1.5 %","Downstream (2000-3000 bp): 1.4 %","5'UTR: 0.2 %","3'UTR: 1.4 %","Coding exon: 2.3 %","Intron: 19.3 %","Distal intergenic: 67.0 %"),col=c("#445FA2","#EB9D86","#799F7A","#6C527F","#5FA1C1","#E8BB77","#A8C5EF","#FDCDB9","#C6E6B5","#F1D5EE","#B4E1F6"),pch=15,bty="n") +> x<-c(0.010000,0.010000,0.010000,0.010000,0.010000,0.010000,0.010000,0.010000,0.010000,0.010000,1.000000) +> pie(x=x,labels=c("0.000 %","0.000 %","0.000 %","0.000 %","0.000 %","0.000 %","0.000 %","0.000 %","0.000 %","0.000 %","100.0 %"),main="ChIP",col=c("#445FA2","#EB9D86","#799F7A","#6C527F","#5FA1C1","#E8BB77","#A8C5EF","#FDCDB9","#C6E6B5","#F1D5EE","#B4E1F6"),clockwise=TRUE,border=FALSE,radius=0.9,cex=0.8,init.angle=90,density=100) +> x<-c(0.000000,1.000000) +> y<-c(0.000000,1.000000) +> plot(x, y,type="n",main="",xlab="",ylab="",frame=FALSE,axes=FALSE,xaxt="s",yaxt="s") +> legend("top",legend=c("Promoter (<=1000 bp): 0.000 %","Promoter (1000-2000 bp): 0.000 %","Promoter (2000-3000 bp): 0.000 %","Downstream (<=1000 bp): 0.000 %","Downstream (1000-2000 bp): 0.000 %","Downstream (2000-3000 bp): 0.000 %","5'UTR: 0.000 %","3'UTR: 0.000 %","Coding exon: 0.000 %","Intron: 0.000 %","Distal intergenic: 100.0 %"),col=c("#445FA2","#EB9D86","#799F7A","#6C527F","#5FA1C1","#E8BB77","#A8C5EF","#FDCDB9","#C6E6B5","#F1D5EE","#B4E1F6"),pch=15,bty="n") +> +> # +> # ChIP regions over the genome +> # +> +> par(mar=c(4, 4, 5, 3.8),oma=c(4, 2, 4, 2)) +> layout(matrix(c(1, 0, 2, 2), 2, 2, byrow = TRUE),widths=c(1, 1),heights=c(1, 5)) +> x<-c(0.000000,2.515610) +> y<-c(0.000000,1.000000) +> plot(x, y,type="n",main="Distribution of Peak Heights",xlab="",ylab="",xlim=c(0.000000,2.515610),ylim=c(0.000000,1.000000),frame=FALSE,xaxt="s",yaxt="n",cex=0.9) +> x<-c(0.000000,2.515610,2.515610,0.000000) +> y<-c(0.000000,0.000000,1.000000,1.000000) +> polygon(x,y,col=c("black")) +> x <- c(0.000000,0.169726,0.339451,0.509177,0.678903,0.848628,1.018354,1.188079,1.357805,1.527531,1.697256,1.866982,2.036708,2.206433,2.376159) +> y<-c(0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.800000) +> lines(x, y,xlim=c(0, 2.51561),ylim=c(0, 1),type="l",col=c("cyan"),lwd=2) +> x<-c(4119129.000000,4119130.000000) +> y<-c(0.855556,1.144444) +> plot(x, y,type="n",main="ChIP Regions (Peaks) over Chromosomes",xlab="Chromosome Size (bp)",ylab="Chromosome",xlim=c(4119129.000000,4119130.000000),ylim=c(0.855556,1.144444),frame=FALSE,xaxt="s",yaxt="n") +> start <- c(4119129) +> end <- c(4119130) +> vals <- c(2.51561) +> vals[vals > 2.51561] <- 2.51561 +> vals[vals < 0] <- 0 +> heights <- 0.288889 * ((vals - 0)/(2.51561 - 0)) + 0.855555555556 +> for (i in 1:length(heights)) { ++ polygon(x=c(start[i], end[i], end[i], start[i]), y=c(0.855555555556, 0.855555555556, heights[i], heights[i]), col=c("#CC0000"), border=c("#CC0000")) ++ } +> mtext("26",side=2,line=0,outer=FALSE,at=1.0) +> dev.off() +null device + 1 +> +INFO @ Tue, 23 Jun 2015 09:12:22: #... cong! See ceas.pdf for the graphical results of CEAS!