Mercurial > repos > jeremyjliu > region_motif_enrichment
changeset 16:9a84f76db861 draft
Fixed RMOTIF_PATH env variable for toolshed deployment
| author | jeremyjliu |
|---|---|
| date | Wed, 12 Nov 2014 15:19:37 -0500 |
| parents | 81bd3a218c51 |
| children | 7afdfd4f4c1b |
| files | region_motif_compare.r region_motif_compare.xml region_motif_db/pwms/jaspar.jolma.pwms.from.seq.RData region_motif_db/pwms/mm9.pwms.from.seq.RData region_motif_db/pwms/pouya.pwms.from.seq.RData region_motif_intersect.r region_motif_intersect.xml region_motif_lib/plotting.r tool_dependencies.xml upload/region_motif_compare.r upload/region_motif_compare.xml upload/region_motif_intersect.r upload/region_motif_intersect.xml upload/tool_dependencies.xml |
| diffstat | 14 files changed, 355 insertions(+), 1168 deletions(-) [+] |
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--- a/region_motif_compare.r Wed Nov 12 15:10:51 2014 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,189 +0,0 @@ -# Name: region_motif_compare.r -# Description: Reads in two count files and determines enriched and depleted -# motifs (or any location based feature) based on poisson tests and gc -# corrections. All enrichment ratios relative to overall count / gc ratios. -# Author: Jeremy liu -# Email: jeremy.liu@yale.edu -# Date: 14/07/03 -# Note: This script is meant to be invoked with the following command -# R --slave --vanilla -f ./region_motif_compare.r --args <workingdir> <db> <intab1> <intab2> -# <enriched_tab> <depleted_tab> <plots_png> -# <workingdir> is working directory of galaxy installation -# <db> types: "t" test, "p" pouya, "j" jaspar jolma, "m" mouse, "c" combined -# Dependencies: plotting.r - -# Auxiliary function to concatenate multiple strings -concat <- function(...) { - input_list <- list(...) - return(paste(input_list, sep="", collapse="")) -} - -# Supress all warning messages to prevent Galaxy treating warnings as errors -options(warn=-1) - -# Set common and data directories -args <- commandArgs() -workingDir = args[7] -commonDir = concat(workingDir, "/tools/my_tools") -dbCode = args[8] -# dbCode "c" implemented when pwmFile is loaded -if (dbCode == "t" | dbCode == "p") { - pwmFile = concat(commonDir, "/region_motif_db/pwms/pouya.pwms.from.seq.RData") -} else if (dbCode == "j") { - pwmFile = concat(commonDir, "/region_motif_db/pwms/jaspar.jolma.pwms.from.seq.RData") -} else if (dbCode == "m") { - pwmFile = concat(commonDir, "/region_motif_db/pwms/mm9.pwms.from.seq.RData") -} else if (dbCode == "c") { # rest of dbCode "c" implemeted when pwmFile loaded - pwmFile = concat(commonDir, "/region_motif_db/pwms/pouya.pwms.from.seq.RData") - pwmFile2 = concat(commonDir, "/region_motif_db/pwms/jaspar.jolma.pwms.from.seq.RData") -} else { - pwmFile = concat(commonDir, "/region_motif_db/pwms/pouya.pwms.from.seq.RData") -} - -# Set input and reference files -inTab1 = args[9] -inTab2 = args[10] -enrichTab = args[11] -depleteTab = args[12] -plotsPng = args[13] - -# Load dependencies -source(concat(commonDir, "/region_motif_lib/plotting.r")) - -# Auxiliary function to read in tab file and prepare the data -read_tsv <- function(file) { - data = read.table(file, sep="\t", stringsAsFactors=FALSE) - names(data)[names(data) == "V1"] = "motif" - names(data)[names(data) == "V2"] = "counts" - return(data) -} - -startTime = Sys.time() -cat("Running ... Started at:", format(startTime, "%a %b %d %X %Y"), "...\n") - -# Loading motif position weight matrix (pwm) file and input tab file -#cat("Loading and reading input region motif count files...\n") -load(pwmFile) # pwms data structure -if (dbCode == "c") { # Remaining implementation of dbCode "c" combined - temp = pwms - load(pwmFile2) - pwms = append(temp, pwms) -} -region1DF = read_tsv(inTab1) -region2DF = read_tsv(inTab2) -region1Counts = region1DF$counts -region2Counts = region2DF$counts -names(region1Counts) = region1DF$motif -names(region2Counts) = region2DF$motif - -# Processing count vectors to account for missing 0 count motifs, then sorting -#cat("Performing 0 count correction and sorting...\n") -allNames = union(names(region1Counts), names(region2Counts)) -region1Diff = setdiff(allNames, names(region1Counts)) -region2Diff = setdiff(allNames, names(region2Counts)) -addCounts1 = rep(0, length(region1Diff)) -addCounts2 = rep(0, length(region2Diff)) -names(addCounts1) = region1Diff -names(addCounts2) = region2Diff -newCounts1 = append(region1Counts, addCounts1) -newCounts2 = append(region2Counts, addCounts2) -region1Counts = newCounts1[sort.int(names(newCounts1), index.return=TRUE)$ix] -region2Counts = newCounts2[sort.int(names(newCounts2), index.return=TRUE)$ix] - -# Generate gc content matrix -gc = sapply(pwms, function(i) mean(i[2:3,3:18])) - -# Apply poisson test, calculate p and q values, and filter significant results -#cat("Applying poisson test...\n") -rValue = sum(region2Counts) / sum(region1Counts) -pValue = sapply(seq(along=region1Counts), function(i) { - poisson.test(c(region1Counts[i], region2Counts[i]), r=1/rValue)$p.value -}) -qValue = p.adjust(pValue, "fdr") -indices = which(qValue<0.1 & abs(log2(region1Counts/region2Counts/rValue))>log2(1.5)) - -# Setting up output diagnostic plots, 4 in 1 png image -png(plotsPng, width=800, height=800) -xlab = "region1_count" -ylab = "region2_count" -lim = c(0.5, 5000) -layout(matrix(1:4, ncol=2)) -par(mar=c(5, 5, 5, 1)) - -# Plot all motif counts along the linear correlation coefficient -plot.scatter(region1Counts+0.5, region2Counts+0.5, log="xy", xlab=xlab, ylab=ylab, - cex.lab=2.2, cex.axis=1.8, xlim=lim, ylim=lim*rValue) -abline(0, rValue, untf=T) -abline(0, rValue*2, untf=T, lty=2) -abline(0, rValue/2, untf=T, lty=2) - -# Plot enriched and depleted motifs in red, housed in second plot -plot.scatter(region1Counts+0.5, region2Counts+0.5, log="xy", xlab=xlab, ylab=ylab, - cex.lab=2.2, cex.axis=1.8, xlim=lim, ylim=lim*rValue) -points(region1Counts[indices]+0.5, region2Counts[indices]+0.5, col="red") -abline(0, rValue, untf=T) -abline(0, rValue*2, untf=T, lty=2) -abline(0, rValue/2, untf=T, lty=2) - -# Apply and plot gc correction and loess curve -#cat("Applying gc correction, rerunning poisson test...\n") -ind = which(region1Counts>5) -gc = gc[names(region2Counts)] # Reorder the indices of pwms to match input data -lo = plot.scatter(gc,log2(region2Counts/region1Counts),draw.loess=T, - xlab="gc content of motif",ylab=paste("log2(",ylab,"/",xlab,")"), - cex.lab=2.2,cex.axis=1.8,ind=ind) # This function is in plotting.r -gcCorrection = 2^approx(lo$loess,xout=gc,rule=2)$y -save(gc, file="gc.RData") - -# Recalculate p and q values, and filter for significant entries -pValueGC = sapply(seq(along=region1Counts),function(i) { - poisson.test(c(region1Counts[i],region2Counts[i]),r=1/gcCorrection[i])$p.value -}) -qValueGC=p.adjust(pValueGC,"fdr") -indicesGC = which(qValueGC<0.1 & abs(log2(region1Counts/region2Counts*gcCorrection))>log2(1.5)) - -# Plot gc corrected motif counts -plot.scatter(region1Counts+0.5, (region2Counts+0.5)/gcCorrection, log="xy", - xlab=xlab, ylab=paste(ylab,"(normalized)"), cex.lab=2.2, cex.axis=1.8, - xlim=lim, ylim=lim) -points(region1Counts[indicesGC]+0.5, - (region2Counts[indicesGC]+0.5)/gcCorrection[indicesGC], col="red") -abline(0,1) -abline(0,1*2,untf=T,lty=2) -abline(0,1/2,untf=T,lty=2) - -# Trim results, compile statistics and output to file -# Only does so if significant results are computed -if(length(indicesGC) > 0) { - # Calculate expected counts and enrichment ratios - #cat("Calculating statistics...\n") - nullExpect = region1Counts * gcCorrection - enrichment = region2Counts / nullExpect - - # Reorder selected indices in ascending pvalue - #cat("Reordering by ascending pvalue...\n") - indicesReorder = indicesGC[order(pValueGC[indicesGC])] - - # Combine data into one data frame and output to two files - #cat("Splitting and outputting data...\n") - outDF = data.frame(motif=names(pValueGC), p=as.numeric(pValueGC), q=qValueGC, - stringsAsFactors=F, region_1_count=region1Counts, - null_expectation=round(nullExpect,2), region_2_count=region2Counts, - enrichment=enrichment)[indicesReorder,] - names(outDF)[which(names(outDF)=="region_1_count")]=xlab - names(outDF)[which(names(outDF)=="region_2_count")]=ylab - indicesEnrich = which(outDF$enrichment>1) - indicesDeplete = which(outDF$enrichment<1) - outDF$enrichment = ifelse(outDF$enrichment>1, - round(outDF$enrichment,3), - paste("1/",round(1/outDF$enrichment,3))) - write.table(outDF[indicesEnrich,], file=enrichTab, quote=FALSE, - sep="\t", append=FALSE, row.names=FALSE, col.names=TRUE) - write.table(outDF[indicesDeplete,], file=depleteTab, quote=FALSE, - sep="\t", append=FALSE, row.names=FALSE, col.names=TRUE) -} - -# Catch display messages and output timing information -catchMessage = dev.off() -cat("Done. Job started at:", format(startTime, "%a %b %d %X %Y."), - "Job ended at:", format(Sys.time(), "%a %b %d %X %Y."), "\n")
--- a/region_motif_compare.xml Wed Nov 12 15:10:51 2014 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,29 +0,0 @@ -<tool id="region_motif_compare" name="Region Motif Count Compare"> - <description>for comparing the motif counts in different region sets</description> - <command interpreter="bash"> - /usr/bin/R --slave --vanilla -f $GALAXY_ROOT_DIR/tools/my_tools/region_motif_compare.r --args $GALAXY_ROOT_DIR $db_type $in_tab_1 $in_tab_2 $out_enriched $out_depleted $out_plots - </command> - <inputs> - <param name="in_tab_1" type="data" format="tabular" label="Region Set 1 Motif Count File"/> - <param name="in_tab_2" type="data" format="tabular" label="Region Set 2 Motif Count File"/> - <param name="db_type" type="select" label="Select Motif Database" > - <option value="t">Test Pouya Subset (hg19)</option> - <option value="p">Pouya Encode Motifs (hg19)</option> - <option value="j">Jaspar and Jolma Motifs (hg19)</option> - <option value="m">Mouse Motifs (mm9)</option> - <option value="c">Pouya, Jaspar, and Jolma Combined (hg19)</option> - </param> - </inputs> - <outputs> - <data name="out_enriched" format="tabular" label="Enriched Motifs"/> - <data name="out_depleted" format="tabular" label="Depleted Motifs"/> - <data name="out_plots" format="png" label="Motif Count Comparison Plots"/> - </outputs> - - <help> - This tools reads in two counts file and determines enriched and depleted - motifs in two different region sets based on poisson calculation with - gc correction. - </help> - -</tool> \ No newline at end of file
--- a/region_motif_intersect.r Wed Nov 12 15:10:51 2014 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,102 +0,0 @@ -# Name: region_motif_intersect.r -# Description: Takes a bed file of target regions and counts intersections -# of each motif (built in rdata database) and target regions. -# Author: Jeremy liu -# Email: jeremy.liu@yale.edu -# Date: 14/07/02 -# Note: This script is meant to be invoked with the following command -# R --slave --vanilla -f ./region_motif_intersect.r --args <workingdir> <db> <inbed> <outtab> -# <workingdir> is working directory of galaxy installation -# <db> types: "t" test, "p" pouya, "j" jaspar jolma, "m" mouse -# Dependencies: none - -# Auxiliary function to concatenate multiple strings -concat <- function(...) { - input_list <- list(...) - return(paste(input_list, sep="", collapse="")) -} - -# Set common and data directories -args <- commandArgs() -workingDir = args[7] -dbDir = concat(workingDir, "/region_motif_db") -dbCode = args[8] -if (dbCode == "t") { - motifDB = concat(dbDir, "/pouya_test_motifs.bed.bgz") -} else if (dbCode == "p") { - motifDB = concat(dbDir, "/pouya_motifs.bed.bgz") -} else if (dbCode == "j") { - motifDB = concat(dbDir, "/jaspar_jolma_motifs.bed.bgz") -} else if (dbCode == "m") { - motifDB = concat(dbDir, "/mm9_motifs.bed.bgz") -} else { - motifDB = concat(dbDir, "/pouya_motifs.bed.bgz") -} - -# Set input and reference files, comment to toggle commmand line arguments -inBed = args[9] -outTab = args[10] - -# Auxiliary function to read in BED file -read_bed <- function(file) { - return(read.table(file, sep="\t", stringsAsFactors=FALSE)) -} - -startTime = Sys.time() -cat("Running ... Started at:", format(startTime, "%a %b %d %X %Y"), "...\n") - -# Load dependencies -cat("Loading dependencies...\n") -suppressPackageStartupMessages(library(Rsamtools, quietly=TRUE)) - -# Initializing hash table (as env) with motif names and loading tabix file -cat("Loading motif database and initializing hash table...\n") -motifTable = new.env() -motifTbx <- TabixFile(motifDB) - -# Loading input bed file, convert integer columns to numeric, name columns -cat("Loading region file...\n") -regionsDF = read_bed(inBed) -dfTemp = sapply(regionsDF, is.integer) -regionsDF[dfTemp] = lapply(regionsDF[dfTemp], as.numeric) -names(regionsDF)[names(regionsDF) == "V1"] = "chr" -names(regionsDF)[names(regionsDF) == "V2"] = "start" -names(regionsDF)[names(regionsDF) == "V3"] = "end" - -# Filtering regions to exclude chromosomes not in motif database -cat("Determining intersection counts...\n") -motifTbxChrs = seqnamesTabix(motifTbx) -regionsDFFilter = subset(regionsDF, chr %in% motifTbxChrs) - -# Loading regions into GRanges object and scanning motif tabix database -# Region end is incremented by 1 since scanTabix querying is inclusive for -# position start but exclusive for position end. -param = GRanges(regionsDFFilter$chr, IRanges(regionsDFFilter$start, - end=regionsDFFilter$end + 1)) -regionsIntersects = scanTabix(motifTbx, param=param) - -# Parsing result list and updating motif count hash table -cat("Parsing result list...\n") -for(regionIntersects in regionsIntersects) { - for(regionIntersect in strsplit(regionIntersects, " ")) { - intersectMotif = strsplit(regionIntersect, "\t")[[1]][4] - if(is.null(motifTable[[intersectMotif]])) { - motifTable[[intersectMotif]] = 1 - } else { - motifTable[[intersectMotif]] = motifTable[[intersectMotif]] + 1 - } - } -} - -# Converting motif count hash table to an integer vector for output -counts = integer(length = length(ls(motifTable))) -names(counts) = ls(motifTable) -for(motifName in ls(motifTable)) { - counts[motifName] = as.integer(motifTable[[motifName]]) -} - -# Outputting intersection counts to tab delineated file -cat("Outputting to file...\n") -write.table(counts, outTab, quote=FALSE, sep="\t", row.names=TRUE, col.names=FALSE) -cat("Done. Job started at:", format(startTime, "%a %b %d %X %Y."), - "Job ended at:", format(Sys.time(), "%a %b %d %X %Y."), "\n")
--- a/region_motif_intersect.xml Wed Nov 12 15:10:51 2014 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,27 +0,0 @@ -<tool id="region_motif_intersect" name="Region Motif Intersect"> - <description>for computing the motifs that lie inside a region set</description> - <requirements> - <requirement type="set_environment">R_SCRIPT_PATH</requirement> - </requirements> - <command interpreter="Rscript"> - region_motif_intersect.r --args \$R_SCRIPT_PATH $db_type $in_bed $out_tab - </command> - <inputs> - <param name="in_bed" type="data" format="bed" label="Input BED File" /> - <param name="db_type" type="select" label="Select Motif Database" > - <option value="t">Test Pouya Subset (hg19)</option> - <option value="p">Pouya Encode Motifs (hg19)</option> - <option value="j">Jaspar and Jolma Motifs (hg19)</option> - <option value="m">Mouse Motifs (mm9)</option> - </param> - </inputs> - <outputs> - <data name="out_tab" format="tabular" /> - </outputs> - - <help> - This tool computes the motifs and the number of motifs that intersect - any region in a input set of regions. - </help> - -</tool> \ No newline at end of file
--- a/region_motif_lib/plotting.r Wed Nov 12 15:10:51 2014 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,815 +0,0 @@ -library(graphics, quietly=TRUE) - -plot.verbose=F -name.cleaner<-function(...,sep="",replace="_") { - plot.name=gsub(" ",replace,paste(...,sep=sep)) - plot.name=gsub("/",replace,plot.name) - plot.name=gsub(",",replace,plot.name) - plot.name=gsub("'",replace,plot.name) - plot.name=gsub("\\+","plus",plot.name) - plot.name=gsub("\\(","",plot.name) - plot.name=gsub("\\)","",plot.name) - return(plot.name) -} -plot.namer <- function(..., date=0, fig.dir=0, format="png",sep="") { - plot.name=name.cleaner(...,sep=sep) - if(date==0) date=gsub("-","",as.character(Sys.Date())) - if(fig.dir==0) fig.dir="/Users/alver/allplots" - plot.name=paste(fig.dir,"/",date,plot.name,".",format,sep="") - if(plot.verbose) cat(" saving figure: ",plot.name,"\n") - return(plot.name) -} - -plot.scatter <- function(x,y=NULL,f=0.1,same=FALSE,n.points=-1,draw.lowess=FALSE,write.r=TRUE,cex.r=1,col=NULL,col.line=NULL,lwd.line=1, - draw.loess=FALSE,span=0.5,bandwidth=bandwidth,draw.prof=FALSE,xlog=FALSE,ylog=FALSE,cor.method="pearson",log="",ind=NULL, - draw.spread=FALSE,...) { - - ## if col is the same length as x, use col for each point matching x. - ## if col is the same length as ind, use col for each point matching x[ind]. - ## else use densCols function based on col. - ## if col is null, densCols is used with bluetone for first plot and redtone for same=T. - - #print(length(x)) - #print(length(y)) - - xy <- xy.coords(x, y) - x=xy$x - y=xy$y - - output=list() - col.use = col - - if(!is.null(ind)) { - if(length(col.use)==length(x)) { - col.use=col.use[ind] - } - x=x[ind] - y=y[ind] - } - - if(length(col.use)!=length(x)) { - col.use=rep(NA,length(x)) - } - - - take=which(is.finite(x) & is.finite(y)) - x=x[take] - y=y[take] - col.use=col.use[take] - - if(grepl("x",log)) xlog=TRUE - if(grepl("y",log)) ylog=TRUE - if(xlog) log="x" - if(ylog) log=paste(log,"y",sep="") - - if(draw.lowess) { - lo = lowess(x,y,f) - output$lowess=lo - } - if(draw.loess | draw.spread) { - px=x;py=y - if(xlog) px=log(x) - if(ylog) py=log(y) - ind = which(is.finite(px+py)) - px=px[ind] - py=py[ind] - lo = loess(py ~ px,span=span,iterations=5) - lo.y=as.numeric(lo$fitted) - lo.x=as.numeric(lo$x) - if(draw.spread) lo.sd = loess((lo.y-py)^2 ~ lo.x,span=span*1.5,iterations=5) - if(xlog) lo.x=exp(lo.x) - if(ylog) lo.y=exp(lo.y) - lo =data.frame(x=lo.x,y=lo.y) - if(draw.spread) { - lo.sd=lo.sd$fitted - if(ylog) lo.sd=lo.sd*lo.y*lo.y - lo$sd=sqrt(pmax(0,lo.sd)) - } - lo=unique(lo) - lo = lo[order(lo$x),] - output$loess=lo - } - - if(draw.prof) { - px=x;py=y - if(xlog) px=log(x) - p=prof(px,py,50) - if(xlog) p$x=exp(p$x) - output$prof=p - } - - r=cor(x,y,method=cor.method) - output$cor=r - output$cor.method=cor.method - - len=length(x) - if(n.points>0 & n.points<len) { - take=sample(1:len,n.points) - x=x[take] - y=y[take] - col.use=col.use[take] - } - - if(xlog) { - ind = which(x>0) - x=x[ind] - y=y[ind] - col.use=col.use[ind] - } - xcol=x - if(xlog) xcol=log(xcol) - if(ylog) { - ind = which(y>0) - x=x[ind] - xcol=xcol[ind] - y=y[ind] - col.use=col.use[ind] - } - ycol=y - if(ylog) ycol=log(ycol) - - if(is.null(col)) { - if(!same) { - col=colorRampPalette(blues9[-(1:3)]) - } else { - col=colorRampPalette(c("lightpink","red","darkred")) - } - } - if(!is.na(col.use[1])) { - col=col.use - } else { - col= suppressPackageStartupMessages(densCols(xcol,ycol,col =col,bandwidth=bandwidth,nbin=500)) - } - if(!same) { - plot(x,y,col=col,log=log,...) - } else { - points(x,y,col=col,...) - } - - if(is.null(col.line)) { - col.line="darkblue" - if(same) col.line="darkred" - } - if(draw.lowess | draw.loess) lines(lo,col=col.line,lwd=lwd.line) - if(draw.spread) { - lines(lo$x,lo$y+lo$sd,col=col.line,lwd=lwd.line) - lines(lo$x,lo$y-lo$sd,col=col.line,lwd=lwd.line) - } - if(draw.prof) { - points(p) - plot.prof(p) - } - if(write.r & !same) mtext(paste("r=",round(r,3),sep=""),cex=cex.r) - return(invisible(output)) -} - -#color.int=c(144,586,465,257,490,100,74,24) -#coli=1 -#cols = integer() -colramp.bwr = vector() -colramp.byr = vector() -colramp.bw = vector() -colramp.bw2 = vector() - -plot.save=F - -setup.plotting <- function() { - pdf.options(useDingbats = FALSE) -# cols<<-colors()[color.int] -# cols<<-rep(cols,100) - colramp.bwr <<- colorRampPalette(c("blue","white","red"),space="Lab")(100); - colramp.byr <<- colorRampPalette(c("blue","yellow","red"),space="Lab")(100); - colramp.bw <<- colorRampPalette(c("white","black"),space="Lab")(100) - colramp.bw2 <<- colorRampPalette(c("grey92","grey5"),space="Lab")(100) -} - - -plot.cluster <- function(x,k, max.points.cl=-1, image.sep=-1,col=NULL, reorder=FALSE) { - x[which(is.na(x))]=0 - if(reorder) { - o=hclust(dist(t(x)))$order - x=x[,o] - } - if(image.sep<0) { - if(max.points.cl>0) { - image.sep=ceiling(0.2*max.points.cl) - } else { - image.sep=ceiling(0.2 * nrow(x) / nrow(k$centers)) - } - } - - distances<-dist(k$centers) - hcl=hclust(distances) - - adjust.branch.sep <-function(ddr,lengths) { - assign.branch.sep <- function(d,i.leaf) { - if(is.leaf(d)) { - attr(d,"members")<-lengths[i.leaf] - i.leaf=i.leaf+1 - output=list(d=d,i.leaf=i.leaf) - return(output) - } - else{ - input=assign.branch.sep(d[[1]],i.leaf) - i.leaf=input$i.leaf - d[[1]]=input$d - - input=assign.branch.sep(d[[2]],i.leaf) - i.leaf=input$i.leaf - d[[2]]=input$d - - attr(d,"members")<-attr(d[[1]],"members")+attr(d[[2]],"members") - output=list(d=d,i.leaf=i.leaf) - return(output) - } - } - ddr<-as.dendrogram(ddr) - ddr=assign.branch.sep(ddr,1)$d - return(ddr) - } - - n.points.actual=k$size - if(max.points.cl>0) { - k$size[which(k$size>max.points.cl)] = max.points.cl -} - - ddr<-adjust.branch.sep(hcl,k$size[hcl$order]+image.sep) - centers=length(hcl$order) - - n.points=sum(k$size) - n.dims=ncol(x) - z=matrix(numeric((n.points+(centers-1)*image.sep)*n.dims),ncol=n.dims) - - - last.row=0 - cluster.y.pos=numeric(centers) - for(i.c in hcl$order) { - n.p=k$size[i.c] - z[last.row+1:n.p,] = x[which(k$cluster==i.c)[1:n.p],] - cluster.y.pos[i.c]=last.row+n.p/2 - last.row=last.row+n.p+image.sep - } - - zlim=c(0,max(z)) - if(min(z)<0) { - m=max(c(z,-z)) - zlim=c(-m,m) - } - if(is.null(col)) { - if(min(z)>=0) { - col= colramp.bw - } else { - col= colorRampPalette(c("blue","yellow","red"),space="Lab")(100); - } - } - x.pl=seq1(n.dims+1)-0.5 - y.pl=seq1(nrow(z)+1)-0.5 - l <- layout(matrix(1:2,ncol=2),widths=c(1,5)) - par(mar = c(6,0.5,6,0)) - my.plot.dendrogram(ddr,horiz=T,axes=F,yaxs="i",xaxs="i",leaflab="none",center=T,lwd=10) - par(mar = c(6,0.1,6,2.1)) - image(x=x.pl,y=y.pl,z=t(z),zlim=zlim,axes=FALSE,xlab="",col=col) - mtext("cluster",side=4,adj=1.1) - mtext("points",side=4,adj=1.1,line=1) - mtext(seq1(centers),side=4,at=cluster.y.pos) - mtext(n.points.actual,side=4,at=cluster.y.pos,line=1) - - if(!is.null(dimnames(x)[[2]])) { - mtext(dimnames(x)[[2]],side=1,at=seq1(n.dims),las=2) - } -} - -plot.cluster2 <- function(k, n.clusters=-1, n.clusters.per.panel=4, cols=c("black","red","blue","darkgreen","orange"),f=0,xshift=0,...) { - if(n.clusters<=0) n.clusters=nrow(k$centers) - - n.elements=as.numeric(unlist(lapply(seq1(n.clusters), function(cl) length(which(abs(k$cluster)==cl))))) - - distances<-dist(k$centers) - n.panels = ceiling(n.clusters/n.clusters.per.panel) - n.rows=ceiling(sqrt(n.panels)) - n.cols=ceiling(n.panels/n.rows) - n.panels.layout=n.rows*n.cols - - layout(matrix(seq1(n.panels.layout),nrow=n.rows,byrow=TRUE)) - - min=min(k$centers) - max=max(k$centers) - - if(f>0) { - for(i.cluster in seq1(n.clusters)) { - k$centers[i.cluster,]=lowess(k$centers[i.cluster,],f=f)$y - } - } - - ## hcl=hclust(distances) - hcl=list() - hcl$order=1:n.clusters - - for(i.cluster in seq1(n.clusters)) { - if(i.cluster %% n.clusters.per.panel == 1 ) { - clusters.of.panel=i.cluster:(i.cluster+n.clusters.per.panel-1) - clusters.of.panel=clusters.of.panel[which(clusters.of.panel<=n.clusters)] - clusters.of.panel=hcl$order[clusters.of.panel] - plot(c(0,length(k$centers[1,]))+xshift,c(min,max),type="n",...) - mtext(paste(clusters.of.panel," (",n.elements[clusters.of.panel],")",sep=""),line=length(clusters.of.panel)-seq1(length(clusters.of.panel)),col=cols[seq1(length(clusters.of.panel)) %% n.clusters.per.panel+1] ) - } - # lines(k$centers[hcl$order[i.cluster],],col=cols[i.cluster %% n.clusters.per.panel+1]) - lines(seq1(length(k$centers[1,]))+xshift,k$centers[hcl$order[i.cluster],],col=cols[i.cluster %% n.clusters.per.panel+1]) - } -} - -my.colors <- function(n) { - few.colors=c("black","red","blue","green3","mediumorchid3","gold2","darkcyan","sienna2") - if(n<=length(few.colors)) return(few.colors [seq1(n)]) - col=integer(n) - n.families=7 - n.members=ceiling(n/n.families) - for(i in seq1(n)) { - member=ceiling(i/n.families) - ratio=(member-1)/(n.members-1) - c2=0+0.8*ratio - if(member %% 2 == 1) ratio=-ratio - c1=0.8-0.2*ratio - c3=0.75-0.2*ratio - if(i %% n.families == 1) {col[i]=rgb(c2,c2,c2)} - if(i %% n.families == 2) {col[i]=rgb(c1,c1/2,c1/2)} - if(i %% n.families == 3) {col[i]=rgb(c1/2,0.9*c1,c1/2)} - if(i %% n.families == 4) {col[i]=rgb(c1/2,c1/2,c1)} - if(i %% n.families == 5) {col[i]=rgb(c3,c3,c3/2)} - if(i %% n.families == 6) {col[i]=rgb(c3,c3/2,c3)} - if(i %% n.families == 0) {col[i]=rgb(c3/2,c3,c3)} - } - return(col) -} - -plot.my.colors <-function(n) { - x11() - col=my.colors(n) - plot(x=c(0,n),y=c(0,1),type="n") - segments(seq1(n)-1,runif(n),seq1(n),runif(n),col=col) -} - - -plot.colors <-function() { - x11(width=10,height=10) - plot(c(0,26),c(0,26),type="n") - c=colors() - n=length(c) - i=1:n - x=i%%26 - y=floor(i/26) - rect(x,y,x+1,y+1,col=c[i],border=c[i]) - text(x+0.5,y+0.5,i) -} - - -adjust.branch.sep <-function(ddr,lengths) { - assign.branch.sep <- function(d,i.leaf) { - if(is.leaf(d)) { - attr(d,"members")<-lengths[i.leaf] - i.leaf=i.leaf+1 - output=list(d=d,i.leaf=i.leaf) - return(output) - } - else{ - input=assign.branch.sep(d[[1]],i.leaf) - i.leaf=input$i.leaf - d[[1]]=input$d - - input=assign.branch.sep(d[[2]],i.leaf) - i.leaf=input$i.leaf - d[[2]]=input$d - - attr(d,"members")<-attr(d[[1]],"members")+attr(d[[2]],"members") - output=list(d=d,i.leaf=i.leaf) - return(output) - } - } - ddr<-as.dendrogram(ddr) - ddr=assign.branch.sep(ddr,1)$d - return(ddr) -} -t.dhcol <- function(dr,h,cols=c(1)) { - # check child heights - if(attr(dr[[1]],"height")<h) { - # color - ecol <- cols[coli]; - coli <<- coli+1; - dr[[1]] <- dendrapply(dr[[1]],function(e) { attr(e,"edgePar") <- list(col=ecol); e}); - attr(dr[[1]],"edgePar") <- list(col=ecol,p.border=NA,p.col=NA,t.col=1,t.cex=1.3); - } else { - dr[[1]] <- t.dhcol(dr[[1]],h,cols); - } - - if(attr(dr[[2]],"height")<h) { - # color - ecol <- cols[coli]; - coli <<- coli+1; - dr[[2]] <- dendrapply(dr[[2]],function(e) { attr(e,"edgePar") <- list(col=ecol); e}); - attr(dr[[2]],"edgePar") <- list(col=ecol,p.border=NA,p.col=NA,t.col=1,t.cex=1.3); - } else { - dr[[2]] <- t.dhcol(dr[[2]],h,cols); - } - return(dr); -} - - - -### The rest is PeterK's my.plot.dendogram - -## FIXME: need larger par("mar")[1] or [4] for longish labels ! -## {probably don't change, just print a warning ..} -my.plot.dendrogram <- - function (x, type = c("rectangle", "triangle"), center = FALSE, - edge.root = is.leaf(x) || !is.null(attr(x, "edgetext")), - nodePar = NULL, edgePar = list(), - leaflab = c("perpendicular", "textlike", "none"), dLeaf = NULL, - xlab = "", ylab = "", xaxt="n", yaxt="s", - horiz = FALSE, frame.plot = FALSE, ...) -{ - type <- match.arg(type) - leaflab <- match.arg(leaflab) - hgt <- attr(x, "height") - if (edge.root && is.logical(edge.root)) - edge.root <- 0.0625 * if(is.leaf(x)) 1 else hgt - mem.x <- .my.memberDend(x) - yTop <- hgt + edge.root - if(center) { x1 <- 0.5 ; x2 <- mem.x + 0.5 } - else { x1 <- 1 ; x2 <- mem.x } - xlim <- c(x1 - 1/2, x2 + 1/2) - ylim <- c(0, yTop) - if (horiz) {## swap and reverse direction on `x': - xl <- xlim; xlim <- rev(ylim); ylim <- xl - tmp <- xaxt; xaxt <- yaxt; yaxt <- tmp - } - plot(0, xlim = xlim, ylim = ylim, type = "n", xlab = xlab, ylab = ylab, - xaxt = xaxt, yaxt = yaxt, frame.plot = frame.plot, ...) - if(is.null(dLeaf)) - dLeaf <- .75*(if(horiz) strwidth("w") else strheight("x")) - - if (edge.root) { -### FIXME: the first edge + edgetext is drawn here, all others in plotNode() -### ----- maybe use trick with adding a single parent node to the top ? - x0 <- my.plotNodeLimit(x1, x2, x, center)$x - if (horiz) - segments(hgt, x0, yTop, x0) - else segments(x0, hgt, x0, yTop) - if (!is.null(et <- attr(x, "edgetext"))) { - my <- mean(hgt, yTop) - if (horiz) - text(my, x0, et) - else text(x0, my, et) - } - } - my.plotNode(x1, x2, x, type = type, center = center, leaflab = leaflab, - dLeaf = dLeaf, nodePar = nodePar, edgePar = edgePar, horiz = horiz) -} - -### the work horse: plot node (if pch) and lines to all children -my.plotNode <- - function(x1, x2, subtree, type, center, leaflab, dLeaf, - nodePar, edgePar, horiz = FALSE) -{ - inner <- !is.leaf(subtree) && x1 != x2 - yTop <- attr(subtree, "height") - bx <- my.plotNodeLimit(x1, x2, subtree, center) - xTop <- bx$x - usrpar <- par("usr"); - - ## handle node specific parameters in "nodePar": - hasP <- !is.null(nPar <- attr(subtree, "nodePar")) - if(!hasP) nPar <- nodePar - - if(getOption("verbose")) { - cat(if(inner)"inner node" else "leaf", ":") - if(!is.null(nPar)) { cat(" with node pars\n"); str(nPar) } - cat(if(inner)paste(" height", formatC(yTop),"; "), - "(x1,x2)= (",formatC(x1,wid=4),",",formatC(x2,wid=4),")", - "--> xTop=", formatC(xTop, wid=8),"\n", sep="") - } - - Xtract <- function(nam, L, default, indx) - rep(if(nam %in% names(L)) L[[nam]] else default, - length.out = indx)[indx] - asTxt <- function(x) # to allow 'plotmath' labels: - if(is.character(x) || is.expression(x) || is.null(x)) x else as.character(x) - - i <- if(inner || hasP) 1 else 2 # only 1 node specific par - - if(!is.null(nPar)) { ## draw this node - pch <- Xtract("pch", nPar, default = 1:2, i) - cex <- Xtract("cex", nPar, default = c(1,1), i) - col <- Xtract("col", nPar, default = par("col"), i) - bg <- Xtract("bg", nPar, default = par("bg"), i) - points(if (horiz) cbind(yTop, xTop) else cbind(xTop, yTop), - pch = pch, bg = bg, col = col, cex = cex) - } - - if(leaflab == "textlike") - p.col <- Xtract("p.col", nPar, default = "white", i) - lab.col <- Xtract("lab.col", nPar, default = par("col"), i) - lab.cex <- Xtract("lab.cex", nPar, default = c(1,1), i) - lab.font <- Xtract("lab.font", nPar, default = par("font"), i) - if (is.leaf(subtree)) { - ## label leaf - if (leaflab == "perpendicular") { # somewhat like plot.hclust - if(horiz) { - X <- yTop + dLeaf * lab.cex - Y <- xTop; srt <- 0; adj <- c(0, 0.5) - } - else { - Y <- yTop - dLeaf * lab.cex - X <- xTop; srt <- 90; adj <- 1 - } - nodeText <- asTxt(attr(subtree,"label")) - text(X, Y, nodeText, xpd = TRUE, srt = srt, adj = adj, - cex = lab.cex, col = lab.col, font = lab.font) - } - } - else if (inner) { - segmentsHV <- function(x0, y0, x1, y1) { - if (horiz) - segments(y0, x0, y1, x1, col = col, lty = lty, lwd = lwd) - else segments(x0, y0, x1, y1, col = col, lty = lty, lwd = lwd) - } - for (k in 1:length(subtree)) { - child <- subtree[[k]] - ## draw lines to the children and draw them recursively - yBot <- attr(child, "height") - if (getOption("verbose")) cat("ch.", k, "@ h=", yBot, "; ") - if (is.null(yBot)) - yBot <- 0 - xBot <- - if (center) mean(bx$limit[k:(k + 1)]) - else bx$limit[k] + .my.midDend(child) - - hasE <- !is.null(ePar <- attr(child, "edgePar")) - if (!hasE) - ePar <- edgePar - i <- if (!is.leaf(child) || hasE) 1 else 2 - ## define line attributes for segmentsHV(): - col <- Xtract("col", ePar, default = par("col"), i) - lty <- Xtract("lty", ePar, default = par("lty"), i) - lwd <- Xtract("lwd", ePar, default = par("lwd"), i) - if (type == "triangle") { - segmentsHV(xTop, yTop, xBot, yBot) - } - else { # rectangle - segmentsHV(xTop,yTop, xBot,yTop)# h - segmentsHV(xBot,yTop, xBot,yBot)# v - } - vln <- NULL - if (is.leaf(child) && leaflab == "textlike") { - nodeText <- asTxt(attr(child,"label")) - if(getOption("verbose")) - cat('-- with "label"',format(nodeText)) - hln <- 0.6 * strwidth(nodeText, cex = lab.cex)/2 - vln <- 1.5 * strheight(nodeText, cex = lab.cex)/2 - rect(xBot - hln, yBot, - xBot + hln, yBot + 2 * vln, col = p.col) - text(xBot, yBot + vln, nodeText, xpd = TRUE, - cex = lab.cex, col = lab.col, font = lab.font) - } - if (!is.null(attr(child, "edgetext"))) { - edgeText <- asTxt(attr(child, "edgetext")) - if(getOption("verbose")) - cat('-- with "edgetext"',format(edgeText)) - if (!is.null(vln)) { - mx <- - if(type == "triangle") - (xTop+ xBot+ ((xTop - xBot)/(yTop - yBot)) * vln)/2 - else xBot - my <- (yTop + yBot + 2 * vln)/2 - } - else { - mx <- if(type == "triangle") (xTop + xBot)/2 else xBot - my <- (yTop + yBot)/2 - } - ## Both for "triangle" and "rectangle" : Diamond + Text - - p.col <- Xtract("p.col", ePar, default = "white", i) - p.border <- Xtract("p.border", ePar, default = par("fg"), i) - ## edge label pars: defaults from the segments pars - p.lwd <- Xtract("p.lwd", ePar, default = lwd, i) - p.lty <- Xtract("p.lty", ePar, default = lty, i) - t.col <- Xtract("t.col", ePar, default = col, i) - t.cex <- Xtract("t.cex", ePar, default = 1, i) - t.font<- Xtract("t.font",ePar, default= par("font"), i) - t.shift <- Xtract("t.shift", ePar, default = 0.01, i) - - vlm <- strheight(c(edgeText,"h"), cex = t.cex)/2 - hlm <- strwidth (c(edgeText,"m"), cex = t.cex)/2 - hl3 <- c(hlm[1], hlm[1] + hlm[2], hlm[1]) - #polygon(mx+ c(-hl3, hl3), my + sum(vlm)*c(-1:1,1:-1), - # col = p.col, border= p.border, lty = p.lty, lwd = p.lwd) - #text(mx, my, edgeText, cex = t.cex, col = t.col, font = t.font) - if(horiz) { - text(my, mx+t.shift*abs(usrpar[3]-usrpar[4]), edgeText, cex = t.cex, col = t.col, font = t.font) - } else { - text(mx+t.shift*abs(usrpar[2]-usrpar[1]), my, edgeText, cex = t.cex, col = t.col, font = t.font) - } - } - my.plotNode(bx$limit[k], bx$limit[k + 1], subtree = child, - type, center, leaflab, dLeaf, nodePar, edgePar, horiz) - } - } -} - -my.plotNodeLimit <- function(x1, x2, subtree, center) -{ - ## get the left borders limit[k] of all children k=1..K, and - ## the handle point `x' for the edge connecting to the parent. - inner <- !is.leaf(subtree) && x1 != x2 - if(inner) { - K <- length(subtree) - mTop <- .my.memberDend(subtree) - limit <- integer(K) - xx1 <- x1 - for(k in 1:K) { - m <- .my.memberDend(subtree[[k]]) - ##if(is.null(m)) m <- 1 - xx1 <- xx1 + (if(center) (x2-x1) * m/mTop else m) - limit[k] <- xx1 - } - limit <- c(x1, limit) - } else { ## leaf - limit <- c(x1, x2) - } - mid <- attr(subtree, "midpoint") - center <- center || (inner && !is.numeric(mid)) - x <- if(center) mean(c(x1,x2)) else x1 + (if(inner) mid else 0) - list(x = x, limit = limit) -} - -.my.memberDend <- function(x) { - r <- attr(x,"x.member") - if(is.null(r)) { - r <- attr(x,"members") - if(is.null(r)) r <- 1:1 - } - r -} - -.my.midDend <- function(x) - if(is.null(mp <- attr(x, "midpoint"))) 0 else mp - - -## original Andy Liaw; modified RG, MM : -my.heatmap <- function (x, Rowv=NULL, Colv=if(symm)"Rowv" else NULL, - distfun = dist, hclustfun = hclust, - reorderfun = function(d,w) reorder(d,w), - add.expr, symm = FALSE, revC = identical(Colv, "Rowv"), - scale = c("row", "column", "none"), na.rm=TRUE, - margins = c(5, 5), ColSideColors, RowSideColors, - cexRow = 0.2 + 1/log10(nr), cexCol = 0.2 + 1/log10(nc), - labRow = NULL, labCol = NULL, main = NULL, xlab = NULL, ylab = NULL, - keep.dendro = FALSE, - verbose = getOption("verbose"), imageSize=4, imageVSize=imageSize,imageHSize=imageSize,lasCol=2, lasRow=2, respect=F, ...) -{ - scale <- if(symm && missing(scale)) "none" else match.arg(scale) - if(length(di <- dim(x)) != 2 || !is.numeric(x)) - stop("'x' must be a numeric matrix") - nr <- di[1] - nc <- di[2] - if(nr <= 1 || nc <= 1) - stop("'x' must have at least 2 rows and 2 columns") - if(!is.numeric(margins) || length(margins) != 2) - stop("'margins' must be a numeric vector of length 2") - - doRdend <- !identical(Rowv,NA) - doCdend <- !identical(Colv,NA) - ## by default order by row/col means - if(is.null(Rowv)) Rowv <- rowMeans(x, na.rm = na.rm) - if(is.null(Colv)) Colv <- colMeans(x, na.rm = na.rm) - - ## get the dendrograms and reordering indices - - if(doRdend) { - if(inherits(Rowv, "dendrogram")) - ddr <- Rowv - else { - hcr <- hclustfun(distfun(x)) - ddr <- as.dendrogram(hcr) - if(!is.logical(Rowv) || Rowv) - ddr <- reorderfun(ddr, Rowv) - } - if(nr != length(rowInd <- order.dendrogram(ddr))) - stop("row dendrogram ordering gave index of wrong length") - } - else rowInd <- 1:nr - - if(doCdend) { - if(inherits(Colv, "dendrogram")) - ddc <- Colv - else if(identical(Colv, "Rowv")) { - if(nr != nc) - stop('Colv = "Rowv" but nrow(x) != ncol(x)') - ddc <- ddr - } - else { - hcc <- hclustfun(distfun(if(symm)x else t(x))) - ddc <- as.dendrogram(hcc) - if(!is.logical(Colv) || Colv) - ddc <- reorderfun(ddc, Colv) - } - if(nc != length(colInd <- order.dendrogram(ddc))) - stop("column dendrogram ordering gave index of wrong length") - } - else colInd <- 1:nc - - ## reorder x - x <- x[rowInd, colInd] - - labRow <- - if(is.null(labRow)) - if(is.null(rownames(x))) (1:nr)[rowInd] else rownames(x) - else labRow[rowInd] - labCol <- - if(is.null(labCol)) - if(is.null(colnames(x))) (1:nc)[colInd] else colnames(x) - else labCol[colInd] - - if(scale == "row") { - x <- sweep(x, 1, rowMeans(x, na.rm = na.rm)) - sx <- apply(x, 1, sd, na.rm = na.rm) - x <- sweep(x, 1, sx, "/") - } - else if(scale == "column") { - x <- sweep(x, 2, colMeans(x, na.rm = na.rm)) - sx <- apply(x, 2, sd, na.rm = na.rm) - x <- sweep(x, 2, sx, "/") - } - - ## Calculate the plot layout - lmat <- rbind(c(NA, 3), 2:1) - lwid <- c(if(doRdend) 1 else 0.05, imageHSize) - lhei <- c((if(doCdend) 1 else 0.05) + if(!is.null(main)) 0.2 else 0, imageVSize) - if(!missing(ColSideColors)) { ## add middle row to layout - if(!is.character(ColSideColors) || length(ColSideColors) != nc) - stop("'ColSideColors' must be a character vector of length ncol(x)") - lmat <- rbind(lmat[1,]+1, c(NA,1), lmat[2,]+1) - lhei <- c(lhei[1], 0.2, lhei[2]) - } - if(!missing(RowSideColors)) { ## add middle column to layout - if(!is.character(RowSideColors) || length(RowSideColors) != nr) - stop("'RowSideColors' must be a character vector of length nrow(x)") - lmat <- cbind(lmat[,1]+1, c(rep(NA, nrow(lmat)-1), 1), lmat[,2]+1) - lwid <- c(lwid[1], 0.2, lwid[2]) - } - lmat[is.na(lmat)] <- 0 - if(verbose) { - cat("layout: widths = ", lwid, ", heights = ", lhei,"; lmat=\n") - print(lmat) - } - - ## Graphics `output' ----------------------- - - op <- par(no.readonly = TRUE) - on.exit(par(op)) - layout(lmat, widths = lwid, heights = lhei, respect = respect) - ## draw the side bars - if(!missing(RowSideColors)) { - par(mar = c(margins[1],0, 0,0.5)) - image(rbind(1:nr), col = RowSideColors[rowInd], axes = FALSE) - } - if(!missing(ColSideColors)) { - par(mar = c(0.5,0, 0,margins[2])) - image(cbind(1:nc), col = ColSideColors[colInd], axes = FALSE) - } - ## draw the main carpet - par(mar = c(margins[1], 0, 0, margins[2])) - if(!symm || scale != "none") - x <- t(x) - if(revC) { # x columns reversed - iy <- nr:1 - ddr <- rev(ddr) - x <- x[,iy] - } else iy <- 1:nr - - image(1:nc, 1:nr, x, xlim = 0.5+ c(0, nc), ylim = 0.5+ c(0, nr), - axes = FALSE, xlab = "", ylab = "", ...) - axis(1, 1:nc, labels= labCol, las= lasCol, line= -0.5, tick= 0, cex.axis= cexCol) - if(!is.null(xlab)) mtext(xlab, side = 1, line = margins[1] - 1.25) - axis(4, iy, labels= labRow, las= lasRow, line= -0.5, tick= 0, cex.axis= cexRow) - if(!is.null(ylab)) mtext(ylab, side = 4, line = margins[2] - 1.25,las=lasRow) - if (!missing(add.expr)) - eval(substitute(add.expr)) - - ## the two dendrograms : - par(mar = c(margins[1], 0, 0, 0)) - if(doRdend) - my.plot.dendrogram(ddr, horiz = TRUE, axes = FALSE, yaxs = "i", leaflab = "none") - else frame() - - par(mar = c(0, 0, if(!is.null(main)) 1 else 0, margins[2])) - if(doCdend) - my.plot.dendrogram(ddc, axes = FALSE, xaxs = "i", leaflab = "none") - else if(!is.null(main)) frame() - - ## title - if(!is.null(main)) title(main, cex.main = 1.5*op[["cex.main"]]) - - invisible(list(rowInd = rowInd, colInd = colInd, - Rowv = if(keep.dendro && doRdend) ddr, - Colv = if(keep.dendro && doCdend) ddc )) -}
--- a/tool_dependencies.xml Wed Nov 12 15:10:51 2014 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,6 +0,0 @@ -<?xml version="1.0"?> -<tool_dependency> - <set_environment version="1.0"> - <environment_variable name="R_SCRIPT_PATH" action="set_to">$REPOSITORY_INSTALL_DIR</environment_variable> - </set_environment> -</tool_dependency> \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/upload/region_motif_compare.r Wed Nov 12 15:19:37 2014 -0500 @@ -0,0 +1,188 @@ +# Name: region_motif_compare.r +# Description: Reads in two count files and determines enriched and depleted +# motifs (or any location based feature) based on poisson tests and gc +# corrections. All enrichment ratios relative to overall count / gc ratios. +# Author: Jeremy liu +# Email: jeremy.liu@yale.edu +# Date: 14/07/03 +# Note: This script is meant to be invoked with the following command +# R --slave --vanilla -f ./region_motif_compare.r --args <workingdir> <db> <intab1> <intab2> +# <enriched_tab> <depleted_tab> <plots_png> +# <workingdir> is working directory of galaxy installation +# <db> types: "t" test, "p" pouya, "j" jaspar jolma, "m" mouse, "c" combined +# Dependencies: plotting.r + +# Auxiliary function to concatenate multiple strings +concat <- function(...) { + input_list <- list(...) + return(paste(input_list, sep="", collapse="")) +} + +# Supress all warning messages to prevent Galaxy treating warnings as errors +options(warn=-1) + +# Set common and data directories +args <- commandArgs() +workingDir = args[7] +dbDir = concat(workingDir, "/region_motif_db") +dbCode = args[8] +# dbCode "c" implemented when pwmFile is loaded +if (dbCode == "t" | dbCode == "p") { + pwmFile = concat(dbDir, "/pwms/pouya.pwms.from.seq.RData") +} else if (dbCode == "j") { + pwmFile = concat(dbDir, "/pwms/jaspar.jolma.pwms.from.seq.RData") +} else if (dbCode == "m") { + pwmFile = concat(dbDir, "/pwms/mm9.pwms.from.seq.RData") +} else if (dbCode == "c") { # rest of dbCode "c" implemeted when pwmFile loaded + pwmFile = concat(dbDir, "/pwms/pouya.pwms.from.seq.RData") + pwmFile2 = concat(dbDir, "/pwms/jaspar.jolma.pwms.from.seq.RData") +} else { + pwmFile = concat(dbDir, "/pwms/pouya.pwms.from.seq.RData") +} + +# Set input and reference files +inTab1 = args[9] +inTab2 = args[10] +enrichTab = args[11] +depleteTab = args[12] +plotsPng = args[13] + +# Load dependencies +source(concat(workingDir, "/region_motif_lib/plotting.r")) + +# Auxiliary function to read in tab file and prepare the data +read_tsv <- function(file) { + data = read.table(file, sep="\t", stringsAsFactors=FALSE) + names(data)[names(data) == "V1"] = "motif" + names(data)[names(data) == "V2"] = "counts" + return(data) +} + +startTime = Sys.time() +cat("Running ... Started at:", format(startTime, "%a %b %d %X %Y"), "...\n") + +# Loading motif position weight matrix (pwm) file and input tab file +cat("Loading and reading input region motif count files...\n") +load(pwmFile) # pwms data structure +if (dbCode == "c") { # Remaining implementation of dbCode "c" combined + temp = pwms + load(pwmFile2) + pwms = append(temp, pwms) +} +region1DF = read_tsv(inTab1) +region2DF = read_tsv(inTab2) +region1Counts = region1DF$counts +region2Counts = region2DF$counts +names(region1Counts) = region1DF$motif +names(region2Counts) = region2DF$motif + +# Processing count vectors to account for missing 0 count motifs, then sorting +cat("Performing 0 count correction and sorting...\n") +allNames = union(names(region1Counts), names(region2Counts)) +region1Diff = setdiff(allNames, names(region1Counts)) +region2Diff = setdiff(allNames, names(region2Counts)) +addCounts1 = rep(0, length(region1Diff)) +addCounts2 = rep(0, length(region2Diff)) +names(addCounts1) = region1Diff +names(addCounts2) = region2Diff +newCounts1 = append(region1Counts, addCounts1) +newCounts2 = append(region2Counts, addCounts2) +region1Counts = newCounts1[sort.int(names(newCounts1), index.return=TRUE)$ix] +region2Counts = newCounts2[sort.int(names(newCounts2), index.return=TRUE)$ix] + +# Generate gc content matrix +gc = sapply(pwms, function(i) mean(i[2:3,3:18])) + +# Apply poisson test, calculate p and q values, and filter significant results +cat("Applying poisson test...\n") +rValue = sum(region2Counts) / sum(region1Counts) +pValue = sapply(seq(along=region1Counts), function(i) { + poisson.test(c(region1Counts[i], region2Counts[i]), r=1/rValue)$p.value +}) +qValue = p.adjust(pValue, "fdr") +indices = which(qValue<0.1 & abs(log2(region1Counts/region2Counts/rValue))>log2(1.5)) + +# Setting up output diagnostic plots, 4 in 1 png image +png(plotsPng, width=800, height=800) +xlab = "region1_count" +ylab = "region2_count" +lim = c(0.5, 5000) +layout(matrix(1:4, ncol=2)) +par(mar=c(5, 5, 5, 1)) + +# Plot all motif counts along the linear correlation coefficient +plot.scatter(region1Counts+0.5, region2Counts+0.5, log="xy", xlab=xlab, ylab=ylab, + cex.lab=2.2, cex.axis=1.8, xlim=lim, ylim=lim*rValue) +abline(0, rValue, untf=T) +abline(0, rValue*2, untf=T, lty=2) +abline(0, rValue/2, untf=T, lty=2) + +# Plot enriched and depleted motifs in red, housed in second plot +plot.scatter(region1Counts+0.5, region2Counts+0.5, log="xy", xlab=xlab, ylab=ylab, + cex.lab=2.2, cex.axis=1.8, xlim=lim, ylim=lim*rValue) +points(region1Counts[indices]+0.5, region2Counts[indices]+0.5, col="red") +abline(0, rValue, untf=T) +abline(0, rValue*2, untf=T, lty=2) +abline(0, rValue/2, untf=T, lty=2) + +# Apply and plot gc correction and loess curve +cat("Applying gc correction, rerunning poisson test...\n") +ind = which(region1Counts>5) +gc = gc[names(region2Counts)] # Reorder the indices of pwms to match input data +lo = plot.scatter(gc,log2(region2Counts/region1Counts),draw.loess=T, + xlab="gc content of motif",ylab=paste("log2(",ylab,"/",xlab,")"), + cex.lab=2.2,cex.axis=1.8,ind=ind) # This function is in plotting.r +gcCorrection = 2^approx(lo$loess,xout=gc,rule=2)$y + +# Recalculate p and q values, and filter for significant entries +pValueGC = sapply(seq(along=region1Counts),function(i) { + poisson.test(c(region1Counts[i],region2Counts[i]),r=1/gcCorrection[i])$p.value +}) +qValueGC=p.adjust(pValueGC,"fdr") +indicesGC = which(qValueGC<0.1 & abs(log2(region1Counts/region2Counts*gcCorrection))>log2(1.5)) + +# Plot gc corrected motif counts +plot.scatter(region1Counts+0.5, (region2Counts+0.5)/gcCorrection, log="xy", + xlab=xlab, ylab=paste(ylab,"(normalized)"), cex.lab=2.2, cex.axis=1.8, + xlim=lim, ylim=lim) +points(region1Counts[indicesGC]+0.5, + (region2Counts[indicesGC]+0.5)/gcCorrection[indicesGC], col="red") +abline(0,1) +abline(0,1*2,untf=T,lty=2) +abline(0,1/2,untf=T,lty=2) + +# Trim results, compile statistics and output to file +# Only does so if significant results are computed +if(length(indicesGC) > 0) { + # Calculate expected counts and enrichment ratios + cat("Calculating statistics...\n") + nullExpect = region1Counts * gcCorrection + enrichment = region2Counts / nullExpect + + # Reorder selected indices in ascending pvalue + cat("Reordering by ascending pvalue...\n") + indicesReorder = indicesGC[order(pValueGC[indicesGC])] + + # Combine data into one data frame and output to two files + cat("Splitting and outputting data...\n") + outDF = data.frame(motif=names(pValueGC), p=as.numeric(pValueGC), q=qValueGC, + stringsAsFactors=F, region_1_count=region1Counts, + null_expectation=round(nullExpect,2), region_2_count=region2Counts, + enrichment=enrichment)[indicesReorder,] + names(outDF)[which(names(outDF)=="region_1_count")]=xlab + names(outDF)[which(names(outDF)=="region_2_count")]=ylab + indicesEnrich = which(outDF$enrichment>1) + indicesDeplete = which(outDF$enrichment<1) + outDF$enrichment = ifelse(outDF$enrichment>1, + round(outDF$enrichment,3), + paste("1/",round(1/outDF$enrichment,3))) + write.table(outDF[indicesEnrich,], file=enrichTab, quote=FALSE, + sep="\t", append=FALSE, row.names=FALSE, col.names=TRUE) + write.table(outDF[indicesDeplete,], file=depleteTab, quote=FALSE, + sep="\t", append=FALSE, row.names=FALSE, col.names=TRUE) +} + +# Catch display messages and output timing information +catchMessage = dev.off() +cat("Done. Job started at:", format(startTime, "%a %b %d %X %Y."), + "Job ended at:", format(Sys.time(), "%a %b %d %X %Y."), "\n")
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/upload/region_motif_compare.xml Wed Nov 12 15:19:37 2014 -0500 @@ -0,0 +1,32 @@ +<tool id="region_motif_compare" name="Region Motif Count Compare"> + <description>for comparing the motif counts in different region sets</description> + <requirements> + <requirement type="set_environment">RMOTIF_PATH</requirement> + </requirements> + <command interpreter="Rscript"> + region_motif_compare.r --args \$RMOTIF_PATH $db_type $in_tab_1 $in_tab_2 $out_enriched $out_depleted $out_plots + </command> + <inputs> + <param name="in_tab_1" type="data" format="tabular" label="Region Set 1 Motif Count File"/> + <param name="in_tab_2" type="data" format="tabular" label="Region Set 2 Motif Count File"/> + <param name="db_type" type="select" label="Select Motif Database" > + <option value="t">Test Pouya Subset (hg19)</option> + <option value="p">Pouya Encode Motifs (hg19)</option> + <option value="j">Jaspar and Jolma Motifs (hg19)</option> + <option value="m">Mouse Motifs (mm9)</option> + <option value="c">Pouya, Jaspar, and Jolma Combined (hg19)</option> + </param> + </inputs> + <outputs> + <data name="out_enriched" format="tabular" label="Enriched Motifs"/> + <data name="out_depleted" format="tabular" label="Depleted Motifs"/> + <data name="out_plots" format="png" label="Motif Count Comparison Plots"/> + </outputs> + + <help> + This tools reads in two counts file and determines enriched and depleted + motifs in two different region sets based on poisson calculation with + gc correction. + </help> + +</tool> \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/upload/region_motif_intersect.r Wed Nov 12 15:19:37 2014 -0500 @@ -0,0 +1,102 @@ +# Name: region_motif_intersect.r +# Description: Takes a bed file of target regions and counts intersections +# of each motif (built in rdata database) and target regions. +# Author: Jeremy liu +# Email: jeremy.liu@yale.edu +# Date: 14/07/02 +# Note: This script is meant to be invoked with the following command +# R --slave --vanilla -f ./region_motif_intersect.r --args <workingdir> <db> <inbed> <outtab> +# <workingdir> is working directory of galaxy installation +# <db> types: "t" test, "p" pouya, "j" jaspar jolma, "m" mouse +# Dependencies: none + +# Auxiliary function to concatenate multiple strings +concat <- function(...) { + input_list <- list(...) + return(paste(input_list, sep="", collapse="")) +} + +# Set common and data directories +args <- commandArgs() +workingDir = args[7] +dbDir = concat(workingDir, "/region_motif_db") +dbCode = args[8] +if (dbCode == "t") { + motifDB = concat(dbDir, "/pouya_test_motifs.bed.bgz") +} else if (dbCode == "p") { + motifDB = concat(dbDir, "/pouya_motifs.bed.bgz") +} else if (dbCode == "j") { + motifDB = concat(dbDir, "/jaspar_jolma_motifs.bed.bgz") +} else if (dbCode == "m") { + motifDB = concat(dbDir, "/mm9_motifs.bed.bgz") +} else { + motifDB = concat(dbDir, "/pouya_motifs.bed.bgz") +} + +# Set input and reference files, comment to toggle commmand line arguments +inBed = args[9] +outTab = args[10] + +# Auxiliary function to read in BED file +read_bed <- function(file) { + return(read.table(file, sep="\t", stringsAsFactors=FALSE)) +} + +startTime = Sys.time() +cat("Running ... Started at:", format(startTime, "%a %b %d %X %Y"), "...\n") + +# Load dependencies +cat("Loading dependencies...\n") +suppressPackageStartupMessages(library(Rsamtools, quietly=TRUE)) + +# Initializing hash table (as env) with motif names and loading tabix file +cat("Loading motif database and initializing hash table...\n") +motifTable = new.env() +motifTbx <- TabixFile(motifDB) + +# Loading input bed file, convert integer columns to numeric, name columns +cat("Loading region file...\n") +regionsDF = read_bed(inBed) +dfTemp = sapply(regionsDF, is.integer) +regionsDF[dfTemp] = lapply(regionsDF[dfTemp], as.numeric) +names(regionsDF)[names(regionsDF) == "V1"] = "chr" +names(regionsDF)[names(regionsDF) == "V2"] = "start" +names(regionsDF)[names(regionsDF) == "V3"] = "end" + +# Filtering regions to exclude chromosomes not in motif database +cat("Determining intersection counts...\n") +motifTbxChrs = seqnamesTabix(motifTbx) +regionsDFFilter = subset(regionsDF, chr %in% motifTbxChrs) + +# Loading regions into GRanges object and scanning motif tabix database +# Region end is incremented by 1 since scanTabix querying is inclusive for +# position start but exclusive for position end. +param = GRanges(regionsDFFilter$chr, IRanges(regionsDFFilter$start, + end=regionsDFFilter$end + 1)) +regionsIntersects = scanTabix(motifTbx, param=param) + +# Parsing result list and updating motif count hash table +cat("Parsing result list...\n") +for(regionIntersects in regionsIntersects) { + for(regionIntersect in strsplit(regionIntersects, " ")) { + intersectMotif = strsplit(regionIntersect, "\t")[[1]][4] + if(is.null(motifTable[[intersectMotif]])) { + motifTable[[intersectMotif]] = 1 + } else { + motifTable[[intersectMotif]] = motifTable[[intersectMotif]] + 1 + } + } +} + +# Converting motif count hash table to an integer vector for output +counts = integer(length = length(ls(motifTable))) +names(counts) = ls(motifTable) +for(motifName in ls(motifTable)) { + counts[motifName] = as.integer(motifTable[[motifName]]) +} + +# Outputting intersection counts to tab delineated file +cat("Outputting to file...\n") +write.table(counts, outTab, quote=FALSE, sep="\t", row.names=TRUE, col.names=FALSE) +cat("Done. Job started at:", format(startTime, "%a %b %d %X %Y."), + "Job ended at:", format(Sys.time(), "%a %b %d %X %Y."), "\n")
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/upload/region_motif_intersect.xml Wed Nov 12 15:19:37 2014 -0500 @@ -0,0 +1,27 @@ +<tool id="region_motif_intersect" name="Region Motif Intersect"> + <description>for computing the motifs that lie inside a region set</description> + <requirements> + <requirement type="set_environment">RMOTIF_PATH</requirement> + </requirements> + <command interpreter="Rscript"> + region_motif_intersect.r --args \$RMOTIF_PATH $db_type $in_bed $out_tab + </command> + <inputs> + <param name="in_bed" type="data" format="bed" label="Input BED File" /> + <param name="db_type" type="select" label="Select Motif Database" > + <option value="t">Test Pouya Subset (hg19)</option> + <option value="p">Pouya Encode Motifs (hg19)</option> + <option value="j">Jaspar and Jolma Motifs (hg19)</option> + <option value="m">Mouse Motifs (mm9)</option> + </param> + </inputs> + <outputs> + <data name="out_tab" format="tabular" /> + </outputs> + + <help> + This tool computes the motifs and the number of motifs that intersect + any region in a input set of regions. + </help> + +</tool> \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/upload/tool_dependencies.xml Wed Nov 12 15:19:37 2014 -0500 @@ -0,0 +1,6 @@ +<?xml version="1.0"?> +<tool_dependency> + <set_environment version="1.0"> + <environment_variable name="RMOTIF_PATH" action="set_to">$REPOSITORY_INSTALL_DIR</environment_variable> + </set_environment> +</tool_dependency> \ No newline at end of file