Mercurial > repos > xuebing > sharplab_interval_analysis
changeset 19:d325683ec368
Deleted selected files
| author | xuebing |
|---|---|
| date | Sat, 31 Mar 2012 08:26:17 -0400 |
| parents | 9bbb37e8683f |
| children | 16ba480adf96 |
| files | interval/StartGenometriCorr.xml interval/Start_GenometriCorr.R interval/align2database.py interval/align2database.xml interval/align2multiple.xml interval/alignr.py interval/alignr.xml interval/alignvis.py interval/alignvis.r interval/alignvis.xml interval/bedClean.py interval/bed_to_bam.xml interval/bedclean.xml interval/bedsort.xml interval/bigWigAverageOverBed.xml interval/binaverage.xml interval/binnedAverage.py interval/bwBinavg.xml interval/closestBed.py interval/closestBed.xml interval/collapseBed.py interval/collapseBed.xml interval/collapseBed2.py interval/collapseTab.py interval/collapseTab.xml interval/endbias.py interval/endbias.xml interval/genomeView.xml interval/genomeview-old2.r interval/genomeview.r interval/genomeview_notused interval/getGenomicScore.py interval/intersectSig.py interval/intersectSig.xml interval/intersectbed.xml interval/intervalOverlap.py interval/intervalSize.py interval/intervalSize.xml interval/makebigwig.sh interval/makebigwig.sh-old interval/makebigwig.xml interval/makewindow.py interval/makewindow.xml interval/metaintv.py interval/metaintv.xml interval/metaintv2.py interval/metaintv3.py interval/metaintv_ext.py interval/metaintv_ext.xml interval/phastCons.xml interval/random_interval.py interval/random_interval.xml interval/removeDuplicate.xml interval/resize.py interval/resize.xml interval/shuffleBed.py interval/shuffleBed.xml interval/spatial_proximity.py interval/spatial_proximity.xml |
| diffstat | 58 files changed, 0 insertions(+), 3508 deletions(-) [+] |
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--- a/interval/StartGenometriCorr.xml Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,23 +0,0 @@ -<tool id="genometric_correlation" name="Genometric Correlation"> -<description>between two files of genomic intervals</description> -<command interpreter="Rscript --vanilla"> -Start_GenometriCorr.R $config $query $reference $output_options $output -</command> -<inputs> -<param format="text" name="config" type="data" label="Configuration file"/> -<param format="text" name="query" type="data" label="Query intervals file"/> -<param format="text" name="reference" type="data" label="Reference intervals file"/> -<param name="output_options" type="select" label="Type of output"> -<option value="plot">ECDF plots</option> -<option value="vis">Graphic visualization</option> -<option value="stats">Text output of statistics</option> -<option value="plot_vis">All</option> -</param> -</inputs> -<outputs> -<data name="output" format="pdf"/> -</outputs> -<help> -This tool determines the statistical relationship (if any) between two sets of genomic intervals. Output can be text only, plot (ECDF curves), or a more colorful graphic. -</help> -</tool> \ No newline at end of file
--- a/interval/Start_GenometriCorr.R Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,105 +0,0 @@ -# Start_GenometriCorr.R - -################################################### -# # -# command-line interface to GenometriCorr # -# functions, for use with Galaxy. # -# # -################################################### - -capture.output <- function (result, pdffile, output_options) -{ - if(output_options != "stats") - { - pdf(file=pdffile, width=10, height=19, paper="special") - - if (output_options != "vis") #need to do a plot - { - mymat <- matrix(ncol=3, nrow=4) - mymat[1,1] <- 1 - mymat[1,2] <- 2 - mymat[1,3] <- 3 - mymat[2,1] <- 4 - mymat[2,2] <- 5 - mymat[2,3] <- 6 - mymat[3,1] <- 7 - mymat[3,2] <- 8 - mymat[3,3] <- 9 - mymat[4,1] <- 10 - mymat[4,2] <- 11 - mymat[4,3] <- 12 - - layout(mymat, heights=c(0.2,0.2,0.2,0.2)) - plot(result, pdffile, make.new=FALSE) - } - if (output_options != "plot") #need to do the bigger graphic - { - mymat <- matrix(ncol=2, nrow=8) - mymat[1,1] <- 2 - mymat[1,2] <- 3 - mymat[2,1] <- 4 - mymat[2,2] <- 4 - mymat[3,1] <- 1 - mymat[3,2] <- 1 - mymat[4,1] <- 5 - mymat[4,2] <- 6 - mymat[5,1] <- 7 - mymat[5,2] <- 7 - mymat[6,1] <- 8 - mymat[6,2] <- 9 - mymat[7,1] <- 10 - mymat[7,2] <- 10 - mymat[8,1] <- 11 - mymat[8,2] <- 12 - layoutresults <- 3 - - layout(mymat, heights=c(0.05,0.05,0.15,0.15,0.15,0.15,0.15,0.15)) - visualize(result, pdffile, make.new=FALSE) - } - dev.off() - } - - if (output_options == "stats") - { - show(result) - } -} - - - -# Reads the command line arguments -args <- commandArgs(trailingOnly=T) - -suppressPackageStartupMessages(library('GenometriCorr', warn.conflicts=F, verbose=F)) -suppressPackageStartupMessages(library('graphics', warn.conflicts=F, verbose=F)) -suppressPackageStartupMessages(library('gdata', warn.conflicts=F, verbose=F)) -suppressPackageStartupMessages(library('gplots', warn.conflicts=F, verbose=F)) -suppressPackageStartupMessages(library('gtools', warn.conflicts=F, verbose=F)) -suppressPackageStartupMessages(library('caTools', warn.conflicts=F, verbose=F)) -suppressPackageStartupMessages(library('grid', warn.conflicts=F, verbose=F)) - - - -# Variables -query_file <- "" -reference_file <- "" -config_file <- "" -output_options <- "" - -# Parse the command line arguments - -config_file <- args[1] -query_file <- as.character(args[2]) -reference_file <- as.character(args[3]) -output_options <- args[4] -pdffile <- args[5] - -conf<-new("GenometriCorrConfig",config_file) - -print('OK') - -result<-suppressWarnings(suppressPackageStartupMessages(GenometriCorr:::run.config(conf,query=query_file,reference=reference_file))) -print('OK2') - -hideoutput <- capture.output(result, pdffile=args[5], output_options) -
--- a/interval/align2database.py Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,104 +0,0 @@ -''' -align mulitple bed to one bed -python align_multiple.py hmChIP_mm9_peak_bed/mm9-GSE19999_PolII_P25_all.cod.bed hmChIP_mm9_peak_bed/ test.txt test.pdf 100 5000 -''' - -import os,sys,random -def main(): - queryfile = sys.argv[1] - inpath = sys.argv[2] - outputdata = sys.argv[3] - outputerr = sys.argv[4] - barplotpdf = sys.argv[5] - min_feat = sys.argv[6] # min features overlap - windowsize = sys.argv[7] - anchor = sys.argv[8] - span = sys.argv[9] # loess smooth parameter - - inpath = inpath.rstrip('/') - #os.system('rm '+inpath+'/*tmp*') - - infiles = os.listdir(inpath) - - #print len(infiles),' files\n' - i = 0 - for infile in infiles: - if 'tmp' in infile: - #os.system('rm '+inpath+'/'+infile) - continue - i = i +1 - print i,infile - output = infile.split('/')[-1]+'-to-'+queryfile.split('/')[-1]#'.summary' - if anchor == 'database': - command = 'python /Users/xuebing/galaxy-dist/tools/mytools/alignr.py -b '+inpath+'/'+infile+' -a '+queryfile+' -o '+output+' --summary-only -q -w '+windowsize - else: - command = 'python /Users/xuebing/galaxy-dist/tools/mytools/alignr.py -a '+inpath+'/'+infile+' -b '+queryfile+' -o '+output+' --summary-only -q -w '+windowsize - #print command+'\n' - os.system(command) - print 'start visualization...' - # visualize - rscriptfile = 'f-'+str(random.random())+'.r' - r = open(rscriptfile,'w') - r.write("files <- dir('.','summary',full.name=T)\n") - #r.write("print(files)\n") - r.write("x <- read.table(files[1])\n") - r.write("err <- read.table(gsub('summary','standarderror',files[1]))\n") - r.write("for (filename in files[2:length(files)]){\n") - r.write(" x <- rbind(x,read.table(filename))\n") - r.write(" err <- rbind(err,read.table(gsub('summary','standarderror',filename)))\n") - r.write("}\n") - r.write("x <- x[x[,2] > "+min_feat+",]\n") - r.write("err <- err[err[,2] > "+min_feat+",]\n") - r.write("name <- as.character(x[,1])\n") - r.write("nfeat <- x[,2]\n") - r.write("x <- x[,3:ncol(x)]\n") - r.write("err <- err[,3:ncol(err)]\n") - r.write("for (i in 1:nrow(x)) {\n") - r.write(" name[i] <- strsplit(name[i],'-to-')[[1]][1]\n") - r.write("}\n") - # remove rows that have no variation, which cause problem in heatmap. This is the case when align to itself - r.write("toremove <- seq(nrow(x))\n") - r.write("for (i in 1:nrow(x)){\n") - r.write(" toremove[i] <- all(x[i,] == x[i,1])\n") - r.write("}\n") - r.write("x <- x[!toremove,]\n") - r.write("err <- err[!toremove,]\n") - r.write("name <- name[!toremove]\n") - r.write("nfeat <- nfeat[!toremove]\n") - r.write("write.table(cbind(name,nfeat,x),file='"+outputdata+"',sep ='\\t',quote=F,row.names=F,col.names=F)\n") - r.write("write.table(cbind(name,nfeat,err),file='"+outputerr+"',sep ='\\t',quote=F,row.names=F,col.names=F)\n") - - r.write("pdf('"+barplotpdf+"')\n") - r.write("heatmap(t(scale(t(as.matrix(x,nc=ncol(x))))),Colv=NA,labRow=name,labCol=NA,margins=c(1,8),cexRow=0.02+1/log(nrow(x)),col=heat.colors(1000))\n") - - if windowsize != '0' : - r.write("xticks <- seq(-"+windowsize+","+windowsize+",length.out=100)\n") - r.write("xlab <- 'relative position (bp)'\n") - else: - r.write("xticks <- seq(100)\n") - r.write("xlab <- 'relative position (bin)'\n") - - #r.write("plot(xticks,colSums(t(scale(t(as.matrix(x,nc=ncol(x)))))),xlab='relative position (bp)',type='l',lwd=2,main='total signal')\n") - r.write("for (i in 1:nrow(x)) {\n") - r.write(" avg <- x[i,]/nfeat[i]\n") - #r.write(" maxv <- max(avg)\n") - #r.write(" minv <- min(avg)\n") - #r.write(" medv <- median(avg)\n") - #r.write(" if (maxv < "+fold+"*medv | minv*"+fold+">medv){next}\n") - #smooth - if float(span) >= 0.1: - r.write(" avg = loess(as.numeric(avg)~xticks,span="+span+")$fitted\n") - r.write(" err[i,] = loess(as.numeric(err[i,])~xticks,span="+span+")$fitted\n") - r.write(" par(cex=1.5)\n") - r.write(" plot(xticks,avg,ylab='average coverage',main=paste(name[i],'\n n=',nfeat[i],sep=''),xlab=xlab,type='l',lwd=1,ylim=c(min(avg-err[i,]),max(avg+err[i,])))\n") - r.write(" polygon(c(xticks,rev(xticks)),c(avg+err[i,],rev(avg-err[i,])),col='slateblue1',border=NA)\n") - r.write(" lines(xticks,avg,type='l',lwd=1)\n") - r.write("}\n") - r.write("dev.off()\n") - r.close() - os.system("R --vanilla < "+rscriptfile) - os.system('rm '+rscriptfile) - os.system('rm *.summary') - os.system('rm *.standarderror') - -main()
--- a/interval/align2database.xml Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,54 +0,0 @@ -<tool id="align2database" name="align-to-database"> - <description> features </description> - <command interpreter="python"> align2database.py $query $database $output_coverage $output_standarderror $output_plot $minfeat $windowsize $anchor $span> $outlog </command> - <inputs> - <param name="query" type="data" format="interval" label="Query intervals" help= "keep it small (less than 1,000,000 lines)"/> - <param name="database" type="select" label="Feature database"> - <option value="/Users/xuebing/galaxy-dist/tool-data/aligndb/mm9/feature_database" selected="true">All mm9 features (over 200)</option> - <option value="/Users/xuebing/galaxy-dist/tool-data/aligndb/mm9/annotation">Annotated mm9 features</option> - <option value="/Users/xuebing/galaxy-dist/tool-data/aligndb/mm9/CLIP">protein bound RNA (CLIP) mm9 </option> - <option value="/Users/xuebing/galaxy-dist/tool-data/aligndb/mm9/conservedmiRNAseedsite">conserved miRNA target sites mm9 </option> - <option value="/Users/xuebing/galaxy-dist/tool-data/aligndb/hg18/all-feature">Human ChIP hmChIP database hg18</option> - <option value="/Users/xuebing/galaxy-dist/tool-data/aligndb/hg18/gene-feature">Human gene features hg18</option> - <option value="/Users/xuebing/galaxy-dist/tool-data/aligndb/hg19/conservedmiRNAseedsite">conserved miRNA target sites hg19 </option> - </param> - <param name="anchor" label="Anchor to query features" help="default anchoring to database featuers" type="boolean" truevalue="query" falsevalue="database" checked="False"/> - <param name="windowsize" size="10" type="integer" value="5000" label="Window size (-w)" help="will create new intervals of w bp flanking the original center. set to 0 will not change input interval size)"/> - <param name="minfeat" size="10" type="integer" value="100" label="Minimum number of query intervals hits" help="database features overlapping with too few query intervals are discarded"/> - <param name="span" size="10" type="float" value="0.1" label="loess span: smoothing parameter" help="value less then 0.1 disables smoothing"/> - <param name="outputlabel" size="80" type="text" label="Output label" value="test"/> - -</inputs> - <outputs> - <data format="txt" name="outlog" label="${outputlabel} (log)"/> - <data format="tabular" name="output_standarderror" label="${outputlabel} (standard error)"/> - <data format="tabular" name="output_coverage" label="${outputlabel} (coverage)"/> - <data format="pdf" name="output_plot" label="${outputlabel} (plot)"/> - </outputs> - <help> - -**Example output** - -.. image:: ./static/operation_icons/align_multiple2.png - - -**What it does** - -This tool aligns a query interval set (such as ChIP peaks) to a database of features (such as other ChIP peaks or TSS/splice sites), calculates and plots the relative distance of database features to the query intervals. Currently two databases are available: - --- **ChIP peaks** from 191 ChIP experiments (processed from hmChIP database, see individual peak/BED files in **Shared Data**) - --- **Annotated gene features**, such as: TSS, TES, 5'ss, 3'ss, CDS start and end, miRNA seed matches, enhancers, CpG island, microsatellite, small RNA, poly A sites (3P-seq-tags), miRNA genes, and tRNA genes. - -Two output files are generated. One is the coverage/profile for each feature in the database that has a minimum overlap with the query set. The first two columns are feature name and the total number of overlapping intervals from the query. Column 3 to column 102 are coverage at each bin. The other file is an PDF file plotting both the heatmap for all features and the average coverage for each individual database feature. - - -**How it works** - -For each interval/peak in the query file, a window (default 10,000bp) is created around the center of the interval and is divided into 100 bins. For each database feature set (such as Pol II peaks), the tool counts how many intervals in the database feature file overlap with each bin. The count is then averaged over all query intervals that have at least one hit in at least one bin. Overall the plotted 'average coverage' represnts the fraction of query features (only those with hits, number shown in individual plot title) that has database feature interval covering that bin. The extreme is when the database feature is the same as the query, then every query interval is covered at the center, the average coverage of the center bin will be 1. - -The heatmap is scaled for each row before clustering. - - </help> -</tool> -
--- a/interval/align2multiple.xml Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,109 +0,0 @@ -<tool id="align2multiple" name="align-to-multiple"> - <description>features</description> - <command>cat $script_file | R --vanilla --slave > $logfile </command> - <inputs> - <param name="query" type="data" format="interval" label="Query intervals" help= "keep it small (less than 1,000,000 lines)"/> - <param name="label" type="text" value="" size="30" label="Data Label"/> - <param name="windowsize" size="10" type="integer" value="5000" label="radius of the window" help="will create new intervals of w bp flanking the original center. set to 0 will not change input interval size)"/> - <param name="nbins" size="10" type="integer" value="20" label="Number of bins dividing the window"/> - <param name="sort" label="Sort intervals" help="Sort by the center of the first input, then the second input, then third..." type="boolean" truevalue="sort" falsevalue="none" checked="True"/> - <repeat name="series" title="input file"> - <param name="label" type="text" value="" size="30" label="Data Label"/> - <param name="input" type="data" format="interval" label="Dataset"/> - </repeat> - </inputs> - - <configfiles> - <configfile name="script_file"> - ## Setup R error handling to go to stderr - cat('\n[',date(),'] Start running job\n') - options(warn=-1) - windowsize = as.integer("$windowsize") - labels = '$label' - ## align query to itself - cmd = 'python /Users/xuebing/galaxy-dist/tools/mytools/alignr.py -a $query -b $query -o $label-$label --profile-only -q -w $windowsize -n $nbins' - cat('\n[',date(),'] ',cmd,'\n') - system(cmd) - ## align other sets to query - #for $i,$s in enumerate( $series ) - labels = c(labels,'$s.label.value') - cmd = 'python /Users/xuebing/galaxy-dist/tools/mytools/alignr.py -a $s.input.file_name -b $query -o $label-$s.label.value --profile-only -q -w $windowsize -n $nbins' - cat('\n[',date(),'] ',cmd,'\n') - system(cmd) - #end for - cat('\n[',date(),'] Read output\n') - ## read output of query2query - print(paste(labels[1],labels[1],sep='-')) - x = read.table(paste(labels[1],labels[1],sep='-')) - ids = as.character(x[,1]) - nfeat = nrow(x) - x = as.matrix(x[,3:ncol(x)]) - nbin = ncol(x) - - ## a table mapping id to position - ind = list() - for (i in 1:nfeat){ - ind[[ids[i]]] = i - } - ## read other output files - for (i in 2:length(labels)){ - print(paste(labels[1],labels[i],sep='-')) - x0 = read.table(paste(labels[1],labels[i],sep='-')) - ids0 = as.character(x0[,1]) - x0 = as.matrix(x0[,3:ncol(x0)]) - x1 = matrix(0,nfeat,nbin) - for (j in 1:nrow(x0)){ - #cat(j,'\t',ids0[j],'\t',ind[[ids0[j]]],'\n') - x1[ind[[ids0[j]]],] = x0[j,] - } - x = cbind(x,x1) - } - ## reorder - if ("${sort}" == "sort"){ - cat('\n[',date(),'] Sort intervals\n') - for (i in rev(2:length(labels))){ - x = x[order(x[,i*nbin-nbin/2]>0),] - } - } - png("${out_file1}") - ##par(mfrow=c(2,length(labels)),mar=c(1,1,4,1)) - layout(matrix(seq(2*length(labels)),nrow=2,byrow=T),heights=c(1,5)) - cat('\n[',date(),'] Plot summary\n') - par(mar=c(0,0,4,0)+0.1) - for (i in 1:length(labels)){ - plot(colSums(x[,((i-1)*nbin+1):(i*nbin)]),type='l',axes=F,main=labels[i]) - } - cat('\n[',date(),'] Plot heatmap\n') - par(mar=c(0,0,0,0)+0.1) - for (i in 1:length(labels)){ - image(-t(log2(1+x[,((i-1)*nbin+1):(i*nbin)])),axes=F) - } - dev.off() - cat('\n[',date(),'] Finished\n') - - </configfile> - </configfiles> - - <outputs> - <data format="txt" name="logfile" label="${tool.name} on ${on_string}: (log)" /> - <data format="png" name="out_file1" label="${tool.name} on ${on_string}: (plot)" /> - </outputs> - -<help> -.. class:: infomark - -This tool allows you to check the co-localization pattern of multiple interval sets. All interval sets are aligned to the center of the intervals in the query interval set. - -Each row represents a window of certain size around the center of one interval in the query set, such as ChIP peaks. Each heatmap shows the position of other features in the SAME window (the same rows in each heatmap represent the same interval/genomic position). - - -The example below shows that of all Fox2 peaks, half of them are within 1kb of TSS. Of the half outside TSS, about one half has H3K4me1, two thirds of which are further depleted of H3K4me3. - ------ - -**Example** - -.. image:: ./static/images/align2multiple.png - -</help> -</tool>
--- a/interval/alignr.py Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,353 +0,0 @@ -''' -the scripts takes two files as input, and compute the coverage of -features in input 1 across features in input 2. Features in input 2 are -divided into bins and coverage is computed for each bin. - -please check the help information by typing: - - python align.py -h - - -requirement: - please install the following tools first: - bedtools: for read/region overlapping, http://code.google.com/p/bedtools/ - -''' - -import os,sys,os.path -from optparse import OptionParser - -def lineCount(filename): - with open(filename) as f: - for i, l in enumerate(f): - pass - return i + 1 - -def combineFilename(f1,f2): - ''' - fuse two file names into one - ''' - return f1.split('/')[-1]+'-'+f2.split('/')[-1] - -def checkFormat(filename1,filename2,input1format): - ''' - check the format of input files - ''' - - # file1 - # read the first line, see how many filds - ncol1 = 6 - if input1format == "BED": - f = open(filename1) - line = f.readline().strip().split('\t') - ncol1 = len(line) - if ncol1 < 3: - print "ERROR: "+filename1+" has only "+str(ncol1)+" columns (>=3 required). Make sure it has NO header line and is TAB-delimited." - sys.exit(1) - f.close() - - # file2 - f = open(filename2) - line = f.readline().strip().split('\t') - ncol2 = len(line) - if ncol2 < 3: - print "ERROR: "+filename2+" has only "+str(ncol2)+" columns (>=3 required). Make sure it has NO header line and is TAB-delimited." - sys.exit(1) - - return ncol1,ncol2 - - -def makeBed(filename,ncol): - ''' - add up to 6 column - ''' - f = open(filename) - outfile = filename+'.tmp.bed' - outf = open(outfile,'w') - if ncol == 3: - for line in f: - outf.write(line.strip()+'\t.\t0\t+\n') - elif ncol == 4: - for line in f: - outf.write(line.strip()+'\t0\t+\n') - if ncol == 5: - for line in f: - outf.write(line.strip()+'\t+\n') - f.close() - outf.close() - return outfile - -def makeWindow(filename,window): - - outfile = filename+'-window='+str(window)+'.tmp.bed' - if not os.path.exists(outfile): - f=open(filename) - out = open(outfile,'w') - lines = f.readlines() - if 'track' in lines[0]: - del lines[0] - for line in lines: - flds = line.strip().split('\t') - - #new position - center = (int(flds[1]) + int(flds[2]))/2 - start = center - window - end = center + window - if start >= 0: - flds[1] = str(start) - flds[2] = str(end) - out.write('\t'.join(flds)+'\n') - f.close() - out.close() - return outfile - -def groupReadsMapped2aRegion(filename,ncol): - ''' - read output from intersectBED - find all reads mapped to each region - ''' - try: - f=open(filename) - #If filename cannot be opened, print an error message and exit - except IOError: - print "could not open",filename,"Are you sure this file exists?" - sys.exit(1) - lines = f.readlines() - - allReadsStart = {} - allReadsEnd = {} - regionStrand = {} - regionStart = {} - regionEnd = {} - - for line in lines: - flds = line.strip().split('\t') - key = '_'.join(flds[ncol:(ncol+4)]) - if not allReadsStart.has_key(key): - allReadsStart[key] = list() - allReadsEnd[key] = list() - #print flds[ncol+0],flds[ncol+1],flds[ncol+2] - allReadsStart[key].append(int(flds[1])) - allReadsEnd[key].append(int(flds[2])) - regionStrand[key] = flds[ncol+5] - regionStart[key] = int(flds[ncol+1]) - regionEnd[key] = int(flds[ncol+2]) - return (allReadsStart,allReadsEnd,regionStrand,regionStart,regionEnd) - - -def createRegionProfile(allReadsStart,allReadsEnd,regionStrand,regionStart,regionEnd,nbins): - ''' - each region is divided into nbins - compute the number of reads covering each bin for each region - ''' - RegionProfile = {} - nRead = {} # num of all reads in the region - for region in allReadsStart.keys(): - RegionProfile[region] = [0]*nbins - nRead[region] = len(allReadsStart[region]) - #print region,nRead[region],allReadsStart[region] - for i in range(nRead[region]): - RegionProfile[region] = updateRegionCount(RegionProfile[region],allReadsStart[region][i],allReadsEnd[region][i],regionStart[region],regionEnd[region],regionStrand[region],nbins) - return RegionProfile,nRead - -def updateRegionCount(RegionCount,readStart,readEnd,regionStart,regionEnd,strand,nbins): - ''' - each region is divided into nbins, - add 1 to each bin covered by the read - ''' - L = regionEnd-regionStart - start = int(nbins*(readStart-regionStart)/L) - end = int(nbins*(readEnd-regionStart)/L) - if start < 0: - start = 0 - if end > nbins: - end = nbins - if strand == '-': - for i in range(start,end): - RegionCount[nbins-1-i] = RegionCount[nbins-1-i] + 1 - else: # if the 6th column of the input is not strand, will treat as + strand by default - for i in range(start,end): - RegionCount[i] = RegionCount[i] + 1 - return RegionCount - -def saveProfile(filename,Profile,nRegion): - out = open(filename,'w') - for regionType in Profile.keys(): - #print Profile[regionType] - out.write(regionType+'\t'+str(nRegion[regionType])+'\t'+'\t'.join(map(str,Profile[regionType]))+'\n') - -def saveSummary(filename,Profile,nbin): - out = open(filename+'.summary','w') - - nfeat = len(Profile) - summaryprofile = [0]*nbin - for regionType in Profile.keys(): - for i in range(nbin): - summaryprofile[i] += Profile[regionType][i] - out.write(filename+'\t'+str(nfeat)+'\t'+'\t'.join(map(str,summaryprofile))+'\n') - out.close() - # calculate standard error - out = open(filename+'.standarderror','w') - sd = [0.0]*nbin - u = [0.0]*nbin - for i in range(nbin): - u[i] = float(summaryprofile[i])/nfeat - for regionType in Profile.keys(): - sd[i] = sd[i] + (Profile[regionType][i] - u[i])**2 - sd[i] = sd[i]**0.5 / nfeat - out.write(filename+'\t'+str(nfeat)+'\t'+'\t'.join(map(str,sd))+'\n') - out.close() - -def main(): - usage = "usage: %prog [options] -a inputA -b inputB" - parser = OptionParser(usage) - parser.add_option("-a", dest="inputA", - help="(required) input file A, interval (first 3 columns are chrN, start and end) or BAM format. The script computes the depth of coverage of features in file A across the features in file B" ) - parser.add_option("-b",dest="inputB", - help="(required) input file B, interval file" ) - parser.add_option("-f",dest="aformat",default="BED", - help="Format of input file A. Can be BED (default) or BAM") - parser.add_option("-w",type='int',dest="window", - help="Generate new inputB by making a window of 2 x WINDOW bp (in total) flanking the center of each input feature" ) - parser.add_option("-n", type="int", dest="nbins",default=100, - help="number of bins. Features in B are binned, and the coverage is computed for each bin. Default is 100") - parser.add_option("-s",action="store_true", dest="strandness", - help="enforce strandness: require overlapping on the same strand. Default is off") - parser.add_option("-p",action="store_true", dest="plot",default=False, - help="load existed intersectBed outputfile") - parser.add_option("-q", action="store_true", dest="quiet",default=False, - help="suppress output on screen") - parser.add_option("-o", dest="output_data", - help="(optional) output coverage file (txt) name." ) - parser.add_option("-v", dest="output_plot", - help="(optional) output plot (pdf) file name." ) - parser.add_option("-l", dest="plot_title", default="", - help="(optional) output title of the plot." ) - parser.add_option("--ylim", dest="ylim", default="min,max", - help="(optional) ylim of the plot" ) - parser.add_option("--summary-only", action="store_true", dest="summary_only",default=False, - help="save profile summary only (no data for individual features)") - parser.add_option("--compute-se", action="store_true", dest="compute_se",default=False, - help="compute and plot standard deviation for each bin. used when --summary-only is on") - parser.add_option("--profile-only", action="store_true", dest="profile_only",default=False, - help="save profile only (no plot)") - parser.add_option("--span", type="float", dest="span",default=0.1, - help="loess span smooth parameter, 0.1 ~ 1") - - (options, args) = parser.parse_args() - - if options.inputA == None or options.inputB == None: - parser.error("Please specify two input files!!") - - if not options.quiet: - print "checking input file format..." - - ncol,ncol2 = checkFormat(options.inputA ,options.inputB,options.aformat) - - if ncol2 < 6: - options.inputB = makeBed(options.inputB,ncol2) - if not options.quiet: - print "fill up 6 columns" - - if options.window > 0: - if not options.quiet: - print "making windows from "+options.inputB+"..." - options.inputB = makeWindow(options.inputB,options.window) - - output = combineFilename(str(options.inputA),str(options.inputB)) - - if not options.plot: - if options.aformat == "BAM": - cmd = "intersectBed -abam "+str(options.inputA)+" -b "+str(options.inputB) + ' -bed -split ' - else: - cmd = "intersectBed -a "+str(options.inputA)+" -b "+str(options.inputB) - if options.strandness: - cmd = cmd + ' -s' - cmd = cmd +" -wo > "+ output+'-intersect.tmp.bed' - if not options.quiet: - print "search for overlappings: "+cmd - status = os.system(cmd) - if status != 0: - sys.exit(1) - - - if not options.quiet: - print 'group reads mapped to the same region...' - - allReadsStart,allReadsEnd,regionStrand,regionStart,regionEnd = groupReadsMapped2aRegion(output+'-intersect.tmp.bed',ncol) - - if len(allReadsStart) == 0: - if not options.quiet: - print 'no overlap found!!' - os.system('rm *tmp.*') - sys.exit(1) - - if not options.quiet: - print 'count number of reads mapped to each bin...' - - RegionProfile,nRead = createRegionProfile(allReadsStart,allReadsEnd,regionStrand,regionStart,regionEnd,options.nbins) - - if options.output_data == None: - options.output_data = output+'.txt' - - if options.summary_only: - saveSummary(options.output_data,RegionProfile,options.nbins) - - else: - saveProfile(options.output_data,RegionProfile,nRead) - - if not options.quiet: - print 'results saved to: '+ options.output_data - - if not (options.summary_only or options.profile_only ): - # visualize - - if options.window < 1: - xlab = 'relative position (bins)' - else: - xlab = 'relative position (bp)' - - if options.output_plot == None: - options.output_plot = output+'.pdf' - - title = options.plot_title+'\n n = '+str(len(RegionProfile)) - - rscript = open("tmp.r","w") - rscript.write("x <- read.table('"+options.output_data+"')\n") - rscript.write("pdf('"+options.output_plot+"')\n") - rscript.write("avg <- colSums(x[,3:ncol(x)])/nrow(x)\n") - rscript.write("err <- sd(x[,3:ncol(x)])/sqrt(nrow(x))\n") - - if options.window == 0: - rscript.write("xticks <- seq("+str(options.nbins)+")\n") - else: - rscript.write("xticks <- seq("+str(-options.window)+","+str(options.window)+",length.out="+str(options.nbins)+")\n") - - if options.ylim != 'min,max': - rscript.write("ylim=c("+options.ylim+")\n") - else: - rscript.write("ylim=c(min(avg-err),max(avg+err))\n") - rscript.write("par(cex=1.5)\n") - #smooth - if options.span >= 0.1: - rscript.write("avg = loess(avg~xticks,span="+str(options.span)+")$fitted\n") - rscript.write("err = loess(err~xticks,span="+str(options.span)+")$fitted\n") - rscript.write("plot(xticks,avg,ylab='average coverage',main='"+title+"',xlab='"+xlab+"',type='l',lwd=0,ylim=ylim)\n") - rscript.write("polygon(c(xticks,rev(xticks)),c(avg+err,rev(avg-err)),col='slateblue1',border=NA)\n") - rscript.write("lines(xticks,avg,type='l',lwd=1)\n") - #rscript.write("xticks <- barplot(avg,names.arg=seq("+str(options.nbins)+"),ylab='average coverage',main='"+title+"',xlab='"+xlab+"',,ylim=c(min(avg-err),max(avg+err)))\n") - #rscript.write("arrows(xticks,avg+err, xticks, avg-err, angle=90, code=3, length=0.0,col='green')\n") - #rscript.write("lines(xticks,avg,lwd=2)\n") - #rscript.write("lines(xticks,avg-err,col='green')\n") - #rscript.write("lines(xticks,avg+err,col='green')\n") - rscript.write("dev.off()\n") - rscript.close() - - os.system("R --vanilla < tmp.r") - - # remove intermediate output - os.system('rm *tmp.*') - - -if __name__ == "__main__": - main()
--- a/interval/alignr.xml Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,142 +0,0 @@ -<tool id="alignr" name="align"> - <description>two interval sets</description> - <command interpreter="python"> alignr.py -a $inputa -w $windowsize -n $nbins -o $output_data -v $output_plot $stranded -q -l $outputlabel --ylim=$ylim --span $span - #if $inputb_source_type.inputb_select == "user": - -b "$inputb" - #else: - -b "${inputb_source_type.selectedb.fields.value}" - #end if - #if $inputa_format.inputa_select == "BAM": - -f BAM - #end if - </command> - <inputs> - <conditional name="inputa_format"> - <param name="inputa_select" type="select" label="Select your first input format" > - <option value="BED" selected="true">BED-like (chrNum start end ...) </option> - <option value="BAM"> BAM</option> - </param> - <when value="BED"> - <param name="inputa" type="data" format="interval" label="Input file for the first interval set (-a)"/> - </when> - <when value="BAM"> - <param name="inputa" type="data" format="bam" label="Input file for the first interval set (-a)"/> - </when> - </conditional> - <conditional name="inputb_source_type"> - <param name="inputb_select" type="select" label="Input source for the second interval set"> - <option value="mm9ucsc" selected="true">mm9 ucsc knownGene annotations</option> - <option value="mm9refseq">mm9 refseq gene annotations</option> - <option value="mm9ensembl">mm9 ensembl gene annotations</option> - <option value="hg18ucsc" >hg18 ucsc knownGene annotations</option> - <option value="hg18refseq">hg18 refseq gene annotations</option> - <option value="hg18ensembl">hg18 ensembl gene annotations</option> - <option value="user">Dataset in Your History</option> - </param> - <when value="user"> - <param name="inputb" type="data" format="interval" label="Input file for the second interval set (-b)" /> - </when> - <when value="mm9ucsc"> - <param name="selectedb" type="select" label="Input for the second interval set (-b)" > - <options from_file="aligndb-mm9-knownGene.loc"> - <column name="name" index="0"/> - <column name="value" index="1"/> - </options> - </param> - </when> - <when value="mm9refseq"> - <param name="selectedb" type="select" label="Input for the second interval set (-b)" > - <options from_file="aligndb-mm9-refGene.loc"> - <column name="name" index="0"/> - <column name="value" index="1"/> - </options> - </param> - </when> - <when value="mm9ensembl"> - <param name="selectedb" type="select" label="Input for the second interval set (-b)" > - <options from_file="aligndb-mm9-ensGene.loc"> - <column name="name" index="0"/> - <column name="value" index="1"/> - </options> - </param> - </when> - <when value="hg18ucsc"> - <param name="selectedb" type="select" label="Input for the second interval set (-b)" > - <options from_file="aligndb-hg18-knownGene.loc"> - <column name="name" index="0"/> - <column name="value" index="1"/> - </options> - </param> - </when> - <when value="hg18refseq"> - <param name="selectedb" type="select" label="Input for the second interval set (-b)" > - <options from_file="aligndb-hg18-refGene.loc"> - <column name="name" index="0"/> - <column name="value" index="1"/> - </options> - </param> - </when> - <when value="hg18ensembl"> - <param name="selectedb" type="select" label="Input for the second interval set (-b)" > - <options from_file="aligndb-hg18-ensGene.loc"> - <column name="name" index="0"/> - <column name="value" index="1"/> - </options> - </param> - </when> - - </conditional> - <param name="windowsize" size="10" type="integer" value="0" label="Change input 2 interval size (-w)" help="will create new intervals of w bp flanking the original center. set to 0 will not change input interval size)"/> - <param name="nbins" size="10" type="integer" value="100" label="Number of bins dividing intervals in input 2(-n)"/> - <param name="span" size="10" type="float" value="0.1" label="loess span: smoothing parameter" help="value less then 0.1 disables smoothing"/> - <param name="stranded" label="Check if require overlap on the same strand (-s)" type="boolean" truevalue="-s" falsevalue="" checked="False"/> - <param name="outputlabel" size="80" type="text" label="Output label" value="test"/> - <param name="ylim" size="10" type="text" label="set ylim of the plot" value="min,max" help="e.g. 0,1 (default is the min and max of the signal)"/> - -</inputs> - <outputs> - <data format="tabular" name="output_data" label="${outputlabel} (data)"/> - <data format="pdf" name="output_plot" label="${outputlabel} (plot)"/> - </outputs> - <help> - -**What it does** - -This tool aligns two sets of intervals, finds overlaps, calculates and plots the coverage of the first set across the second set. Applications include: - -- check read distribution around TSS/poly A site/splice site/motif site/miRNA target site -- check relative position/overlap of two lists of ChIP-seq peaks - -Two output files are generated. One is the coverage/profile for each interval in input 2. The first two columns are interval ID and the total number of overlapping intervals from input 1. Column 3 to column nbins+2 are coverage at each bin. The other file is an PDF file plotting the average coverage of each bin. To modify the visualization, please downlaod the coverage file and make your own plots. - ------ - -**Annotated features** - -Currently supports mouse genome build mm9 and human hg18. Each interval spans 1000bp upstream and 1000bp downstream of a feature such as TSS. Features with overlapping exons in the intronic/intergenic part of the 2000bp interval are removed. - ------ - -**Usage** - - -h, --help show this help message and exit - -a INPUTA (required) input file A, BED-like (first 3 columns: chr, start, end) or BAM format. The - script computes the depth of coverage of features in file - A across the features in file B - -b INPUTB (required) input file B, BED format or MACS peak file. - Requires an unique name for each line in column 4 - -m inputB is a MACS peak file. - -f AFORMAT Format of input file A. Can be BED (default) or BAM - -w WINDOW Generate new inputB by making a window of 2 x WINDOW bp - (in total) flanking the center of each input feature - -n NBINS number of bins. Features in B are binned, and the coverage - is computed for each bin. Default is 100 - -s enforce strandness: require overlapping on the same - strand. Default is off - -p load existed intersectBed outputfile - -q suppress output on screen - -o OUTPUTPROFILE (optional) output profile name. - -v PLOTFILE (optional) plot file name - </help> -</tool> -
--- a/interval/alignvis.py Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,76 +0,0 @@ -import sys,os - -infile = sys.argv[1] -outfile = sys.argv[2] -uselog = sys.argv[3] -subset = sys.argv[4] -reorder = sys.argv[5] -color = sys.argv[6] -scale = sys.argv[7] # rescale each row -rscript = open('tmp.r','w') - -rscript.write("x <- read.table('"+infile+"')\n") -rscript.write("nfeat <- nrow(x) \n") -rscript.write("nbin <- ncol(x) - 2\n") -rscript.write("totalcov <- x[,2]\n") -rscript.write("x <- x[,3:ncol(x)]\n") - -if subset =='subset': - rscript.write("if (nfeat*nbin > 100000) {\n") - rscript.write(" nfeat2 <- as.integer(100000/nbin)\n") - rscript.write(" subind <- sample(seq(nfeat),nfeat2)\n") - rscript.write(" x <- x[subind,]\n") - rscript.write(" totalcov <- totalcov[subind]\n") - rscript.write("}\n") - -rscript.write("pdf('"+outfile+"')\n") - -if uselog == 'uselog': - rscript.write("x <- -(log(1+as.matrix(x,nc=ncol(x)-2)))\n") -else: - rscript.write("x <- -as.matrix(x,nc=ncol(x)-2)\n") -if scale == 'scale': - rscript.write("x <- scale(x)\n") -if reorder == 'average': - rscript.write("hc <- hclust(dist(x),method= 'average')\n") - rscript.write("x <- x[hc$order,]\n") -elif reorder == 'centroid': - rscript.write("hc <- hclust(dist(x),method= 'centroid')\n") - rscript.write("x <- x[hc$order,]\n") -elif reorder == 'complete': - rscript.write("hc <- hclust(dist(x),method= 'complete')\n") - rscript.write("x <- x[hc$order,]\n") -elif reorder == 'single': - rscript.write("hc <- hclust(dist(x),method= 'single')\n") - rscript.write("x <- x[hc$order,]\n") -elif reorder == 'median': - rscript.write("hc <- hclust(dist(x),method= 'median')\n") - rscript.write("x <- x[hc$order,]\n") -elif reorder == 'sort_by_total': - rscript.write("srt <- sort(totalcov,index.return=T)\n") - rscript.write("x <- x[srt$ix,]\n") -elif reorder == 'sort_by_center': - rscript.write("srt <- sort(x[,as.integer(nbin/2)],index.return=T)\n") - rscript.write("x <- x[srt$ix,]\n") -if color == 'heat': - rscript.write("colormap = heat.colors(1000)\n") -elif color == 'topo': - rscript.write("colormap = topo.colors(1000)\n") -elif color == 'rainbow': - rscript.write("colormap = rainbow(1000)\n") -elif color == 'terrain': - rscript.write("colormap = terrain.colors(1000)\n") -else: - rscript.write("colormap = gray.colors(1000)\n") - -#rscript.write("qt <- quantile(as.vector(x),probs=c(0.1,0.9))\n") -#rscript.write("breaks <- c(min(as.vector(x)),seq(qt[1],qt[2],length.out=99),max(as.vector(x)))\n") -#rscript.write("image(t(x),col=colormap,breaks=breaks,axes=F)\n") -rscript.write("image(t(x),col=colormap,axes=F)\n") -rscript.write("dev.off()\n") - -rscript.close() - -os.system("R --slave < tmp.r") -os.system("rm tmp.r") -
--- a/interval/alignvis.r Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,8 +0,0 @@ -args <- commandArgs(TRUE) -x <- read.table(args[1]) -pdf(args[2]) -#visualize the profile with heatmap -srt <- sort(x[,2],index.return=T) # sort by total number of reads -image(-t(log(as.matrix(x[srt$ix[1:nrow(x)],3:ncol(x)],nc=ncol(x)-2))),col=gray.colors(100)) -dev.off() -
--- a/interval/alignvis.xml Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,42 +0,0 @@ -<tool id="alignvis" name="heatmap"> - <description>of align output</description> - <command interpreter="python"> alignvis.py $input $output $uselog $subset $reorder $color $scale </command> - <inputs> - <param name="input" format="tabular" type="data" label="Original file"/> - <param name="uselog" label="log transform the data" type="boolean" truevalue="uselog" falsevalue="none" checked="True"/> - <param name="subset" label="sample a subset if the data is too large" type="boolean" truevalue="subset" falsevalue="none" checked="True"/> - <param name="scale" label="normalize by row/feature" type="boolean" truevalue="scale" falsevalue="none" checked="False"/> - <param name="reorder" type="select" label="reorder features (rows)"> - <option value="none" selected="true">None</option> - <option value="sort_by_sum">Sort row by sum</option> - <option value="sort_by_center">Sort row by center </option> - <option value="average">Cluster rows (average)</option> - <option value="median">Cluster rows (median) </option> - <option value="centroid">Cluster rows (centroid)</option> - <option value="complete">Cluster rows (complete)</option> - <option value="single">Cluster rows (single)</option> - </param> - - <param name="color" type="select" label="color scheme"> - <option value="heat" selected="true">heat</option> - <option value="gray">gray</option> - <option value="rainbow">rainbow</option> - <option value="topo">topo</option> - <option value="terrain">terrain</option> - </param> - </inputs> - <outputs> - <data format="pdf" name="output" /> - </outputs> - <help> - -**What it does** - -This tool generates a heatmap for output from 'align' tool. Each row is the color-coded coverage of a feature, and the features are sorted by the total coverage in the interval. - -**Example** - -.. image:: ./static/operation_icons/heatmap.png - - </help> -</tool>
--- a/interval/bedClean.py Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,43 +0,0 @@ -import sys - -def readChrSize(filename): - f = open(filename) - chrSize = {} - for line in f: - chrom,size = line.strip().split() - chrSize[chrom]=int(size) - f.close() - return chrSize - -def cleanFile(filename,chrSize,outfile): - f = open(filename) - out = open(outfile,'w') - i = 0 - for line in f: - i = i + 1 - flds = line.strip().split('\t') - if len(flds) < 3: - print 'line',i,'incomplete line:\n',line - elif chrSize.has_key(flds[0]): - if int(flds[1]) > int(flds[2]): - tmp = flds[1] - flds[1] = flds[2] - flds[2] = tmp - if int( flds[1]) < 0 or int(flds[2]) <0: - print 'line',i,'negative coordinates:\n',line - elif int(flds[2]) > chrSize[flds[0]]: - print 'line',i,'end larger than chr size:\n',line - else: - if flds[5] == '*': - flds[5] = '+' - print 'line',i,' strand * changed to +\n', line - out.write('\t'.join(flds)+'\n') - else: - print 'line',i,'chromosome',flds[0],'not found!\n',line - f.close() - out.close() - -if len(sys.argv) < 4: - print "python bedClean.py in.bed chrsizefile out.bed" - exit() -cleanFile(sys.argv[1],readChrSize(sys.argv[2]),sys.argv[3])
--- a/interval/bed_to_bam.xml Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,19 +0,0 @@ -<tool id="bedToBam" name="bedToBam"> - <description>convert BED or GFF or VCF to BAM</description> - <command>bedToBam -i $input -g $genome $bed12 $mapq $ubam > $outfile </command> - <inputs> - <param name="input" format="bed,gff,vcf" type="data" label="Input file (BED,GFF,VCF)" help="BED files must be at least BED4 to be amenable to BAM (needs name field)"/> - <param name="genome" type="select" label="Select genome"> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/chrsize/mouse.mm9.genome" selected="true">mm9</option> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/chrsize/mouse.mm8.genome">mm8</option> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/chrsize/human.hg18.genome">hg18</option> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/chrsize/human.hg19.genome">hg19</option> - </param> - <param name="mapq" size="10" type="integer" value="255" label="Set the mappinq quality for the BAM records"/> - <param name="bed12" label="The BED file is in BED12 format" help="The BAM CIGAR string will reflect BED blocks" type="boolean" truevalue="-bed12" falsevalue="" checked="False"/> - <param name="ubam" label="Write uncompressed BAM output" help="Default is to write compressed BAM" type="boolean" truevalue="-ubam" falsevalue="" checked="False"/> - </inputs> - <outputs> - <data format="bam" name="outfile" /> - </outputs> -</tool>
--- a/interval/bedclean.xml Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,33 +0,0 @@ -<tool id="bedclean" name="clean interval"> - <description>remove off-chromosome lines</description> - <command interpreter="python">bedclean.py $input $genome $output > $log </command> - <inputs> - <param name="input" type="data" format="interval" label="Original interval file"/> - <param name="genome" type="select" label="Select genome"> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/chrsize/mouse.mm9.genome" selected="true">mm9</option> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/chrsize/mouse.mm8.genome">mm8</option> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/chrsize/human.hg18.genome">hg18</option> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/chrsize/human.hg19.genome">hg19</option> - </param> - </inputs> - <outputs> - <data format="input" name="output" label="${tool.name} on ${on_string} (interval)"/> - <data format="txt" name="log" label="${tool.name} on ${on_string} (log)"/> - </outputs> - <help> - -**Description** - -remove lines that are - -1. comment or track name lines - -2. on chr*_random - -3. or have negative coordinates - -4. or the end is larger than chromosome size - - - </help> -</tool>
--- a/interval/bedsort.xml Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,23 +0,0 @@ -<tool id="bedsort" name="sort"> - <description>a interval file by chr and start</description> - <command> head -n $skip $input > $output - && tail -n+`expr $skip + 1` $input | sort -k1,1 -k2,2g >> $output - </command> - <inputs> - <param name="input" type="data" format="bed" label="Input interval file"/> - <param name="skip" type="integer" value="0" label="top lines to skip" help="output directly, not sorted"/> - </inputs> - <outputs> - <data format="bed" name="output" /> - </outputs> - <help> - -**Description** - -Unix command used:: - - head -n $skip $input > $output - tail -n+`expr $skip + 1` $input | sort -k1,1 -k2,2g >> $output - - </help> -</tool>
--- a/interval/bigWigAverageOverBed.xml Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,12 +0,0 @@ -<tool id="bigWigAverageOverBed" name="bigWigAverageOverBed"> - <description>average interval coverage</description> - <command>bigWigAverageOverBed $bw $bed $outtab -bedOut=$outbed 2> err </command> - <inputs> - <param name="bw" format="bigwig" type="data" label="BigWig file"/> - <param name="bed" format="bed" type="data" label="Bed file"/> - </inputs> - <outputs> - <data format="tabular" name="outtab" label="${tool.name} on ${on_string} (tab)"/> - <data format="bed" name="outbed" label="${tool.name} on ${on_string} (bed)"/> - </outputs> -</tool>
--- a/interval/binaverage.xml Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,74 +0,0 @@ -<tool id="binaverage" name="bin and average"> - <description>of numeric columns</description> - <command>cat $script_file | R --vanilla --slave > $out_log </command> - <inputs> - <param name="input" type="data" format="tabular" label="Data file"/> - <param name="data_avg" type="integer" value="1" label="Column number of the data to average"/> - <param name="label_avg" type="text" value="label-avg" size="30" label="data label"/> - <param name="log_avg" label="log2 transform the data" type="boolean" truevalue="logavg" falsevalue="none" checked="False"/> - <param name="data_bin" type="integer" value="2" label="Column number of the data used to make bins"/> - <param name="label_bin" type="text" value="label-bin" size="30" label="data label"/> - <param name="log_bin" label="log2 transform the data" type="boolean" truevalue="logbin" falsevalue="none" checked="False"/> - <param name="nbin" type="integer" value="3" label="number of bins"/> - <param name="bintype" type="select" label="Bin by rank or by value" > - <option value="rank" selected="true">by rank: bins have the same number of data points</option> - <option value="value">by value: bins may have different number of data points</option> - </param> - <param name="legendloc" type="select" label="legend location on CDF plot" > - <option value="bottomright" selected="true">bottomright</option> - <option value="bottomleft">bottomleft</option> - <option value="bottom">bottom</option> - <option value="left">left</option> - <option value="topleft">topleft</option> - <option value="top">top</option> - <option value="topright">topright</option> - <option value="right">right</option> - <option value="center">center</option> - </param> - - <param name="title" type="text" value="bin-average" size="50" label="title of this analysis"/> - - </inputs> - - <configfiles> - <configfile name="script_file"> - ## Setup R error handling to go to stderr - options(warn=-1) - source("/Users/xuebing/galaxy-dist/tools/mytools/cdf.r") - x = read.table("${input}",sep='\t') - x = x[,c($data_bin,$data_avg)] - label_avg = "${label_avg}" - label_bin = "${label_bin}" - if ("${log_bin}" == "logbin"){ - x[,1] = log2(1+x[,1]) - label_bin = paste('log2',label_bin) - } - if ("${log_avg}" == "logavg"){ - x[,2] = log2(1+x[,2]) - label_avg = paste('log2',label_avg) - } - res = binaverage(x,$nbin,"${bintype}") - attach(res) - for (i in 1:${nbin}){ - print(paste(label_bin,labels[i],sep=':')) - print(summary(binned[[i]])) - } - pdf("${out_file}") - mycdf(binned,"${title}",labels,"$legendloc",label_avg,label_bin) - dev.off() - </configfile> - </configfiles> - - <outputs> - <data format="txt" name="out_log" label="${title}: (log)" /> - <data format="pdf" name="out_file" label="${title}: (plot)" /> - </outputs> - -<help> - -.. class:: infomark - -This tool generates barplot and CDF plot comparing data/rows in a numeric column that are binned by a second numeric column. The input should have at least two numeric columns. One of the column is used to group rows into bins, and then values in the other column are compared using barplot, CDF plot, and KS test. - -</help> -</tool>
--- a/interval/binnedAverage.py Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,77 +0,0 @@ -''' -get binned score of intervals,allow extension -''' - -import os,sys,numpy,random,string - -from resize import * - -from bx.bbi.bigwig_file import BigWigFile - -def binning(x,n): - # make n bin of x - y = numpy.zeros(n,dtype=float) - if len(x) == 0: - return y - step = float(len(x))/n - for k in range(n): - i = int(step*k) - j = int(step*(k+1)) + 1 - y[k] = x[i:j].mean() - #print i,j,k,y[k] - return y - -def getBinnedScore(bwfile,intvfile,outfile,outplot,nbin): - ''' - get binned average and std - ''' - fbw = open(bwfile) - bw = BigWigFile(file=fbw) - fin = open(intvfile) - out = open(outfile,'w') - zeros = '\t'.join(['0']*nbin) - for line in fin: - #chrom,start,end,name,score,strand - line = line.strip() - flds = line.split('\t') - #get the score at base resolution as an array - scores = bw.get_as_array(flds[0],int(flds[1]),int(flds[2])) - if scores == None: - print 'not found:\t',line - out.write(line+'\t'+zeros+'\n') - continue - # reverse if on minus strand - if flds[5] == '-': - scores = scores[::-1] - # no score = 0 - scores = numpy.nan_to_num(scores) - # bin the data - binned = binning(scores,nbin) - out.write(line+'\t'+'\t'.join(map(str,binned))+'\n') - fin.close() - out.close() - # plot - if nbin > 1: - tmp = "".join(random.sample(string.letters+string.digits, 8)) - rscript = open(tmp,"w") - rscript.write("options(warn=-1)\n") - rscript.write("x <- read.table('"+outfile+"',sep='\t')\n") - rscript.write("x <- x[,(ncol(x)+1-"+str(nbin)+"):ncol(x)]\n") - rscript.write("pdf('"+outplot+"')\n") - rscript.write("avg <- apply(x,2,mean)\n") - rscript.write("err <- apply(x,2,sd)/sqrt(nrow(x))\n") - rscript.write("print(avg)\n") - rscript.write("print(err)\n") - rscript.write("ylim=c(min(avg-err),max(avg+err))\n") - rscript.write("xticks <- seq(ncol(x))\n") - rscript.write("plot(xticks,avg,xlab='',ylab='average',type='l',lwd=0,ylim=ylim)\n") - rscript.write("polygon(c(xticks,rev(xticks)),c(avg+err,rev(avg-err)),col='lightgreen',border=NA)\n") - rscript.write("lines(xticks,avg,type='l',lwd=1)\n") - rscript.write("dev.off()\n") - rscript.close() - os.system("R --vanilla < "+tmp) - os.system("rm "+tmp) - -print sys.argv -prog,bwfile,intvfile,nbin,outfile,outplot = sys.argv -getBinnedScore(bwfile,intvfile,outfile,outplot,int(nbin))
--- a/interval/bwBinavg.xml Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,44 +0,0 @@ -<tool id="bwbinavg" name="bigwig summary"> - <description>for intervals</description> - <command interpreter="python">getGenomicScore.py $input $output $score_type $bwfile $nbin $strand $outplot $span</command> - <inputs> - <param name="input" format="interval" type="data" label="Interval file"/> - <param name="bwfile" format="bigwig" type="data" label="BigWig file"/> - <param name="score_type" type="select" label="Select score summary type" > - <option value="mean" selected="true">mean</option> - <option value="max">maximum</option> - <option value="min">minimum</option> - <option value="std">standard deviation</option> - <option value="coverage">coverage:fraction covered</option> - </param> - <param name="nbin" type="integer" value="1" label="number of bins"/> - <param name="strand" type="integer" value="0" label="Specify the strand column" help="leave 0 to ignore strand information. Only matters if using more than 1 bin"/> - <param name="span" size="10" type="float" value="0.1" label="loess span: smoothing parameter" help="value less then 0.1 disables smoothing"/> - </inputs> - <outputs> - <data format="pdf" name="outplot" label="${tool.name} on ${on_string}[plot]"/> - <data format="interval" name="output" label="${tool.name} on ${on_string}[data]"/> - </outputs> - <help> - -.. class:: infomark - -Each interval is binned and the average base-resolution score/coverage/density in the bigwig file is added as new columns appended at the end of the original file . - -**Example** - -If your original data has the following format: - -+-----+-----+---+------+ -|chrom|start|end|other2| -+-----+-----+---+------+ - -and you choose to divide each interval into 3 bins and return the mean scores of each bin, your output will look like this: - -+-----+-----+---+------+-----+-----+-----+ -|chrom|start|end|other2|mean1|mean2|mean3| -+-----+-----+---+------+-----+-----+-----+ - - -</help> -</tool>
--- a/interval/closestBed.xml Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,32 +0,0 @@ -<tool id="closestbed" name="closestBed"> - <description>find closest features</description> - <command>closestBed -a $inputa -b $inputb $strandness -d $no -t $tie> $output_data - </command> - <inputs> - <param name="inputa" type="data" format="interval,bam,bed,gff,vcf" label="Input A (-a)"/> - <param name="inputb" type="data" format="interval,bam,bed,gff,vcf" label="Input B (-b)"/> - <param name="strandness" type="select" label="Strand requirement" > - <option value="" selected="true"> none </option> - <option value="-s" > -s: closest feature on the same strand</option> - <option value="-S" > -S: closest feature on the opposite strand </option> - </param> - - <param name="no" label="Only look for non-overlaping features" type="boolean" truevalue="-no" falsevalue="" checked="False"/> - <param name="tie" type="select" label="Strand requirement" > - <option value="all" selected="true"> report all ties </option> - <option value="first" > report the first that occurred</option> - <option value="last" > report the last that occurred </option> - </param> - </inputs> - <outputs> - <data format="input" name="output_data"/> - </outputs> - <help> - -**What it does** - -This is a wrapper for closestBed. - - </help> -</tool> -
--- a/interval/collapseBed.py Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,58 +0,0 @@ -''' -collapse intervals -''' - -def collapseInterval_strand(filename): - uniqintv = {} - data = {} - f = open(filename) - header = f.readline() - if 'chr' in header: - flds = header.strip().split('\t') - key = '\t'.join([flds[0],flds[1],flds[2],flds[5]]) - uniqintv[key] = 1 - data[key] = flds - for line in f: - flds = line.strip().split('\t') - key = '\t'.join([flds[0],flds[1],flds[2],flds[5]]) - if uniqintv.has_key(key): - uniqintv[key] = uniqintv[key] + 1 - else: - uniqintv[key] = 1 - data[key] = flds - f.close() - for key in uniqintv.keys(): - print '\t'.join(data[key]+[str(uniqintv[key])]) - #flds = key.split('\t') - #print '\t'.join([flds[0],flds[1],flds[2],'.',str(uniqintv[key]),flds[3]]) - -def collapseInterval(filename): - uniqintv = {} - data = {} - f = open(filename) - header = f.readline() - if 'chr' in header: - flds = header.strip().split('\t') - key = '\t'.join([flds[0],flds[1],flds[2]]) - uniqintv[key] = 1 - data[key] = flds - for line in f: - flds = line.strip().split('\t') - key = '\t'.join([flds[0],flds[1],flds[2]]) - if uniqintv.has_key(key): - uniqintv[key] = uniqintv[key] + 1 - else: - uniqintv[key] = 1 - data[key] = flds - f.close() - for key in uniqintv.keys(): - print '\t'.join(data[key]+[str(uniqintv[key])]) - #flds = key.split('\t') - #print '\t'.join([flds[0],flds[1],flds[2],'.',str(uniqintv[key])]) - -import sys - -if sys.argv[2] == 'strand': - collapseInterval_strand(sys.argv[1]) -else: - collapseInterval(sys.argv[1])
--- a/interval/collapseBed.xml Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,19 +0,0 @@ -<tool id="collapseBed" name="collapse"> - <description>intervals</description> - <command interpreter="python">collapseBed2.py $input $strand $score > $outfile </command> - <inputs> - <param name="input" format="interval" type="data" label="Original file"/> - <param name="strand" size="10" type="integer" value="6" label="strand column" help="set 0 to ignore strand information" /> - <param name="score" size="10" type="integer" value="5" label="for duplicate lines, keep the one with max value in column" help="set 0 to ignore score information" /> - </inputs> - <outputs> - <data format="input" name="outfile" /> - </outputs> - <help> - -**What it does** - -This tool collapses genomic intervals that have the same position (and strandness if specified) and output a set of unique intervals. - - </help> -</tool>
--- a/interval/collapseBed2.py Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,36 +0,0 @@ -''' -collapse intervals -''' - -def collapseInterval_strand(filename,c_strand,c_score): - # keeping max column c - uniqintv = {} - data = {} - f = open(filename) - header = f.readline() - if 'chr' in header: - flds = header.strip().split('\t') - key = '\t'.join([flds[0],flds[1],flds[2],flds[c_strand]]) - uniqintv[key] = float(flds[c_score]) - data[key] = flds - for line in f: - flds = line.strip().split('\t') - key = '\t'.join([flds[0],flds[1],flds[2],flds[c_strand]]) - if not uniqintv.has_key(key): - uniqintv[key] = float(flds[c_score]) - data[key] = flds - elif uniqintv[key] < float(flds[c_score]): - uniqintv[key] = float(flds[c_score]) - data[key] = flds - - f.close() - for key in uniqintv.keys(): - print '\t'.join(data[key]) - -import sys - -if sys.argv[2] == '0':#ignore strand - sys.argv[2] = 1 -if sys.argv[3] == '0':# ignore score - sys.argv[3] = 2 -collapseInterval_strand(sys.argv[1],int(sys.argv[2])-1,int(sys.argv[3])-1)
--- a/interval/collapseTab.py Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,37 +0,0 @@ -''' -collapse tabular files, with key columns, and max columns -''' - -def collapseTab(filename,c_key,c_max): - # keeping rows with max value in column c_max - nCol = max(max(c_key),c_max) - c_max = c_max - 1 - for i in range(len(c_key)): - c_key[i] = c_key[i] - 1 - uniqintv = {} - data = {} - f = open(filename) - for line in f: - flds = line.strip().split('\t') - if len(flds) < nCol: - continue - key = '' - for i in c_key: - key = key + flds[i-1] # i is 1-based, python is 0-based - if not uniqintv.has_key(key): - uniqintv[key] = float(flds[c_max]) - data[key] = flds - elif uniqintv[key] < float(flds[c_max]): - uniqintv[key] = float(flds[c_max]) - data[key] = flds - - f.close() - for key in uniqintv.keys(): - print '\t'.join(data[key]) - -import sys - -# convert string to number list -c_key = map(int,sys.argv[2].split(',')) -c_max = int(sys.argv[3]) -collapseTab(sys.argv[1],c_key,c_max)
--- a/interval/collapseTab.xml Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,19 +0,0 @@ -<tool id="collapseTab" name="collapse tabular"> - <description>files</description> - <command interpreter="python">collapseTab.py $input $key $max > $outfile </command> - <inputs> - <param name="input" format="tabular" type="data" label="Original file"/> - <param name="key" size="10" type="text" value="1,2,3" label="key column(s)" help="columns to define unique rows" /> - <param name="max" size="10" type="text" value="5" label="for lines with identical key, keep the one with max value in this column" help="need to be numeric" /> - </inputs> - <outputs> - <data format="input" name="outfile" /> - </outputs> - <help> - -**What it does** - -Similar to 'Group' but returns the entire line. - - </help> -</tool>
--- a/interval/endbias.py Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,52 +0,0 @@ -''' -usage: - -python endbias.py utr5-coverage utr3-coverage outputfile -''' -import sys,math - -def getCoverage(filename): - f = open(filename) - coverage = {} - for line in f: - flds = line.strip().split('\t') - score = float(flds[4]) - name = (flds[0].split('utr'))[0].strip('_') - if coverage.has_key(name): - if score > coverage[name]: - coverage[name] = score - else: - coverage[name] = score - return coverage - -def endBias(filename,utr5,utr3): - out = open(filename,'w') - for txpt in utr5.keys(): - if utr3.has_key(txpt): - out.write('\t'.join([txpt,str(utr5[txpt]),str(utr3[txpt]),str(math.log((1+utr5[txpt])/(1+utr3[txpt]),2))])+'\n') - out.close() - - -utr5 = getCoverage(sys.argv[1]) -utr3 = getCoverage(sys.argv[2]) -endBias(sys.argv[3],utr5,utr3) - -''' - -utr5 = getCoverage('hmga2-utr5.coverage') -utr3 = getCoverage('hmga2-utr3.coverage') -logratio, cov5,cov3= endBias(utr5,utr3) -2**pylab.median(logratio.values()) - -log2utr5 = pylab.log2(pylab.array(cov5)+1) -log2utr3 = pylab.log2(pylab.array(cov3)+1) - -pylab.plot(log2utr5,log2utr3,'bo') - -pylab.show() - -utr5 = getCoverage('control-utr5.coverage') -utr3 = getCoverage('control-utr3.coverage') -logratio, cov5,cov3= endBias(utr5,utr3) -2**pylab.median(logratio.values()) -'''
--- a/interval/endbias.xml Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,11 +0,0 @@ -<tool id="endbias" name="bias"> - <description>of UTR coverage</description> - <command interpreter="python"> endbias.py $input1 $input2 $output </command> - <inputs> - <param name="input1" format="txt" type="data" label="5' UTR coverage" help="tabular output from bigWigAverageOverBed"/> - <param name="input2" format="txt" type="data" label="3' UTR coverage" help="tabular output from bigWigAverageOverBed"/> - </inputs> - <outputs> - <data format="tabular" name="output" /> - </outputs> -</tool>
--- a/interval/genomeView.xml Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,108 +0,0 @@ -<tool id="genomeview" name="whole genome"> - <description>plot and correlation</description> - <command>cat $script_file | R --vanilla --slave 2> err.log </command> - <inputs> - <param name="genome" type="select" label="Select genome"> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/chrsize/mouse.mm9.genome" selected="true">mm9</option> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/chrsize/mouse.mm8.genome">mm8</option> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/chrsize/human.hg18.genome">hg18</option> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/chrsize/human.hg19.genome">hg19</option> - </param> - <param name="resolution" type="integer" label="resolution" value="5000" help="resolution in bps. It must be between 200 and 10,000,000"> - <validator type="in_range" max="1000000000" min="200" message="Resolution is out of range, Resolution has to be between 200 to 100000000" /> - </param> - <param name="log" label="plot the log" type="boolean" truevalue="log" falsevalue="none" checked="False"/> - <param name="union" label="compute correlation in union regions" help="ignore regions covered by neither interval sets. Recommended for sparse data under high resolution when most regions are empty" type="boolean" truevalue="union" falsevalue="none" checked="False"/> - <repeat name="series" title="input file"> - <param name="label" type="text" value="" size="30" label="Data Label"/> - <param name="input" type="data" format="interval" label="Dataset"/> - </repeat> - </inputs> - - <configfiles> - <configfile name="script_file"> - ## Setup R error handling to go to stderr - options(warn=-1) - source("/Users/xuebing/galaxy-dist/tools/mytools/genomeview.r") - genome = read.table( "${genome}") - uselog = as.character("${log}") - union = as.character("${union}") - resolution = as.integer("${resolution}") - cat('resolution=',resolution,'\n') - offset = caloffset(genome) - mcov = matrix(ncol=1,nrow=as.integer(offset[length(offset)] / resolution)) - ## Open output PDF file - pdf( "${out_file1}" ,height=4,width=20) - labels = character(0) - ## Determine range of all series in the plot - #for $i, $s in enumerate( $series ) - x = read.table( "${s.input.file_name}" ) - res = coverage(x,genome,offset,resolution) - plotcov(res,genome,offset,"${s.label.value}",uselog) - labels = c(labels,"${s.label.value}") - attach(res) - mcov = cbind(mcov,cov) - detach(res) - #end for - dev.off() - pdf("${out_file2}") - mcov = mcov[,-1] - nSample = length(labels) - if (nSample > 1) { - if (union == 'union') { - cm = matrix(0,nrow=nSample,ncol=nSample) - for (i in 1:(nSample-1)) { - cm[i,i] = 1 - for (j in (i+1):nSample){ - cm[i,j] = union_correlation(mcov[,i],mcov[,j]) - cm[j,i] = cm[i,j] - } - } - cm[nSample,nSample] = 1 - } else { - cm = cor(mcov) - } - rm(mcov) - ##heatmap(-cm,margins=c(8,8),sym=T,scale='none',labRow=labels,labCol=labels) - ##heatmap2(cm,'none',TRUE,c(8,8),labels,labels) - x = cm - h = heatmap(-x,scale='none',sym=T,margins=c(8,8),labRow=labels,labRol=labels) - attach(h) - x = x[rowInd,colInd] - tx = numeric(0) - ty = numeric(0) - txt = character(0) - for (i in 1:nrow(x)){ - for (j in 1:ncol(x)){ - tx = c(tx,i) - ty = c(ty,ncol(x)-j+1) - txt = c(txt,round(x[i,j]*100)/100) - } - } - heatmap(-x,scale='none',sym=T,margins=c(8,8),labRow=labels[rowInd],labCol=labels[colInd],add.expr=text(tx,ty,txt,col='black')) - library(gplots) - heatmap.2(cm,margins=c(8,8),scale='none',key=TRUE,trace='none', symkey=T,symbreaks=T,col=bluered,labRow=labels,labCol=labels,symm=T) - } - dev.off() - </configfile> - </configfiles> - - <outputs> - <data format="pdf" name="out_file1" label="${tool.name} on ${on_string}: (plot)" /> - <data format="pdf" name="out_file2" label="${tool.name} on ${on_string}: (correlation)" /> - </outputs> - -<help> -.. class:: infomark - -This tool allows you to plot multiple intervals across all chromosomes at different resolution, and it also plots the correlation matrix if multiple intervals are provided. - ------ - -**Example** - -.. image:: ./static/images/correlationmatrix.png -.. image:: ./static/images/wholegenome.png - -</help> -</tool>
--- a/interval/genomeview-old2.r Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,52 +0,0 @@ - -caloffset = function(genome){ - total_len = sum(as.numeric(genome[,2])) - offset = 0 - for (i in 1:nrow(genome)) { - offset = c(offset,offset[i]+genome[i,2]) - } - offset -} - -coverage = function(intervals,genome,offset,resolution) { - - nChr = length(offset) - 1 - total_len = offset[nChr+1] - nbin = as.integer(total_len / resolution) - #cat('nbin=',nbin,'genomelen=',total_len,'\n') - cov = numeric(nbin)#coverage - col = numeric(nbin)#color - for (i in 1:nChr) { - d = x[x[,1]==as.character(genome[i,1]),2:3] - if (nrow(d) > 0){ - #cat('dim(d)=',dim(d),'\n') - d = ceiling((d+offset[i])*nbin/total_len) - for (j in 1:nrow(d)){ - cov[d[j,1]:d[j,2]] = cov[d[j,1]:d[j,2]] + 1 - } - } - col[ceiling(offset[i]*nbin/total_len):ceiling(offset[i]*nbin/total_len)] = i - } - list(nbin=nbin,cov=cov) -} - -# plot coverage -# res = genomeView(x,genome,100000) -plotcov = function(res,genome,offset,title,uselog) { - if (uselog == 'log'){ - res$cov = log10(res$cov+1) - } - ymax = max(res$cov) - par(mar=c(5,5,5,1)) - plot(seq(length(res$cov)),res$cov,type='h',cex=0.1,cex.axis=2,cex.lab=2,cex.main=3,col=res$col,xaxt='n',main=title,xlab='chromosome',ylab='coverage',frame.plot=F,ylim=c(0,ymax)) - xticks = numeric(nrow(genome)) - for (i in 1:nrow(genome)){ - xticks[i] = (offset[i]+offset[i+1])/2*res$nbin/offset[length(offset)] - } - mtext(genome[,1],side=1,at=xticks,adj=1,las=2,col=seq(nrow(genome))) -} - -union_correlation = function(x,y){ - z = x>0 | y>0 - cor(x[z],y[z]) -}
--- a/interval/genomeview.r Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,70 +0,0 @@ - -caloffset = function(genome){ - total_len = sum(as.numeric(genome[,2])) - offset = 0 - for (i in 1:nrow(genome)) { - offset = c(offset,offset[i]+genome[i,2]) - } - offset -} - -coverage = function(intervals,genome,offset,resolution) { - - nChr = length(offset) - 1 - total_len = offset[nChr+1] - nbin = as.integer(total_len / resolution) - cov = numeric(nbin)#coverage - col = numeric(nbin)#color - for (i in 1:nChr) { - d = x[x[,1]==as.character(genome[i,1]),2:3] - d = ceiling(((d[,1]+d[,2])/2+offset[i])*nbin/total_len) - t = table(d) - pos = as.numeric(row.names(t)) - cov[pos] = cov[pos] + as.numeric(t) - col[pos] = i - } - list(nbin=nbin,cov=cov,col=col) -} - -# plot coverage -# res = genomeView(x,genome,100000) -plotcov = function(res,genome,offset,title,uselog) { - if (uselog == 'log'){ - res$cov = log10(res$cov+1) - } - ymax = max(res$cov) - #print(ymax) - par(mar=c(5,5,5,1)) - plot(seq(length(res$cov)),res$cov,type='h',cex=0.1,cex.axis=2,cex.lab=2,cex.main=3,col=res$col,xaxt='n',main=title,xlab='chromosome',ylab='coverage',frame.plot=F,ylim=c(0,ymax)) - xticks = numeric(nrow(genome)) - for (i in 1:nrow(genome)){ - xticks[i] = (offset[i]+offset[i+1])/2*res$nbin/offset[length(offset)] - } - mtext(genome[,1],side=1,at=xticks,adj=1,las=2,col=seq(nrow(genome))) -} - -union_correlation = function(x,y){ - z = x>0 | y>0 - cor(x[z],y[z]) -} - - -heatmap2 = function(x,scale,sym,margins,labRow,labCol){ - h = heatmap(x,scale=scale,sym=sym,margins=margins,labRow=labRow,labCol=labCol) - x = x[h$rowInd,h$colInd] - tx = numeric(0) - ty = numeric(0) - txt = character(0) - for (i in 1:nrow(x)){ - for (j in 1:ncol(x)){ - tx <- c(tx,i) - ty <- c(ty,ncol(x)-j+1) - txt <- c(txt,format(x[i,j],digits=2,nsmall=2)) - } - } - #heatmap(x,scale=scale,sym=sym,margins=margins,labRow=labRow[h$rowInd],labCol=labCol[h$colInd],add.expr=text(1:4,1:4,1:4)) - cat(dim(tx)) - text(tx,ty,txt) - heatmap(x,scale=scale,sym=sym,margins=margins,labRow=labRow[h$rowInd],labCol=labCol[h$colInd],add.expr=text(tx,ty,txt)) - -}
--- a/interval/genomeview_notused Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,45 +0,0 @@ - -caloffset = function(genome){ - total_len = sum(as.numeric(genome[,2])) - offset = 0 - for (i in 1:nrow(genome)) { - offset = c(offset,offset[i]+genome[i,2]) - } - offset -} - -coverage = function(intervals,genome,offset,resolution) { - - nChr = length(offset) - 1 - total_len = offset[nChr+1] - nbin = as.integer(total_len / resolution) - - pos = numeric(0) - cov = numeric(0)#coverage - col = numeric(0)#color - for (i in 1:nChr) { - d = x[x[,1]==as.character(genome[i,1]),2:3] - d = ceiling(((d[,1]+d[,2])/2+offset[i])*nbin/total_len) - t = table(d) - pos = c(pos,as.numeric(row.names(t))) - cov = c(cov, as.numeric(t)) - col = c(col,numeric(length(t))+i) - } - list(nbin=nbin,pos=pos,cov=cov,col=col) -} - -# plot coverage -# res = genomeView(x,genome,100000) -plotcov = function(res,genome,offset,title,uselog) { - if (uselog == 'log'){ - res$cov = log10(res$cov+1) - } - ymax = max(res$cov) - par(mar=c(5,5,5,1)) - plot(res$pos,res$cov,type='h',cex=0.1,cex.axis=2,cex.lab=2,cex.main=3,col=res$col,xaxt='n',main=title,xlab='chromosome',ylab='coverage',frame.plot=F,xlim=c(0,res$nbin),ylim=c(0,ymax)) - xticks = numeric(nrow(genome)) - for (i in 1:nrow(genome)){ - xticks[i] = (offset[i]+offset[i+1])/2*res$nbin/offset[length(offset)] - } - mtext(genome[,1],side=1,at=xticks,adj=1,las=2,col=seq(nrow(genome))) -}
--- a/interval/getGenomicScore.py Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,78 +0,0 @@ -import random,string,os,sys - - -def getScore(intvfile,outfile,summary_type,bwfilepath,nbin,strand,outplot,span): - f = open(intvfile) - tmpsh = "".join(random.sample(string.letters+string.digits, 8)) - tmpout = "".join(random.sample(string.letters+string.digits, 8)) - tmp = open(tmpsh,'w') - if os.path.isdir(bwfilepath): - for line in f: - flds = line.strip().split('\t') - cmd = 'bigWigSummary -type='+summary_type+' '+bwfilepath+'/'+flds[0]+'.bw '+flds[0]+' '+flds[1]+' '+flds[2]+' '+nbin+' >> '+tmpout+' 2>>'+tmpout+'\n' - tmp.write(cmd) - else: - for line in f: - flds = line.strip().split('\t') - cmd = 'bigWigSummary -type='+summary_type+' '+bwfilepath+' '+flds[0]+' '+flds[1]+' '+flds[2]+' '+nbin+' >> '+tmpout+' 2>>'+tmpout+'\n' - tmp.write(cmd) - f.close() - # remove blank lines - tmp.write("sed '/^$/d' "+tmpout+'>'+tmpout+".1\n") - tmp.write("sed '/^Can/d' "+tmpout+".1 >"+tmpout+".2\n") - # set n/a to 0 - tmp.write("sed 's/n\/a/0/g' "+tmpout+".2 >"+tmpout+".3\n") - # replace text with 0 - zeros = ''.join(['0\t']*int(nbin)) - tmp.write("sed 's/^[a-zA-Z]/"+zeros+"/' "+tmpout+".3 >"+tmpout+".4\n") - # cut the first nbin columns - tmp.write("cut -f 1-"+nbin+" "+tmpout+".4 > "+tmpout+".5\n") - tmp.write("paste "+intvfile+" "+tmpout+".5 >"+outfile+"\n") - tmp.close() - os.system('chmod +x '+tmpsh) - os.system('./'+tmpsh) - #os.system('rm '+tmpout+'*') - #os.system('rm '+tmpsh) - - # strandness: need to reverse bins for - strand - if nbin > 1 and strand > 0: - strand = strand - 1 # python is 0 based - os.system('mv '+outfile+' '+tmpout) - f = open(tmpout) - out = open(outfile,'w') - for line in f: - flds=line.strip().split('\t') - if flds[strand] == '+': - out.write(line) - else: - scores = flds[-int(nbin):] - scores.reverse() - flds = flds[:-int(nbin)]+scores - out.write('\t'.join(flds)+'\n') - os.system('rm '+tmpout) - f.close() - out.close() - # plot - if int(nbin) > 1: - rscript = open(tmpsh,"w") - rscript.write("options(warn=-1)\n") - rscript.write("x <- read.table('"+outfile+"',sep='\t')\n") - rscript.write("x <- x[,(ncol(x)+1-"+nbin+"):ncol(x)]\n") - rscript.write("pdf('"+outplot+"')\n") - rscript.write("avg <- apply(x,2,mean)\n") - rscript.write("err <- apply(x,2,sd)/sqrt(nrow(x))\n") - rscript.write("ylim=c(min(avg-err),max(avg+err))\n") - rscript.write("xticks <- seq(ncol(x))-(1+ncol(x))/2\n") - if span >= 0.1: - rscript.write("avg = loess(avg~xticks,span="+str(span)+")$fitted\n") - rscript.write("err = loess(err~xticks,span="+str(span)+")$fitted\n") - rscript.write("par(cex=1.5)\n") - rscript.write("plot(xticks,avg,ylab='average conservation score',xlab='relative position (bin)',type='l',lwd=0,ylim=ylim)\n") - rscript.write("polygon(c(xticks,rev(xticks)),c(avg+err,rev(avg-err)),col='slateblue1',border=NA)\n") - rscript.write("lines(xticks,avg,type='l',lwd=1)\n") - rscript.write("dev.off()\n") - rscript.close() - os.system("R --vanilla < "+tmpsh) - os.system("rm "+tmpsh) - -getScore(sys.argv[1],sys.argv[2],sys.argv[3],sys.argv[4],sys.argv[5],int(sys.argv[6]),sys.argv[7],float(sys.argv[8]))
--- a/interval/intersectSig.py Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,90 +0,0 @@ -''' -find overlap and test signifiance -''' - -import os,sys - -def lineCount(filename): - if os.stat(filename).st_size == 0: - return 0 - with open(filename) as f: - for i, l in enumerate(f): - pass - print i - return i+1 - -def intersect(fileA,fileB,outfile,fraction,reciprocal): - # return fileA intervals that overlap with interval in fileB - cmd = 'intersectBed -a '+fileA+' -b '+fileB + ' -u -wa -f '+fraction +' '+ reciprocal + '>'+outfile - #print cmd - os.system(cmd) - -def shuffle(fileA,fileB,genomefile,fraction,reciprocal,N): - # shuffle fileA N times, return the distribution of overlaps - nOverlap = [] - for i in range(N): - # shuffle fileA using shuffleBed - #cmd = 'shuffleBed -i '+fileA+' -g '+genomefile +'>fileA.shuffled' - # using random_interval.py - cmd = 'python /Users/xuebing/galaxy-dist/tools/mytools/random_interval.py '+fileA+' fileA.shuffled across '+genomefile - os.system(cmd) - intersect('fileA.shuffled',fileB,'tmp',fraction,reciprocal) - nOverlap.append(lineCount('tmp')) - os.system('rm tmp') - os.system('rm fileA.shuffled') - return nOverlap - -def main(): - fileA = sys.argv[1] - fileB = sys.argv[2] - outfile = sys.argv[3] - outplot = sys.argv[4] - outshuffle = sys.argv[5] - N = int(sys.argv[6]) # times to shuffle - genomefile = sys.argv[7] - fraction = sys.argv[8] - if len(sys.argv) == 10: - reciprocal = sys.argv[9] # can only be '-r' - else: - reciprocal = '' - - #print sys.argv - - # number of lines in input - nA = lineCount(fileA) - nB = lineCount(fileB) - - # intersect on real data - intersect(fileA,fileB,outfile,fraction,reciprocal) - # number of overlaps - nOverlapReal = lineCount(outfile) - - #print 'number of intervals in inputA that overlap with intervals in inputB:',nOverlapReal - - # shuffle fileA to estimate background - nOverlapNull = shuffle(fileA,fileB,genomefile,fraction,reciprocal,N) - out = open(outshuffle,'w') - out.write("\t".join(map(str,nOverlapNull))) - out.close() - - # plot histogram - rscript = open('tmp.r','w') - rscript.write("options(warn=-1)\n") - rscript.write("x0 <- "+str(nOverlapReal)+"\n") - rscript.write("x <- c("+','.join(map(str,nOverlapNull))+")\n") - rscript.write("library(MASS)\n") - rscript.write("pv <- min((1+sum(x>=x0))/length(x),(1+sum(x<=x0))/length(x))\n") - rscript.write("title <- paste('actual:chance = ',x0,':',format(mean(x),digits=1,nsmall=1),' = ',format(x0/mean(x),digits=1,nsmall=2),', p-value < ',pv,sep='')\n") - rscript.write("pdf('"+outplot+"')\n") - rscript.write("library(grid)\n") - rscript.write("library(VennDiagram)\n") - rscript.write("venn <- venn.diagram(x=list(A=1:"+str(nA)+",B="+str(nA-nOverlapReal+1)+":"+str(nA+nB-nOverlapReal)+"),filename=NULL,fill=c('red','blue'),col='transparent',alpha=0.5,label.col='black',cex=3,lwd=0,fontfamily='serif',fontface='bold',cat.col = c('red', 'blue'),cat.cex=3,cat.fontfamily='serif',cat.fontface='bold')\n") - rscript.write("grid.draw(venn)\n") - rscript.write("h <- hist(x,breaks=50,xlab='number of overlaps',ylab='frequency',main=title)\n") - rscript.write("plot(h$mids,h$counts,type='h',xlim=c(min(h$mids,x0),max(x0,h$mids)),ylim=c(0,max(h$counts)),xlab='number of overlaps',ylab='frequency',main=title)\n") - rscript.write("points(x0,0,col='red')\n") - rscript.write("dev.off()\n") - rscript.close() - os.system("R --vanilla < tmp.r") - os.system('rm tmp.r') -main()
--- a/interval/intersectSig.xml Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,30 +0,0 @@ -<tool id="intersectsig" name="test overlap"> - <description>of two interval lists</description> - <command interpreter="python"> intersectSig.py $fileA $fileB $outfile $outplot $outshuffle $n $genome $fraction $reciprocal </command> - <inputs> - <param name="fileA" type="data" format="interval" label="Return intervals in file A" /> - <param name="fileB" type="data" format="interval" label="that overlap with intervals in file B" /> - <param name="genome" type="select" label="Select genome"> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/chrsize/mouse.mm9.genome" selected="true">mm9</option> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/chrsize/mouse.mm8.genome">mm8</option> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/chrsize/human.hg18.genome">hg18</option> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/chrsize/human.hg19.genome">hg19</option> - </param> - <param name="fraction" size="10" type="float" value="1e-9" label="Minimum overlap required as a fraction of interval in file A" help="Default is 1E-9 (i.e., 1bp)."/> - <param name="reciprocal" label="Require that the fraction overlap be reciprocal for A and B" type="boolean" truevalue="-r" falsevalue="" checked="False"/> - <param name="n" size="10" type="integer" value="100" label="Number of permutations to run" help="File A is shuffled this number of times and the number of random overlaps is used to estimate the null distribution and compute the p value"/> -</inputs> - <outputs> - <data format="interval" name="outfile" label="${tool.name} on ${on_string}:overlap"/> - <data format="txt" name="outshuffle" label="${tool.name} on ${on_string}:null"/> - <data format="pdf" name="outplot" label="${tool.name} on ${on_string}:plot"/> - </outputs> - <help> - -**What it does** - -This tool uses intersectBed to find intervals in the first dataset that overlap with intervals in the second dataset. To estimate the significance of the overlap, the first dataset is shuffled then intersect with the second dataset to generate a null distribution of the number of overlaps. The tool returns venn diagram plot, histogram of the null distribution, overlapped intervals from the first input, and the null distribution of overlaps. - - </help> -</tool> -
--- a/interval/intersectbed.xml Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,103 +0,0 @@ -<tool id="intersectbed" name="intersectBed"> - <description>intersect two interval sets</description> - <command> intersectBed -a $inputa -b $inputb $output_opt $strandness $r -f $f $split > $output_data - </command> - <inputs> - <param name="inputa" type="data" format="interval,bam,bed,gff,vcf" label="Input A (-a)"/> - <param name="inputb" type="data" format="interval,bam,bed,gff,vcf" label="Input B (-b)"/> - <param name="output_opt" type="select" label="Output style" > - <option value="-wa" selected="true"> -wa: entry in A that overlaps B</option> - <option value="-wb" > -wb: entry in B that overlaps A</option> - <option value="-wo" > -wo: A,B, and num bases overlap </option> - <option value="-wao" > -wao: A,B, and num bases overlap </option> - <option value="-u" > -u: A only </option> - <option value="-c" > -c: A, num B features overlap </option> - <option value="-v" > -v: A without overlap </option> - </param> - - <param name="f" size="10" type="float" value="1E-9" label="Minimum overlap required as a fraction of A"/> - - <param name="strandness" type="select" label="Strand requirement" > - <option value="" selected="true"> none </option> - <option value="-s" > -s: require overlap on the same strand</option> - <option value="-S" > -S: require overlap on the opposite strand </option> - </param> - - <param name="r" label="Require that the fraction overlap be reciprocal for A and B (-r)." type="boolean" truevalue="-r" falsevalue="" checked="False"/> - <param name="split" label="Treat'split' BAM or BED12 entries as distinct BED intervals (-split)." type="boolean" truevalue="-split" falsevalue="" checked="False"/></inputs> - <outputs> - <data format="bed" name="output_data"/> - </outputs> - <help> - -**What it does** - -This is a wrapper for intersecBed. - - Program: intersectBed (v2.13.3) - Author: Aaron Quinlan (aaronquinlan@gmail.com) - Summary: Report overlaps between two feature files. - -Usage:: - - intersectBed [OPTIONS] -a (bed/gff/vcf) -b (bed/gff/vcf) - -Options:: - -abam The A input file is in BAM format. Output will be BAM as well. - - -ubam Write uncompressed BAM output. Default is to write compressed BAM. - - -bed When using BAM input (-abam), write output as BED. The default - is to write output in BAM when using -abam. - - -wa Write the original entry in A for each overlap. - - -wb Write the original entry in B for each overlap. - - Useful for knowing _what_ A overlaps. Restricted by -f and -r. - - -wo Write the original A and B entries plus the number of base - pairs of overlap between the two features. - - Overlaps restricted by -f and -r. - Only A features with overlap are reported. - - -wao Write the original A and B entries plus the number of base - pairs of overlap between the two features. - - Overlapping features restricted by -f and -r. - However, A features w/o overlap are also reported - with a NULL B feature and overlap = 0. - - -u Write the original A entry _once_ if _any_ overlaps found in B. - - In other words, just report the fact >=1 hit was found. - - Overlaps restricted by -f and -r. - - -c For each entry in A, report the number of overlaps with B. - - Reports 0 for A entries that have no overlap with B. - - Overlaps restricted by -f and -r. - - -v Only report those entries in A that have _no overlaps_ with B. - - Similar to "grep -v" (an homage). - - -f Minimum overlap required as a fraction of A. - - Default is 1E-9 (i.e., 1bp). - - FLOAT (e.g. 0.50) - - -r Require that the fraction overlap be reciprocal for A and B. - - In other words, if -f is 0.90 and -r is used, this requires - that B overlap 90% of A and A _also_ overlaps 90% of B. - - -s Require same strandedness. That is, only report hits in B that - overlap A on the _same_ strand. - - By default, overlaps are reported without respect to strand. - - -S Require different strandedness. That is, only report hits in B that - overlap A on the _opposite_ strand. - - By default, overlaps are reported without respect to strand. - - -split Treat "split" BAM or BED12 entries as distinct BED intervals. - - -sorted Use the "chromsweep" algorithm for sorted (-k1,1 -k2,2n) input - NOTE: this will trust, but not enforce that data is sorted. Caveat emptor. - - </help> -</tool> -
--- a/interval/intervalOverlap.py Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,82 +0,0 @@ -''' -find overlap and test signifiance -''' - -import os,sys - -def lineCount(filename): - i = 0 - with open(filename) as f: - for i, l in enumerate(f): - pass - return i + 1 - -def intersect(fileA,fileB,outfile,fraction,reciprocal): - # return fileA intervals that overlap with interval in fileB - cmd = 'intersectBed -a '+fileA+' -b '+fileB + ' --wo -f '+fraction +' '+ reciprocal + '>'+outfile - #print cmd - os.system(cmd) - -def parseIntersect(filename): - # get number of overlapped A and B - nA = 0 - nB = 0 - return nA,nb - -def shuffle(fileA,fileB,genomefile,fraction,reciprocal,N): - # shuffle fileA N times, return the distribution of overlaps - nOverlap = [] - for i in range(N): - # shuffle fileA using shuffleBed - #cmd = 'shuffleBed -i '+fileA+' -g '+genomefile +'>fileA.shuffled' - # using random_interval.py - cmd = 'python /Users/xuebing/galaxy-dist/tools/mytools/random_interval.py '+fileA+' fileA.shuffled across '+genomefile - os.system(cmd) - intersect('fileA.shuffled',fileB,'tmp',fraction,reciprocal) - nOverlap.append(lineCount('tmp')) - os.system('rm tmp') - os.system('rm fileA.shuffled') - return nOverlap - -def main(): - fileA = sys.argv[1] - fileB = sys.argv[2] - outfile = sys.argv[3] - outplot = sys.argv[4] - N = int(sys.argv[5]) # times to shuffle - genomefile = sys.argv[6] - fraction = sys.argv[7] - if len(sys.argv) == 9: - reciprocal = sys.argv[8] # can only be '-r' - else: - reciprocal = '' - - print sys.argv - - # intersect on real data - intersect(fileA,fileB,outfile,fraction,reciprocal) - # number of overlaps - nOverlapReal = lineCount(outfile) - - print 'number of intervals in inputA that overlap with intervals in inputB:',nOverlapReal - - # shuffle fileA to estimate background - nOverlapNull = shuffle(fileA,fileB,genomefile,fraction,reciprocal,N) - - # plot histogram - rscript = open('tmp.r','w') - rscript.write("x0 <- "+str(nOverlapReal)+"\n") - rscript.write("x <- c("+','.join(map(str,nOverlapNull))+")\n") - rscript.write("library(MASS)\n") - rscript.write("\n") - rscript.write("pv <- min((1+sum(x>=x0))/length(x),(1+sum(x<=x0))/length(x))\n") - rscript.write("title <- paste('actual:chance = ',x0,':',round(mean(x)),' = ',format(x0/mean(x),digits=1,nsmall=2),', p-value < ',pv,sep='')\n") - rscript.write("pdf('"+outplot+"')\n") - rscript.write("h <- hist(x,breaks=50,xlab='number of overlaps',ylab='frequency',main=title)\n") - rscript.write("plot(h$mids,h$counts,type='h',xlim=c(min(h$mids,x0),max(x0,h$mids)),ylim=c(0,max(h$counts)),xlab='number of overlaps',ylab='frequency',main=title)\n") - rscript.write("points(x0,0,col='red')\n") - rscript.write("dev.off()") - rscript.close() - os.system("R --vanilla < tmp.r") - os.system('rm tmp.r') -main()
--- a/interval/intervalSize.py Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,18 +0,0 @@ -''' -plot histogram of interval size -''' - -import os,sys - -inputfile = sys.argv[1] -outputfile = sys.argv[2] - -rf = open('tmp.r','w') -rf.write("x <- read.table('"+inputfile+"')\n") -rf.write("len <- x[,3]-x[,2]\n") -rf.write("pdf('"+outputfile+"')\n") -rf.write("hist(len,breaks=100,xlab='interval size',main=paste('mean=',mean(len),sep=''))\n") -rf.write("dev.off()") -rf.close() -os.system("R --vanilla < tmp.r") -os.system('rm tmp.r')
--- a/interval/intervalSize.xml Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,17 +0,0 @@ -<tool id="intervalsize" name="interval size"> - <description>distribution</description> - <command interpreter="python">intervalSize.py $input $output</command> - <inputs> - <param name="input" format="txt" type="data" label="Plot the size distribution of the following file"/> - </inputs> - <outputs> - <data format="pdf" name="output" /> - </outputs> - <help> - -**What it does** - -This tool generates a histogram of the interval size. - - </help> -</tool>
--- a/interval/makebigwig.sh Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,57 +0,0 @@ -# use of output: move to public_html and visualize in ucsc genome browser with the following: -# track name="xxx" color=0,0,255 type=bigWig bigDataUrl=http://rous.mit.edu/~wuxbl/xxx.bw - -if [ $# -lt 6 ] -then - echo "./bigwig.sh infile outtag bam/bed sorted/none genome strand/none [-split]" - exit -fi - -f=$1 -outf=$2 -extension=$3 -sorted=$4 -genome=$5 -strand=$6 -split=$7 -i=i -if [ $extension = bam ] -then - i=ibam - if [ $sorted != sorted ] - then - echo 'sorting bam file...=>' $f.sorted.bam - samtools sort $f $f.sorted - f=$f.sorted.bam - fi -else - if [ $sorted != sorted ] - then - echo 'sorting bed file...=>' $f.sorted.bed - sort -k1,1 $f > $f.sorted.bed - f=$f.sorted.bed - fi -fi - - echo 'making bedgraph file...=>' $f.bedgraph - if [ $strand != strand ] - then - genomeCoverageBed -bg -$i $f -g $genome $split > $f.bedgraph - echo 'making bigwig file...=>' $outf.bw - bedGraphToBigWig $f.bedgraph $genome $outf - else - genomeCoverageBed -bg -$i $f -g $genome $split -strand + > $f+.bedgraph - genomeCoverageBed -bg -$i $f -g $genome $split -strand - > $f-.bedgraph - echo 'making bigwig file for + strand...=>' $outf+.bw - bedGraphToBigWig $f+.bedgraph $genome $outf+.bw - echo 'making bigwig file for - strand...=>' $outf-.bw - bedGraphToBigWig $f-.bedgraph $genome $outf-.bw - fi - -# remove intermediate files -if [ $sorted != sorted ] - then - rm $f -fi -rm $f*.bedgraph -
--- a/interval/makebigwig.sh-old Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,59 +0,0 @@ -# make bigwig file for genome browser visulization -# usage -# makebigwig.sh <infilename> <outfile> bedorbam sorted genome strand -split -# input file types: *.bed, *.bam - -# use of output: move to public_html and visualize in ucsc genome browser with the following: -# track name="xxx" color=0,0,255 type=bigWig bigDataUrl=http://rous.mit.edu/~wuxbl/xxx.bw - -if [ $# -lt 6 ] -then - echo "./makebigwig.sh infile outfile bedorbam sorted genome [-split -strand]" - exit -fi - -f=$1 -outf=$2 -extension=$3 -sorted=$4 -genome=$5 -strand=$6 -split=$7 -i=i -echo 'genome:' $genome -echo 'strand:' $strand - -if [ $extension = bam ] -then - i=ibam - if [ $sorted != sorted ] - then - echo 'sorting bam file...=>' $f.sorted.bam - samtools sort $f $f.sorted - f=$f.sorted.bam - fi -else - if [ $sorted != sorted ] - then - echo 'sorting bed file...=>' $f.sorted.bed - sort -k1,1 -k2,2g $f > $f.sorted.bed - f=$f.sorted.bed - fi -fi - - echo 'making bedgraph file...=>' $f.bedgraph - if [ $strand != strand ] - then - genomeCoverageBed -bg -$i $f -g $genome $split > $f.bedgraph - echo 'making bigwig file...=>' $f.bw - bedGraphToBigWig $f.bedgraph $genome $outf - else - genomeCoverageBed -bg -$i $f -g $genome $split -strand + > $f+.bedgraph - genomeCoverageBed -bg -$i $f -g $genome $split -strand - > $f-.bedgraph - echo 'making bigwig file for + strand...' $f+.bw - bedGraphToBigWig $f+.bedgraph $genome $outf+ - echo 'making bigwig file for - strand...=>' $f-.bw - bedGraphToBigWig $f-.bedgraph $genome $outf- - fi - rm $f -
--- a/interval/makebigwig.xml Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,37 +0,0 @@ -<tool id="makebigwig" name="make bigwig"> - <description>from BED or BAM</description> - <command interpreter="sh"> makebigwig.sh $input $outfile - #if $inputa_format.bedorbam == "bed": - bed - #else: - bam - #end if - $sorted $genome none $split >$log 2> $log </command> - <inputs> - <conditional name="inputa_format"> - <param name="bedorbam" type="select" label="Select input format" > - <option value="bed" selected="true">BED</option> - <option value="bam"> BAM</option> - </param> - <when value="bed"> - <param name="input" type="data" format="bed" label="Input file"/> - </when> - <when value="bam"> - <param name="input" type="data" format="bam" label="Input file"/> - </when> - </conditional> - <param name="genome" type="select" label="Select genome"> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/chrsize/mouse.mm9.genome" selected="true">mm9</option> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/chrsize/mouse.mm8.genome">mm8</option> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/chrsize/human.hg18.genome">hg18</option> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/chrsize/human.hg19.genome">hg19</option> - </param> - <param name="sorted" label="Check if the input is sorted" type="boolean" truevalue="sorted" falsevalue="none" checked="False"/> - <param name="split" label="Split junctions" help="Treat 'split' BAM or BED12 entries as distinct BED intervals." type="boolean" truevalue="-split" falsevalue="" checked="False"/> - </inputs> - <outputs> - <data format="txt" name="log" label="makebigwig LOG" /> - <data format="bigwig" name="outfile" /> - - </outputs> -</tool>
--- a/interval/makewindow.py Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,19 +0,0 @@ -def makeWindow(filename,outfile,window): - window = window/2 - f=open(filename) - out = open(outfile,'w') - for line in f: - flds = line.strip().split() - #new position - center = (int(flds[1]) + int(flds[2]))/2 - start = center - window - end = center + window - if start >= 0: - flds[1] = str(start) - flds[2] = str(end) - out.write('\t'.join(flds)+'\n') - f.close() - out.close() - -import sys -makeWindow(sys.argv[1],sys.argv[2],int(sys.argv[3]))
--- a/interval/makewindow.xml Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,18 +0,0 @@ -<tool id="makewindow" name="make-window"> - <description>around interval center </description> - <command interpreter="python"> makewindow.py $input $output $window </command> - <inputs> - <param name="input" type="data" format="interval" label="Input interval file"/> - <param name="window" type="integer" value="1000" label="window size (bps)" /> - </inputs> - <outputs> - <data format="input" name="output" /> - </outputs> - <help> - -**Description** - -For each interval in the input file, take the middle point, then extend each side windowsize/2 bps. - - </help> -</tool>
--- a/interval/metaintv.py Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,109 +0,0 @@ -''' -get binned score of intervals,allow extension -''' - -import os,sys,numpy - -from resize import * - -from bx.bbi.bigwig_file import BigWigFile - -def binning(x,n): - # make n bin of x - y = numpy.zeros(n,dtype=float) - if len(x) == 0: - return y - step = float(len(x))/n - for k in range(n): - i = int(step*k) - j = int(step*(k+1)) + 1 - y[k] = x[i:j].mean() - #print i,j,k,y[k] - return y - -def getBinnedScore(bwfile,intvfile,nbin): - ''' - get binned average and std - ''' - fbw = open(bwfile) - bw = BigWigFile(file=fbw) - fin = open(intvfile) - avg = numpy.zeros(nbin) - sqr = numpy.zeros(nbin) - N = 0 - for line in fin: - #chrom,start,end,name,score,strand - flds = line.strip().split('\t') - #get the score at base resolution as an array - scores = bw.get_as_array(flds[0],int(flds[1]),int(flds[2])) - if scores == None: - print 'not found:\t',line - continue - N = N + 1 - #print line,scores - # reverse if on minus strand - if flds[5] == '-': - scores = scores[::-1] - # no score = 0 - scores = numpy.nan_to_num(scores) - # bin the data - binned = binning(scores,nbin) - avg = avg + binned - sqr = sqr + binned**2 - # compute avg and std - avg = avg / N - err = ((sqr/N-avg**2)**0.5)/(N**0.5) - return avg,err - -def getExtendedBinScore(bwfile,intvfile,nbins,exts): - ''' - nbins: n1,n2,n3 - exts: l1,l2,l3,l4 - ''' - # make left extension - resize(intvfile,intvfile+'.tmp','start-'+str(exts[0]),'start+'+str(exts[1]),'stranded') - # compute binned average - avg,err = getBinnedScore(bwfile,intvfile+'.tmp',nbins[0]) - # make center region - resize(intvfile,intvfile+'.tmp','start+'+str(exts[1]),'end-'+str(exts[2]),'stranded') - # compute binned average - avg1,err1 = getBinnedScore(bwfile,intvfile+'.tmp',nbins[1]) - avg = numpy.concatenate((avg,avg1)) - err = numpy.concatenate((err,err1)) - # make right region - resize(intvfile,intvfile+'.tmp','end-'+str(exts[2]),'end+'+str(exts[3]),'stranded') - # compute binned average - avg2,err2 = getBinnedScore(bwfile,intvfile+'.tmp',nbins[2]) - avg = numpy.concatenate((avg,avg2)) - err = numpy.concatenate((err,err2)) - - return avg,err - -print sys.argv -prog,bwfile,intvfile,nbin,outfile,outplot = sys.argv -avg, err = getBinnedScore(bwfile,intvfile,int(nbin)) -out = open(outfile,'w') -numpy.savetxt(out, avg, fmt='%.6f', delimiter=' ', newline=' ') -out.write('\n') -numpy.savetxt(out, err, fmt='%.6f', delimiter=' ', newline=' ') -out.write('\n') -out.close() - -# plot -rscript = open("tmp.r","w") -rscript.write("options(warn=-1)\n") -rscript.write("x <- read.table('"+outfile+"')\n") -rscript.write("pdf('"+outplot+"')\n") -rscript.write("avg <- x[1,]\n") -rscript.write("err <- x[2,]\n") -rscript.write("print(x)\n") -rscript.write("ylim=c(min(avg-err),max(avg+err))\n") -rscript.write("xticks <- seq(ncol(x))\n") -rscript.write("plot(xticks,avg,xlab='',ylab='average coverage',type='l',lwd=0,ylim=ylim)\n") -rscript.write("polygon(c(xticks,rev(xticks)),c(avg+err,rev(avg-err)),col='lightgreen',border=NA)\n") -rscript.write("lines(xticks,avg,type='l',lwd=1)\n") -rscript.write("dev.off()\n") -rscript.close() -os.system("R --vanilla < tmp.r") -os.system("rm tmp.r") -
--- a/interval/metaintv.xml Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,36 +0,0 @@ -<tool id="metaintv" name="binned-average"> - <description>from bigwig</description> - <command interpreter="python">binnedAverage.py $bwfile $intvfile $nbin $outfile $outplot </command> - <inputs> - <param name="intvfile" format="bed" type="data" label="BED file (require strand in column 6)"/> - <param name="bwfile" format="bigwig" type="data" label="BigWig file"/> - <param name="nbin" type="integer" value="20" label="number of bins"/> - - </inputs> - <outputs> - <data format="tabular" name="outfile" label="${tool.name} on ${on_string}[data]"/> - <data format="pdf" name="outplot" label="${tool.name} on ${on_string}[plot]"/> - </outputs> - <help> - -.. class:: infomark - -Each interval is binned and the average base-resolution score/coverage/density in the bigwig file is added as new columns appended at the end of the original file . - -**Example** - -If your original data has the following format: - -+-----+-----+---+------+ -|chrom|start|end|other2| -+-----+-----+---+------+ - -and you choose to divide each interval into 3 bins and return the mean scores of each bin, your output will look like this: - -+-----+-----+---+------+-----+-----+-----+ -|chrom|start|end|other2|mean1|mean2|mean3| -+-----+-----+---+------+-----+-----+-----+ - - -</help> -</tool>
--- a/interval/metaintv2.py Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,109 +0,0 @@ -''' -get binned score of intervals,allow extension -''' - -import os,sys,numpy - -from resize import * - -from bx.bbi.bigwig_file import BigWigFile - -def binning(x,n): - # make n bin of x - y = numpy.zeros(n,dtype=float) - if len(x) == 0: - return y - step = float(len(x))/n - for k in range(n): - i = int(step*k) - j = int(step*(k+1)) + 1 - y[k] = x[i:j].mean() - #print i,j,k,y[k] - return y - -def getBinnedScore(bwfile,intvfile,nbin): - ''' - get binned average and std - ''' - fbw = open(bwfile) - bw = BigWigFile(file=fbw) - fin = open(intvfile) - avg = numpy.zeros(nbin) - sqr = numpy.zeros(nbin) - N = 0 - for line in fin: - #chrom,start,end,name,score,strand - flds = line.strip().split('\t') - #get the score at base resolution as an array - scores = bw.get_as_array(flds[0],int(flds[1]),int(flds[2])) - if scores == None: - print 'not found:\t',line - continue - N = N + 1 - #print line,scores - # reverse if on minus strand - if flds[5] == '-': - scores = scores[::-1] - # no score = 0 - scores = numpy.nan_to_num(scores) - # bin the data - binned = binning(scores,nbin) - avg = avg + binned - sqr = sqr + binned**2 - # compute avg and std - avg = avg / N - err = ((sqr/N-avg**2)**0.5)/(N**0.5) - return avg,err - -def getExtendedBinScore(bwfile,intvfile,nbins,exts): - ''' - nbins: n1,n2,n3 - exts: l1,l2,l3,l4 - ''' - # make left extension - resize(intvfile,intvfile+'.tmp','start-'+str(exts[0]),'start+'+str(exts[1]),'stranded') - # compute binned average - avg,err = getBinnedScore(bwfile,intvfile+'.tmp',nbins[0]) - # make center region - resize(intvfile,intvfile+'.tmp','start+'+str(exts[1]),'end-'+str(exts[2]),'stranded') - # compute binned average - avg1,err1 = getBinnedScore(bwfile,intvfile+'.tmp',nbins[1]) - avg = numpy.concatenate((avg,avg1)) - err = numpy.concatenate((err,err1)) - # make right region - resize(intvfile,intvfile+'.tmp','end-'+str(exts[2]),'end+'+str(exts[3]),'stranded') - # compute binned average - avg2,err2 = getBinnedScore(bwfile,intvfile+'.tmp',nbins[2]) - avg = numpy.concatenate((avg,avg2)) - err = numpy.concatenate((err,err2)) - - return avg,err - -print sys.argv -bwfile,intvfile,exts,nbins,outfile,outplot = sys.argv -avg, err = getExtendedBinScore(bwfile,intvfile,numpy.fromstring(nbins,sep=','),numpy.fromstring(exts,sep=',')) -out = open(outfile,'w') -numpy.savetxt(out, avg, fmt='%.6f', delimiter=' ', newline=' ') -out.write('\n') -numpy.savetxt(out, err, fmt='%.6f', delimiter=' ', newline=' ') -out.write('\n') -out.close() - -# plot -rscript = open("tmp.r","w") -rscript.write("options(warn=-1)\n") -rscript.write("x <- read.table('"+outfile+"')\n") -rscript.write("pdf('"+outplot+"')\n") -rscript.write("avg <- x[1,]\n") -rscript.write("err <- x[2,]\n") -rscript.write("print(x)\n") -rscript.write("ylim=c(min(avg-err),max(avg+err))\n") -rscript.write("xticks <- seq(ncol(x))\n") -rscript.write("plot(xticks,avg,ylab='average coverage',type='l',lwd=0,ylim=ylim)\n") -rscript.write("polygon(c(xticks,rev(xticks)),c(avg+err,rev(avg-err)),col='lightgreen',border=NA)\n") -rscript.write("lines(xticks,avg,type='l',lwd=1)\n") -rscript.write("dev.off()\n") -rscript.close() -os.system("R --vanilla < tmp.r") -os.system("rm tmp.r") -
--- a/interval/metaintv3.py Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,109 +0,0 @@ -''' -get binned score of intervals,allow extension -''' - -import os,sys,numpy - -from resize import * - -from bx.bbi.bigwig_file import BigWigFile - -def binning(x,n): - # make n bin of x - y = numpy.zeros(n,dtype=float) - if len(x) == 0: - return y - step = float(len(x))/n - for k in range(n): - i = int(step*k) - j = int(step*(k+1)) + 1 - y[k] = x[i:j].mean() - #print i,j,k,y[k] - return y - -def getBinnedScore(bwfile,intvfile,nbin): - ''' - get binned average and std - ''' - fbw = open(bwfile) - bw = BigWigFile(file=fbw) - fin = open(intvfile) - avg = numpy.zeros(nbin) - sqr = numpy.zeros(nbin) - N = 0 - for line in fin: - #chrom,start,end,name,score,strand - flds = line.strip().split('\t') - #get the score at base resolution as an array - scores = bw.get_as_array(flds[0],int(flds[1]),int(flds[2])) - if scores == None: - print 'not found:\t',line - continue - N = N + 1 - #print line,scores - # reverse if on minus strand - if flds[5] == '-': - scores = scores[::-1] - # no score = 0 - scores = numpy.nan_to_num(scores) - # bin the data - binned = binning(scores,nbin) - avg = avg + binned - sqr = sqr + binned**2 - # compute avg and std - avg = avg / N - err = ((sqr/N-avg**2)**0.5)/(N**0.5) - return avg,err - -def getExtendedBinScore(bwfile,intvfile,nbins,exts): - ''' - nbins: n1,n2,n3 - exts: l1,l2,l3,l4 - ''' - # make left extension - resize(intvfile,intvfile+'.tmp','start-'+str(exts[0]),'start+'+str(exts[1]),'stranded') - # compute binned average - avg,err = getBinnedScore(bwfile,intvfile+'.tmp',nbins[0]) - # make center region - resize(intvfile,intvfile+'.tmp','start+'+str(exts[1]),'end-'+str(exts[2]),'stranded') - # compute binned average - avg1,err1 = getBinnedScore(bwfile,intvfile+'.tmp',nbins[1]) - avg = numpy.concatenate((avg,avg1)) - err = numpy.concatenate((err,err1)) - # make right region - resize(intvfile,intvfile+'.tmp','end-'+str(exts[2]),'end+'+str(exts[3]),'stranded') - # compute binned average - avg2,err2 = getBinnedScore(bwfile,intvfile+'.tmp',nbins[2]) - avg = numpy.concatenate((avg,avg2)) - err = numpy.concatenate((err,err2)) - - return avg,err - -print sys.argv -bwfile,intvfile,exts,nbins,outfile,outplot = sys.argv -avg, err = getExtendedBinScore(bwfile,intvfile,numpy.fromstring(nbins,sep=','),numpy.fromstring(exts,sep=',')) -out = open(outfile,'w') -numpy.savetxt(out, avg, fmt='%.6f', delimiter=' ', newline=' ') -out.write('\n') -numpy.savetxt(out, err, fmt='%.6f', delimiter=' ', newline=' ') -out.write('\n') -out.close() - -# plot -rscript = open("tmp.r","w") -rscript.write("options(warn=-1)\n") -rscript.write("x <- read.table('"+outfile+"')\n") -rscript.write("pdf('"+outplot+"')\n") -rscript.write("avg <- x[1,]\n") -rscript.write("err <- x[2,]\n") -rscript.write("print(x)\n") -rscript.write("ylim=c(min(avg-err),max(avg+err))\n") -rscript.write("xticks <- seq(ncol(x))\n") -rscript.write("plot(xticks,avg,ylab='average coverage',type='l',lwd=0,ylim=ylim)\n") -rscript.write("polygon(c(xticks,rev(xticks)),c(avg+err,rev(avg-err)),col='lightgreen',border=NA)\n") -rscript.write("lines(xticks,avg,type='l',lwd=1)\n") -rscript.write("dev.off()\n") -rscript.close() -os.system("R --vanilla < tmp.r") -os.system("rm tmp.r") -
--- a/interval/metaintv_ext.py Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,128 +0,0 @@ -''' -get binned score of intervals,allow extension -''' - -import os,sys,numpy -import string, random - -from resize import * - -from bx.bbi.bigwig_file import BigWigFile - -def binning(x,n): - # make n bin of x - y = numpy.zeros(n,dtype=float) - if len(x) == 0: - return y - step = float(len(x))/n - for k in range(n): - i = int(step*k) - j = int(step*(k+1)) + 1 - y[k] = x[i:j].mean() - #print i,j,k,y[k] - return y - -def getBinnedScore(bwfile,intvfile,nbin): - ''' - get binned average and std - ''' - fbw = open(bwfile) - bw = BigWigFile(file=fbw) - fin = open(intvfile) - avg = numpy.zeros(nbin) - sqr = numpy.zeros(nbin) - N = 0 - for line in fin: - #print N - #chrom,start,end,name,score,strand - flds = line.strip().split('\t') - #get the score at base resolution as an array - scores = bw.get_as_array(flds[0],int(flds[1]),int(flds[2])) - if scores == None: - print 'not found:\t',N,line - continue - N = N + 1 - #print line,scores - # reverse if on minus strand - if flds[5] == '-': - scores = scores[::-1] - # no score = 0 - scores = numpy.nan_to_num(scores) - # bin the data - binned = binning(scores,nbin) - avg = avg + binned - sqr = sqr + binned**2 - # compute avg and std - avg = avg / N - err = ((sqr/N-avg**2)**0.5)/(N**0.5) - return avg,err,N - -def getExtendedBinScore(bwfile,intvfile,nbins,exts): - ''' - nbins: n1,n2,n3 - exts: l1,l2,l3,l4 - ''' - avg = [] - err = [] - tmpfile = "".join(random.sample(string.letters+string.digits, 8)) - if exts[0]>0 or exts[1]>0: - print 'make left extension' - resize(intvfile,tmpfile,'start-'+str(exts[0]),'start+'+str(exts[1]),'stranded') - print 'compute binned average' - avg,err,N = getBinnedScore(bwfile,tmpfile,nbins[0]) - print 'regions used:',N - print 'make center region' - resize(intvfile,tmpfile,'start+'+str(exts[1]),'end-'+str(exts[2]),'stranded') - print 'compute binned average' - avg1,err1,N = getBinnedScore(bwfile,tmpfile,nbins[1]) - print 'regions used:',N - avg = numpy.concatenate((avg,avg1)) - err = numpy.concatenate((err,err1)) - if exts[2]>0 or exts[3]>0: - print 'make right region' - resize(intvfile,tmpfile,'end-'+str(exts[2]),'end+'+str(exts[3]),'stranded') - print 'compute binned average' - avg2,err2,N = getBinnedScore(bwfile,tmpfile,nbins[2]) - print 'regions used:',N - avg = numpy.concatenate((avg,avg2)) - err = numpy.concatenate((err,err2)) - os.system('rm '+tmpfile) - return avg,err - -prog,bwfile,intvfile,exts,nbins,outfile,outplot = sys.argv -nbins = numpy.fromstring(nbins,dtype=int,sep=',') -exts = numpy.fromstring(exts,dtype=int,sep=',') -avg, err = getExtendedBinScore(bwfile,intvfile,nbins,exts) -print 'save data' -out = open(outfile,'w') -numpy.savetxt(out, avg, fmt='%.6f', delimiter=' ', newline=' ') -out.write('\n') -numpy.savetxt(out, err, fmt='%.6f', delimiter=' ', newline=' ') -out.write('\n') -out.close() - -print 'plot' -start = exts[0]*nbins[0]/(exts[0]+exts[1]) -end = nbins[0]+nbins[1]+exts[2]*nbins[2]/(exts[2]+exts[3]) -#print start,end -rscript = open("tmp.r","w") -rscript.write("options(warn=-1)\n") -rscript.write("x <- read.table('"+outfile+"')\n") -rscript.write("pdf('"+outplot+"')\n") -rscript.write("avg <- x[1,]\n") -rscript.write("err <- x[2,]\n") -#rscript.write("print(x)\n") -rscript.write("ylim=c(min(avg-err),max(avg+err))\n") -rscript.write("xticks <- seq(ncol(x))\n") -#rscript.write("print(xticks)\n") -rscript.write("plot(xticks,avg,xlab='',ylab='average coverage',type='l',lwd=0,ylim=ylim,xaxt='n')\n") -rscript.write("axis(1, at=c(min(xticks),"+str(start)+","+str(end)+",max(xticks)),labels=c(-"+str(exts[0])+",0,0,"+str(exts[3])+"), las=2)\n") -rscript.write("polygon(c(xticks,rev(xticks)),c(avg+err,rev(avg-err)),col='lightgreen',border=NA)\n") -rscript.write("lines(xticks,avg,type='l',lwd=1)\n") -rscript.write("lines(c(min(xticks),max(xticks)),c(0,0),lwd=2)\n") -rscript.write("lines(c("+str(start)+","+str(end)+"),c(0,0),lwd=10)\n") -rscript.write("dev.off()\n") -rscript.close() -os.system("R --vanilla --slave < tmp.r") -os.system("rm tmp.r") -
--- a/interval/metaintv_ext.xml Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,23 +0,0 @@ -<tool id="metaintv_ext" name="aggregrate binned-average"> - <description>from bigwig (allow extension)</description> - <command interpreter="python">metaintv_ext.py $bwfile $intvfile $exts $nbins $outfile $outplot > $outlog </command> - <inputs> - <param name="intvfile" format="interval" type="data" label="Interval file"/> - <param name="bwfile" format="bigwig" type="data" label="BigWig file"/> - <param name="exts" type="text" size="80" value="100,50,50,100" label="extensions"/> - <param name="nbins" type="text" size="80" value="10,10,10" label="number of bins"/> - - </inputs> - <outputs> - <data format="txt" name="outlog" label="${tool.name} on ${on_string}[log]"/> - <data format="tabular" name="outfile" label="${tool.name} on ${on_string}[data]"/> - <data format="pdf" name="outplot" label="${tool.name} on ${on_string}[plot]"/> - </outputs> - <help> - -.. class:: infomark - -To be added - -</help> -</tool>
--- a/interval/phastCons.xml Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,48 +0,0 @@ -<tool id="getScore" name="conservation"> - <description>phastCons or phyloP,vertebrate30way</description> - <command interpreter="python">getGenomicScore.py $input $output $score_type $score_path $nbin $strand $outplot $span</command> - <inputs> - <param name="input" format="interval" type="data" label="Interval file"/> - <param name="score_path" type="select" label="Select score" > - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/mm8/phastcons" >mm8-phastCons17way</option> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/mm9/phastcon" selected="true">mm9-phastCons30way-vertebrate</option> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/mm9/phyloP30way">mm9-phyloP30way-vertebrate</option> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/hg18/phastCons28wayPlacMam">hg18-phastCons28wayPlacMam</option> </param> - <param name="score_type" type="select" label="Select score summary type" > - <option value="mean" selected="true">mean</option> - <option value="max">maximum</option> - <option value="min">minimum</option> - <option value="std">standard deviation</option> - <option value="coverage">coverage:fraction covered</option> - </param> - <param name="nbin" type="integer" value="1" label="number of bins"/> - <param name="span" size="10" type="float" value="0.1" label="loess span: smoothing parameter" help="value less then 0.1 disables smoothing"/> - <param name="strand" type="integer" value="0" label="Specify the strand column" help="leave 0 to ignore strand information. Only matters if using more than 1 bin"/> - </inputs> - <outputs> - <data format="pdf" name="outplot" label="${tool.name} on ${on_string}[plot]"/> - <data format="interval" name="output" label="${tool.name} on ${on_string}[data]"/> - </outputs> - <help> - -.. class:: infomark - -The score for each interval is added as a new column appended at the end of the original file . - -**Example** - -If your original data has the following format: - -+-----+-----+---+------+ -|chrom|start|end|other2| -+-----+-----+---+------+ - -and you choose to return the mean of phastCons scores, your output will look like this: - -+-----+-----+---+------+----+ -|chrom|start|end|other2|mean| -+-----+-----+---+------+----+ - - -</help> -</tool>
--- a/interval/random_interval.py Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,96 +0,0 @@ -''' -simulate a random interval set that mimics the size and strand of a reference set -''' - -def inferSizeFromRefBed(filename): - ''' - read reference interval set, get chrom size information - ''' - chrSize = {} - f = open(filename) - for line in f: - flds = line.strip().split('\t') - if not chrSize.has_key(flds[0]): - chrSize[flds[0]] = int(flds[2]) - elif chrSize[flds[0]] < int(flds[2]): - chrSize[flds[0]] = int(flds[2]) - f.close() - return chrSize - -def getChrSize(filename): - chrSize = {} - f = open(filename) - for line in f: - flds = line.strip().split() - if len(flds) >1: - chrSize[flds[0]] = int(flds[1]) - f.close() - return chrSize - -def makeWeightedChrom(chrSize): - ''' - make a list of chr_id, the freq is proportional to its length - ''' - - genome_len = 0 - - for chrom in chrSize: - chrom_len = chrSize[chrom] - genome_len += chrom_len - - weighted_chrom = [] - for chrom in chrSize: - weight = int(round(1000*float(chrSize[chrom])/genome_len)) - weighted_chrom += [chrom]*weight - - return weighted_chrom - -def randomIntervalWithinChrom(infile,outfile,chrSize): - ''' - ''' - fin = open(infile) - fout = open(outfile,'w') - n = 0 - for line in fin: - n = n + 1 - flds = line.strip().split('\t') - interval_size = int(flds[2]) - int(flds[1]) - flds[1] = str(random.randint(0,chrSize[flds[0]]-interval_size)) - flds[2] = str(int(flds[1])+interval_size) - fout.write('\t'.join(flds)+'\n') - fin.close() - fout.close() - -def randomIntervalAcrossChrom(infile,outfile,chrSize,weighted_chrom): - ''' - ''' - fin = open(infile) - fout = open(outfile,'w') - n = 0 - for line in fin: - n = n + 1 - flds = line.strip().split('\t') - interval_size = int(flds[2]) - int(flds[1]) - # find a random chrom - flds[0] = weighted_chrom[random.randint(0, len(weighted_chrom) - 1)] - flds[1] = str(random.randint(0,chrSize[flds[0]]-interval_size)) - flds[2] = str(int(flds[1])+interval_size) - fout.write('\t'.join(flds)+'\n') - fin.close() - fout.close() - -import sys,random -def main(): - # python random_interval.py test100.bed testout.bed across human.hg18.genome - - reference_interval_file = sys.argv[1] - output_file = sys.argv[2] - across_or_within_chrom = sys.argv[3] # within or across - chrom_size_file = sys.argv[4] - chrSize = getChrSize(chrom_size_file) - print chrSize.keys() - if across_or_within_chrom == 'within': - randomIntervalWithinChrom(reference_interval_file,output_file,chrSize) - else: - randomIntervalAcrossChrom(reference_interval_file,output_file,chrSize,makeWeightedChrom(chrSize)) -main()
--- a/interval/random_interval.xml Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,45 +0,0 @@ -<tool id="randominterval" name="shuffle intervals"> - <description>weight chromosome by length</description> - <command interpreter="python">random_interval.py $input $output $within $genome </command> - <inputs> - <param name="input" format="interval" type="data" label="reference interval file to mimic"/> - <param name="within" label="randomize within chromosome" help="If checked, for each original interval will move it to a random position in the SAME chromosome. The default is to move it to any chromosome (chance proportional to chromosome size)" type="boolean" truevalue="within" falsevalue="across" checked="False"/> - <param name="genome" type="select" label="Select genome"> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/chrsize/mouse.mm9.genome" selected="true">mm9</option> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/chrsize/mouse.mm8.genome">mm8</option> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/chrsize/human.hg18.genome">hg18</option> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/chrsize/human.hg19.genome">hg19</option> - </param> - </inputs> - <outputs> - <data format="interval" name="output" /> - </outputs> - <help> - - -**What it does** - -This tool will generate a set of intervals randomly distributed in the genome, mimicking the size distribution of the reference set. The same number of intervals are generated. - - -**How it works** - -For each interval in the reference set, the script picks a random position as the new start in the genome, and then pick the end such that the size of the random interval is the same as the original one. The default setting is to move the interval to any chromosome, with the probability proportional to the size/length of the chromosome. You can have it pick a random position in the same chromosome, such that in the randomized set each chromosome has the same number of intervals as the reference set. The size of the chromosome can be either learned from the reference set (chromosome size = max(interval end)) or read from a chromosome size file. When learning from the reference set, only regions spanned by reference intervals are used to generate random intervals. Regions (may be an entire chromosome) not covered by the reference set will not appear in the output. - -**Chromosome size file** - -Chromosome size files for hg18,hg19,mm8,and mm9 can be found in 'Shared Data'. To use those files, select the correct one and import into to the history, then the file will be listed in the drop-down menu of this tool. You can also make your own chromosme size file: each line specifies the size of a chromosome (tab-delimited): - -chr1 92394392 - -chr2 232342342 - - -You can use the following script from UCSC genome browser to download chromosome size files for other genomes: - -http://hgdownload.cse.ucsc.edu/admin/exe/linux.x86_64/fetchChromSizes - - - </help> - -</tool>
--- a/interval/removeDuplicate.xml Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,10 +0,0 @@ -<tool id="removeDuplicate" name="remove duplicate"> - <description>lines</description> - <command> cat $input | sort | uniq > $output </command> - <inputs> - <param name="input" format="txt" type="data" label="Original file"/> - </inputs> - <outputs> - <data format="input" name="output" /> - </outputs> -</tool>
--- a/interval/resize.py Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,57 +0,0 @@ -''' -change start and end of interval files -''' - -import sys - -def resize(infile,outfile,expr_start,expr_end,strand): - fin = open(infile) - fout = open(outfile,'w') - if expr_start[0:3] == 'end': - c1 = 2 - n1 = int(expr_start[3:]) - else: - c1 = 1 - n1 = int(expr_start[5:]) - if expr_end[0:3] == 'end': - c2 = 2 - n2 = int(expr_end[3:]) - else: - c2 = 1 - n2 = int(expr_end[5:]) - if strand == 'ignore': - for line in fin: - flds = line.strip().split('\t') - start = int(flds[c1]) + n1 - if start >= 0: - end = int(flds[c2]) + n2 - if end >= start: - flds[1] = str(start) - flds[2] = str(end) - fout.write('\t'.join(flds)+'\n') - else:# upstream downstream - for line in fin: - flds = line.strip().split('\t') - if flds[5] == '+': - start = int(flds[c1]) + n1 - if start >= 0: - end = int(flds[c2]) + n2 - if end >= start: - flds[1] = str(start) - flds[2] = str(end) - fout.write('\t'.join(flds)+'\n') - else: # on the - strand - start = int(flds[3-c2]) - n2 # end=end+n2 - if start >= 0: - end = int(flds[3-c1]) - n1 - if end >= start: - flds[1] = str(start) - flds[2] = str(end) - fout.write('\t'.join(flds)+'\n') - fin.close() - fout.close() - -if __name__ == "__main__": - resize(sys.argv[1],sys.argv[2],sys.argv[3],sys.argv[4],sys.argv[5]) - # python resize.py in.bed out.bed start-3 end+5 both - # python resize.py <input.bed> <output.bed> expr_start expr_end strand(both/+/-)
--- a/interval/resize.xml Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,32 +0,0 @@ -<tool id="resize" name="resize"> - <description>intervals</description> - <command interpreter="python">resize.py $infile $outfile $expr_start $expr_end $strand </command> - <inputs> - <param name="infile" format="interval" type="data" label="Original file"/> - <param name="expr_start" size="20" type="text" value="start-0" label="start=" help="e.g. start+10, start-10, end-100"/> - <param name="expr_end" size="20" type="text" value="end+0" label="end=" help="e.g. end-100, start+10"/> - <param name="strand" label="Enforce strandness" type="boolean" truevalue="strand" falsevalue="ignore" checked="False"/> - </inputs> - <outputs> - <data format="input" name="outfile" /> - </outputs> - <help> - -**What it does** - -This tool changes start and end of each row in an interval file. When strandness is enforced, chromosome start and end are treated as the 5' and 3' end for intervals on the '+' strand, and the opposite for intervals on the '-' strand. In the expression such as 'start=start-1000', 'start' and 'end' are interpreted as the 5' and 3' end, respectively, and the operator '+' and '-' means moving downsteam and upsteam, respectively. For example, when enforcing strandness, - -**start=start-1000**: extend 1000 bp on the 5' end (moving start upstream) - -**start=start+1000**: trancate 1000 bp on the 5' end (moving start downsteam) - -**end=end+1000**: extend 1000 bp on the 3' end (moving end downsteam) - -**end=start+1000**: moving the end to 1000 bp downsteam of the start (return the first 1000 bp on the 5' end) - -**end=start+1**: taking the 5' end of the interval - -**start=end-1**: taking the 3' end of the interval - - </help> -</tool>
--- a/interval/shuffleBed.py Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,107 +0,0 @@ -''' -simulate a random interval set that mimics the size and strand of a reference set -''' - -def inferSizeFromRefBed(filename,header): - ''' - read reference interval set, get chrom size information - ''' - chrSize = {} - f = open(filename) - if header: - header = f.readline() - for line in f: - flds = line.strip().split('\t') - if not chrSize.has_key(flds[0]): - chrSize[flds[0]] = int(flds[2]) - elif chrSize[flds[0]] < int(flds[2]): - chrSize[flds[0]] = int(flds[2]) - f.close() - return chrSize - -def getChrSize(filename): - chrSize = {} - f = open(filename) - for line in f: - flds = line.strip().split('\t') - if len(flds) >1: - chrSize[flds[0]] = int(flds[1]) - f.close() - return chrSize - -def makeWeightedChrom(chrSize): - ''' - make a list of chr_id, the freq is proportional to its length - ''' - - genome_len = 0 - - for chrom in chrSize: - chrom_len = chrSize[chrom] - genome_len += chrom_len - - weighted_chrom = [] - for chrom in chrSize: - weight = int(round(1000*float(chrSize[chrom])/genome_len)) - weighted_chrom += [chrom]*weight - - return weighted_chrom - -def randomIntervalWithinChrom(infile,outfile,chrSize,header): - ''' - ''' - fin = open(infile) - if header: - header = fin.readline() - fout = open(outfile,'w') - n = 0 - for line in fin: - n = n + 1 - flds = line.strip().split('\t') - interval_size = int(flds[2]) - int(flds[1]) - rstart = random.randint(0,chrSize[flds[0]]-interval_size) - fout.write(flds[0]+'\t'+str(rstart)+'\t'+str(rstart+interval_size)+'\t'+str(n)+'\t0\t+\n') - fin.close() - fout.close() - -def randomIntervalAcrossChrom(infile,outfile,chrSize,weighted_chrom,header): - ''' - ''' - fin = open(infile) - if header: - header = fin.readline() - fout = open(outfile,'w') - n = 0 - for line in fin: - n = n + 1 - flds = line.strip().split('\t') - interval_size = int(flds[2]) - int(flds[1]) - # find a random chrom - flds[0] = weighted_chrom[random.randint(0, len(weighted_chrom) - 1)] - # random start in the chrom - rstart = random.randint(0,chrSize[flds[0]]-interval_size) - fout.write(flds[0]+'\t'+str(rstart)+'\t'+str(rstart+interval_size)+'\t'+str(n)+'\t0\t+\n') - fin.close() - fout.close() - -import sys,random -def main(): - # python random_interval.py test100.bed testout.bed across header human.hg18.genome - - reference_interval_file = sys.argv[1] - output_file = sys.argv[2] - across_or_within_chrom = sys.argv[3] # within or across - if sys.argv[4] == 'header': - header = True - else: - header = False - if len(sys.argv) == 6: - chrom_size_file = sys.argv[5] - chrSize = getChrSize(chrom_size_file) - else: - chrSize = inferSizeFromRefBed(reference_interval_file,header) - if across_or_within_chrom == 'within': - randomIntervalWithinChrom(reference_interval_file,output_file,chrSize,header) - else: - randomIntervalAcrossChrom(reference_interval_file,output_file,chrSize,makeWeightedChrom(chrSize),header) -main()
--- a/interval/shuffleBed.xml Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,43 +0,0 @@ -<tool id="shufflebed" name="shuffleBed"> - <description>chromosome not weighted by length</description> - <command>shuffleBed -i $input -g $genome $chrom > $outfile - #if $limit.limit_select=="include": - -incl $limitfile - #else if $limit.limit_select=="exclude": - -excl $limitfile - #end if - </command> - <inputs> - <param name="input" format="bed,gff,vcf" type="data" label="Original intervals (BED/GFF/VCF)" /> - <param name="genome" type="select" label="Select genome"> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/chrsize/mouse.mm9.genome" selected="true">mm9</option> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/chrsize/mouse.mm8.genome">mm8</option> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/chrsize/human.hg18.genome">hg18</option> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/chrsize/human.hg19.genome">hg19</option> - </param> - <param name="chrom" label="keep intervals on the same chromosome?" type="boolean" truevalue="-chrom" falsevalue="" checked="False"/> - <conditional name="limit"> - <param name="limit_select" type="select" label="restrictions for the shuffling" help="Instead of randomly placing features in a genome, one can specify regions features should or should not be randomly placed (e.g. genes.bed or repeats.bed)."> - <option value="none" selected="true">None</option> - <option value="include">within specified regions</option> - <option value="exclude">outside specified regions</option> - </param> - <when value="include"> - <param name="limitfile" type="data" format="interval" label="specify regions"/> - </when> - <when value="exclude"> - <param name="limitfile" type="data" format="interval" label="specify regions"/> - </when> - </conditional> - </inputs> - <outputs> - <data format="input" name="outfile" /> - </outputs> - <help> - -.. class:: infomark - -Every chromosome are choosed with equal probability, regardless their size. Please use the tool 'random intervals' instead for general randomization. - - </help> -</tool>
--- a/interval/spatial_proximity.py Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,36 +0,0 @@ - -import os,sys - -file1 = sys.argv[1] -file2 = sys.argv[2] -genome = sys.argv[3] -outplot = sys.argv[4] -outlog = sys.argv[5] -outbed = sys.argv[6] - -strandness = '' -if len(sys.argv) > 7: - strandness = sys.argv[7] - -# real distance -cmd = 'closestBed -a '+file1+' -b '+file2 + ' '+strandness + ' -d -t first > '+outbed -os.system(cmd) -# shuffle -cmd = 'shuffleBed -chrom -g '+genome+' -i '+file1+'> shuffled.bed' -os.system(cmd) -# shuffled distance -cmd = 'closestBed -a shuffled.bed -b '+file2 + ' '+strandness + ' -d -t first > shuffled.dist' -os.system(cmd) - - -# test in R -r = open('tmp.r','w') -r.write("options(warn=-1)\n") -r.write("source('/Users/xuebing/galaxy-dist/tools/mytools/cdf.r')\n") -r.write("x = read.table('"+outbed+"',sep='\t')\n") -r.write("y = read.table('shuffled.dist',sep='\t')\n") -r.write("pdf('"+outplot+"')\n") -r.write("mycdf(list(log10(1+x[,ncol(x)]),log10(1+y[,ncol(y)])),'spatial distance',c('real','shuffled'),'topleft','log10 distance','')\n") -r.write("dev.off()\n") -r.close() -os.system("R --vanilla < tmp.r >"+outlog)
--- a/interval/spatial_proximity.xml Sat Mar 31 08:24:32 2012 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,32 +0,0 @@ -<tool id="spatialproximity" name="spatial proximity"> - <description>of two interval sets</description> - <command interpreter="python">spatial_proximity.py $inputa $inputb $genome $outplot $outlog $outbed $strandness - </command> - <inputs> - <param name="inputa" format="interval" type="data" label="Interval set 1" /> - <param name="inputb" format="interval" type="data" label="Interval set 2" /> - <param name="genome" type="select" label="Select genome"> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/chrsize/mouse.mm9.genome" selected="true">mm9</option> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/chrsize/mouse.mm8.genome">mm8</option> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/chrsize/human.hg18.genome">hg18</option> - <option value="/Users/xuebing/galaxy-dist/tool-data/genome/chrsize/human.hg19.genome">hg19</option> - </param> - <param name="strandness" type="select" label="Strand requirement" > - <option value="" selected="true"> none </option> - <option value="-s" > -s: closest feature on the same strand</option> - <option value="-S" > -S: closest feature on the opposite strand </option> - </param> - </inputs> - <outputs> - <data format="input" name="outbed" label="${tool.name} on ${on_string}: (bed)" /> - <data format="pdf" name="outplot" label="${tool.name} on ${on_string}: (plot)" /> - <data format="txt" name="outlog" label="${tool.name} on ${on_string}: (log)" /> - </outputs> - <help> - -.. class:: infomark - -for each feature in the first interval set, find the closest in the second set, then compared the distance distribution to shuffled set 1. - - </help> -</tool>