# HG changeset patch # User pjbriggs # Date 1435662485 14400 # Node ID f411ce97a351f1253b363add23b5e183d046a04c Uploaded initial version 1.0.2-2 diff -r 000000000000 -r f411ce97a351 README.rst --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/README.rst Tue Jun 30 07:08:05 2015 -0400 @@ -0,0 +1,84 @@ +CEAS: Cis-regulatory Element Annotation System +============================================== + +Galaxy tool wrapper for the CEAS (Cis-regulatory Element Annotation System), which +can be used to annotate intervals and scores with genome features. + +This tool uses the Cistrome version of the package, which provides two versions of +the core program: in addition to the ``ceas`` program (the same as that available +from the main CEAS website), it also includes the ``ceasBW`` program (which can handle +bigwig input). + +The tool assumes that the ``ceas`` and ``ceasBW`` programs are on the Galaxy user's +path. + +The official CEAS website is at: + +- http://liulab.dfci.harvard.edu/CEAS/index.html + +The Cistrome version can be found via + +- https://bitbucket.org/cistrome/cistrome-applications-harvard/overview + +Automated installation +====================== + +Installation via the Galaxy Tool Shed will take care of installing the tool wrapper +and the CEAS programs, and setting the appropriate environment variables. + +In addition this will also install a data manager which can be used to install +reference GDB data files necessary for the tool. + +Manual Installation +=================== + +There are two files to install: + +- ``ceas_wrapper.xml`` (the Galaxy tool definition) +- ``ceas_wrapper.sh`` (the shell script wrapper) + +The suggested location is in a ``tools/ceas/`` folder. You will then +need to modify the ``tools_conf.xml`` file to tell Galaxy to offer the tool +by adding the line: + + + +You also need to make a copy of the ``ceas.loc`` file (a sample version is +provided here) which points to the available GDB files for different genomes. + +This file should be placed in the ``tool-data`` directory of your Galaxy +installation. + +Reference Data +============== + +CEAS requires reference data in the form of GDB files (essentially, SQLite database +files) containing the RefSeq genes for the genome in question. + +A limited number of GDB files are available for download from the CEAS website; to +make new ones, see the section "Build a sqlite3 file with a gene annotation table +and genome background annotation for CEAS" in the CEAS manual: + +- http://liulab.dfci.harvard.edu/CEAS/usermanual.html + +History +======= + +========== ====================================================================== +Version Changes +---------- ---------------------------------------------------------------------- +1.0.2-2 - Major updates to fix various bugs, add tests and enable ceasBW to + be used without an existing chromosome sizes file. +1.0.2-1 - Modified to work with Cistrome-version of CEAS (includes additional + 'ceasBW' program which can take bigWig input) +1.0.2-0 - Initial version. +========== ====================================================================== + +Developers +========== + +This tool is developed on the following GitHub repository: +https://github.com/fls-bioinformatics-core/galaxy-tools/tree/master/ceas + +For making the "Galaxy Tool Shed" http://toolshed.g2.bx.psu.edu/ tarball I use +the ``package_ceas.sh`` script. diff -r 000000000000 -r f411ce97a351 ceas_wrapper.sh --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/ceas_wrapper.sh Tue Jun 30 07:08:05 2015 -0400 @@ -0,0 +1,113 @@ +#!/bin/sh -e +# +# Wrapper script to run CEAS as a Galaxy tool +# +# This runs the Cistrome versions of CEAS, which provides two executables: +# - ceas (same as the "official" version) +# - ceasBW (modified version that accepts a bigwig file as input) +# +# Usage: ceas_wrapper.sh $BED_IN $GDB_IN $LOG_OUT $PDF_OUT $XLS_OUT [OPTIONS] +# +# Initialise +CEAS=ceas +# +# Process command line +echo $* +BED_IN=$1 +GDB_IN=$2 +LOG_OUT=$3 +PDF_OUT=$4 +XLS_OUT=$5 +# +# Initialise other variables +EXTRA_BED_IN= +# +# Collect remaining args +OPTIONS= +while [ ! -z "$6" ] ; do + if [ "$6" == "--bigwig" ] ; then + # Bigwig input, need to use 'ceasBW' + CEAS=ceasBW + OPTIONS="$OPTIONS --bigwig" + elif [ "$6" == "--length" ] ; then + # Need a chrom sizes file + chrom_sizes=$7 + if [ ! -f "$chrom_sizes" ] ; then + # If chrom sizes file doesn't already exist then attempt to + # download the data from UCSC + echo "WARNING no file $chrom_sizes" + dbkey=$(echo $(basename $chrom_sizes) | cut -d'.' -f1) + if [ $dbkey == '?' ] ; then + # DBkey not set, this is fatal + echo "ERROR genome build not set, cannot get sizes for '?'" >&2 + echo "Assign a genome build to your input dataset and rerun" >&2 + exit 1 + fi + # Fetch the sizes using fetchChromSizes + echo -n "Attempting to download chromosome sizes for $dbkey..." + chrom_sizes=$(basename $chrom_sizes) + fetchChromSizes $dbkey >$chrom_sizes 2>/dev/null + if [ $? -ne 0 ] ; then + echo "failed" + echo "ERROR unable to fetch data for ${dbkey}" >&2 + echo "Please check the genome build associated with your input dataset" >&2 + echo "or update your Galaxy instance to include an appropriate .len file" >&2 + exit 1 + else + echo "ok" + fi + fi + OPTIONS="$OPTIONS --length $chrom_sizes" + shift + else + OPTIONS="$OPTIONS $6" + fi + shift +done +# +# Convenience variables for local files +base_name="ceas" +log_file=${base_name}.log +pdf_report=${base_name}.pdf +xls_file=${base_name}.xls +# +# Get CEAS version +echo Running $CEAS +$CEAS --version >$log_file 2>/dev/null +# +# Construct and run CEAS command line +ceas_cmd="$CEAS --name $base_name $OPTIONS -g $GDB_IN -b $BED_IN" +echo "Running $ceas_cmd" +$ceas_cmd >>$log_file 2>&1 +status=$? +if [ $status -ne 0 ] ; then + echo "Error: log file tail:" + tail $log_file + echo "ERROR $CEAS exited with non-zero code: $status" >&2 + exit $status +fi +# +# Move outputs to final destination +if [ -e $log_file ] ; then + echo "Moving $log_file to $LOG_OUT" + /bin/mv $log_file $LOG_OUT +else + echo ERROR failed to make log file >&2 + exit 1 +fi +if [ -e $xls_file ] ; then + echo "Moving $xls_file to $XLS_OUT" + /bin/mv $xls_file $XLS_OUT +else + echo ERROR failed to generate XLS file >&2 + exit 1 +fi +if [ -e $pdf_report ] ; then + echo "Moving $pdf_report to $PDF_OUT" + /bin/mv $pdf_report $PDF_OUT +else + echo ERROR failed to generate PDF report >&2 + exit 1 +fi +# +# Done diff -r 000000000000 -r f411ce97a351 ceas_wrapper.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/ceas_wrapper.xml Tue Jun 30 07:08:05 2015 -0400 @@ -0,0 +1,160 @@ + + Annotate intervals and scores with genome features + + python_mysqldb + bx_python + cistrome_ceas + ucsc_fetchChromSizes + R + + ceas --version 2>&1 | tail -1 + ceas_wrapper.sh + $bed_file ${gdb_file.fields.path} + $log_output $pdf_report $xls_output + #if (str($wig_file) != 'None') + #if (str($wig_file.ext) == 'bigwig') + --bigwig $wig_file + --length $GALAXY_DATA_INDEX_DIR/shared/ucsc/chrom/${bed_file.dbkey}.len + #else + --wig $wig_file + #end if + #end if + #if (str($extra_bed_file) != 'None') + --ebed $extra_bed_file + #end if + #if (str($span) and int(str($span)) > 0) + --span $span + #end if + --sizes $sizes_lower,$sizes_middle,$sizes_upper + --bisizes $bisizes_lower,$bisizes_upper + --pf-res $profiling_resolution + --rel-dist $relative_distance + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +**What it does** + +CEAS (Cis-regulatory Element Annotation System) is a tool for characterizing genome-wide +protein-DNA interaction patterns from ChIP-chip and ChIP-Seq of both sharp and broad +binding factors. It provides statistics on ChIP enrichment at important genome features +such as specific chromosome, promoters, gene bodies, or exons, and infers genes most +likely to be regulated by a binding factor. + +CEAS also enables biologists to visualize the average ChIP enrichment signals over +specific genomic features, allowing continuous and broad ChIP enrichment to be perceived +which might be too subtle to detect from ChIP peaks alone. + +**Usage** + +CEAS takes the following inputs: + + * BED file with discrete ChIP regions (for example, the 'summits' output from the MACS + peak caller) + * WIG or bigWIG file with a continuous ChIP enrichment signal + * Gene annotation table (provided as reference data) + +Optionally it can also take a BED file describing extra regions of interest (for example +non-coding regions). + +The analysis modules are: + + * **ChIP region annotation:** estimates the relative enrichment level of ChIP regions in + each gene feature with respect to the whole genome. + * **Gene-centered annotation:** identifies genes associated with ChIP regions to infer + the direct regulatory gene targets of the binding factor of interest. + * **Average signal profiling within/near important genomic features:** displays continuous + ChIP enrichment signal within/around important gene features to help visualize the + average binding patterns. + +**Background** + +This tool is compatible with the ceasBW version of CEAS from the Cistrome package +obtained from + +https://bitbucket.org/cistrome/cistrome-applications-harvard/overview + +(commit id d8c0751, datestamp 20140929). The CEAS code is under the +published-packages/CEAS/ subdirectory. + +Cistrome data files and documentation can be found at + +http://liulab.dfci.harvard.edu/CEAS/index.html + +The CEAS user manual is available at http://liulab.dfci.harvard.edu/CEAS/usermanual.html + + + + 10.1093/bioinformatics/btp479 + + diff -r 000000000000 -r f411ce97a351 data_manager/data_manager_ceas_fetch_annotations.py --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/data_manager/data_manager_ceas_fetch_annotations.py Tue Jun 30 07:08:05 2015 -0400 @@ -0,0 +1,153 @@ +#!/usr/bin/env python +# + +import sys +import os +import subprocess +import tempfile +import optparse +import urllib2 +import gzip +import shutil + +from galaxy.util.json import from_json_string, to_json_string + +# Download file from specified URL and put into local subdir + +if __name__ == '__main__': + #Parse Command Line + parser = optparse.OptionParser() + options,args = parser.parse_args() + print "options: %s" % options + print "args : %s" % args + if len(args) != 2: + p.error("Need to supply JSON file name and description text") + + # Read the JSON supplied from the data manager tool + # Results from this program will be returned via the + # same file + jsonfile = args[0] + params = from_json_string(open(jsonfile).read() ) + print "%s" % params + + # Extract the data from the input JSON + # See https://wiki.galaxyproject.org/Admin/Tools/DataManagers/HowTo/Define?highlight=%28\bAdmin%2FTools%2FDataManagers\b%29 + # for example of JSON + # + # We want the values set in the data manager XML + dbkey = params['param_dict']['dbkey'] + description = args[1].strip() + identifier = params['param_dict']['unique_id'].strip() + # Where to put the output file + # Nb we have to make this ourselves, it doesn't exist by default + target_dir = params['output_data'][0]['extra_files_path'] + os.mkdir(target_dir) + + method = params['param_dict']['reference_source']['reference_source_selector'] + + # Dictionary for returning to data manager + data_manager_dict = {} + data_manager_dict['data_tables'] = dict() + + # Download from URL + if method == 'web': + url = params['param_dict']['reference_source']['annotation_url'] + print "Downloading: %s" % url + annotation_file_name = os.path.basename(url) + annotation_file_path = os.path.join(target_dir,annotation_file_name) + print "Annotation file name: %s" % annotation_file_name + print "Annotation file path: %s" % annotation_file_path + open(annotation_file_path,'wb').write(urllib2.urlopen(url).read()) + if annotation_file_name.endswith('.gz'): + # Uncompress + uncompressed_file = annotation_file_path[:-3] + open(uncompressed_file,'wb').write(gzip.open(annotation_file_path,'rb').read()) + # Remove gzipped file + os.remove(annotation_file_path) + annotation_file_name = os.path.basename(uncompressed_file) + annotation_file_path = uncompressed_file + # Update the identifier and description + if not identifier: + identifier = "%s_ceas_web" % dbkey + if not description: + description = "%s (%s)" % (os.path.splitext(annotation_file_name)[0],dbkey) + # Update the output dictionary + data_manager_dict['data_tables']['ceas_annotations'] = { + 'value': identifier, + 'dbkey': dbkey, + 'name': description, + 'path': annotation_file_name, + } + elif method == 'server': + # Pull in a file from the server + filename = params['param_dict']['reference_source']['annotation_filename'] + create_symlink = params['param_dict']['reference_source']['create_symlink'] + print "Canonical gene list file name: %s" % filename + print "Create symlink: %s" % create_symlink + target_filename = os.path.join(target_dir,os.path.basename(filename)) + if create_symlink == 'copy_file': + shutil.copyfile(filename,target_filename) + else: + os.symlink(filename,target_filename) + # Update the identifier and description + if not identifier: + identifier = "%s_%s" % (dbkey, + os.path.splitext(os.path.basename(filename))[0]) + if not description: + description = "%s: %s" % (dbkey, + os.path.splitext(os.path.basename(filename))[0]) + # Update the output dictionary + data_manager_dict['data_tables']['ceas_annotations'] = { + 'value': identifier, + 'dbkey': dbkey, + 'name': description, + 'path': os.path.basename(filename), + } + elif method == 'from_wig': + # Make a reference file from a wig file + wig_file = params['param_dict']['reference_source']['wig_file'] + gene_annotation = params['param_dict']['reference_source']['gene_annotation'] + target_filename = os.path.join(target_dir,"%s_%s.%s" % (dbkey, + os.path.basename(wig_file), + gene_annotation)) + print "Wig file: %s" % wig_file + print "Gene annotation: %s" % gene_annotation + print "Output file: %s" % os.path.basename(target_filename) + # Make a working directory + working_dir = tempfile.mkdtemp() + # Collect stderr in a file for reporting later + stderr_filen = tempfile.NamedTemporaryFile().name + # Build the command to run + cmd = "build_genomeBG -d %s -g %s -w %s -o %s" % (dbkey, + gene_annotation, + wig_file, + target_filename) + print "Running %s" % cmd + proc = subprocess.Popen(args=cmd,shell=True,cwd=working_dir, + stderr=open(stderr_filen,'wb')) + proc.wait() + # Copy stderr to stdout + with open(stderr_filen,'r') as fp: + sys.stdout.write(fp.read()) + # Update identifier and description + if not identifier: + identifier = "%s_%s_%s" % (dbkey, + gene_annotation, + os.path.basename(wig_file)) + if not description: + description = "%s %s from %s" % (dbkey, + gene_annotation, + os.path.basename(wig_file)) + # Update the output dictionary + data_manager_dict['data_tables']['ceas_annotations'] = { + 'value': identifier, + 'dbkey': dbkey, + 'name': description, + 'path': os.path.basename(target_filename), + } + else: + raise NotImplementedError("Method '%s' not implemented" % method) + + #save info to json file + open(jsonfile,'wb').write(to_json_string(data_manager_dict)) + diff -r 000000000000 -r f411ce97a351 data_manager/data_manager_ceas_fetch_annotations.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/data_manager/data_manager_ceas_fetch_annotations.xml Tue Jun 30 07:08:05 2015 -0400 @@ -0,0 +1,95 @@ + + + python_mysqldb + bx_python + cistrome_ceas + + Fetch and install annotation databases for CEAS + data_manager_ceas_fetch_annotations.py + "${out_file}" + "${description}" + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +.. class:: infomark + +**What it does** + +Adds a CEAS gene annotation table file to the *ceas_annotations"* data table. The +database file can be downloaded from the CEAS website, imported from a file on the +Galaxy server, or generated from a ``wig`` file in a Galaxy history. + +**Notice:** If you leave the identifier or description blank then they will be +generated automatically. + +------ + +.. class:: infomark + +**Fetching, uploading or creating gene annotation table files** + +The gene annotation table files are SQLite database files which are on the CEAS website: + + - http://liulab.dfci.harvard.edu/CEAS/usermanual.html + +The data manager allows you to fetch a pre-built table from the CEAS website; note +that these are based on the ``RefSeq`` annotation and are only available for a subset +of genome builds. + +To create an annotation table for a different genome build or a different annotation, +use the *Generated from wig* file option. This runs the CEAS utility ``build_genomeBG`` +to make a custom table from a wig file, which represents the genome background (e.g. +a wig file created from the ``control lambda`` bedgraph file output from MACS2). + +Alternatively if you already have an existing custom annotation file then this can be +imported from a path on the Galaxy server. + + diff -r 000000000000 -r f411ce97a351 data_manager_conf.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/data_manager_conf.xml Tue Jun 30 07:08:05 2015 -0400 @@ -0,0 +1,20 @@ + + + + + + + + + + + ${path} + ceas/${dbkey}/${path} + + ${GALAXY_DATA_MANAGER_DATA_PATH}/ceas/${dbkey}/${path} + abspath + + + + + diff -r 000000000000 -r f411ce97a351 test-data/ceas.loc --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/ceas.loc Tue Jun 30 07:08:05 2015 -0400 @@ -0,0 +1,1 @@ +galGal3_test galGal3 galGal3 ${__HERE__}/galGal3.refGene diff -r 000000000000 -r f411ce97a351 test-data/ceas_in.bed --- /dev/null Thu Jan 01 00:00:00 1970 +0000 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step=1000 span=1 +0.00000 +fixedStep chrom=chr26 start=4126452 step=1000 span=1 +20000.00000 +fixedStep chrom=chr26 start=4126695 step=1000 span=1 +0.00000 +fixedStep chrom=chr26 start=4127518 step=1000 span=1 +20000.00000 diff -r 000000000000 -r f411ce97a351 test-data/ceas_out1.log --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/ceas_out1.log Tue Jun 30 07:08:05 2015 -0400 @@ -0,0 +1,184 @@ +ceas -- 0.9.9.7 (package version 1.0.2) +INFO @ Tue, 23 Jun 2015 09:12:22: +# ARGUMENTS: +# name = ceas +# gene annotation table = galGal3.refGene +# BED file = ceas_in.bed +# WIG file = None +# extra BED file = None +# ChIP annotation = On +# gene-centered annotation = On +# average profiling = Off +# dump profiles = Off +# re-annotation for genome background (ChIP region annotation) = False +# promoter sizes (ChIP region annotation) = 1000,2000,3000 bp +# downstream sizes (ChIP region annotation) = 1000,2000,3000 bp +# bidrectional promoter sizes (ChIP region annotation) = 2500,5000 bp +# span size (gene-centered annotation) = 3000 bp +INFO @ Tue, 23 Jun 2015 09:12:22: #1 read the gene table... +INFO @ Tue, 23 Jun 2015 09:12:22: #2 read the bed file of ChIP regions... +INFO @ Tue, 23 Jun 2015 09:12:22: #3 perform gene-centered annotation... +INFO @ Tue, 23 Jun 2015 09:12:22: #4 See ceas.xls for gene-centered annotation! +INFO @ Tue, 23 Jun 2015 09:12:22: #5 read the pre-computed genome bg annotation... +INFO @ Tue, 23 Jun 2015 09:12:22: #6 perform ChIP region annotation... +INFO @ Tue, 23 Jun 2015 09:12:22: #7 write a R script of ChIP region annotation... + +R version 3.1.2 (2014-10-31) -- "Pumpkin Helmet" +Copyright (C) 2014 The R Foundation for Statistical Computing +Platform: x86_64-redhat-linux-gnu (64-bit) + +R is free software and comes with ABSOLUTELY NO WARRANTY. +You are welcome to redistribute it under certain conditions. +Type 'license()' or 'licence()' for distribution details. + + Natural language support but running in an English locale + +R is a collaborative project with many contributors. +Type 'contributors()' for more information and +'citation()' on how to cite R or R packages in publications. + +Type 'demo()' for some demos, 'help()' for on-line help, or +'help.start()' for an HTML browser interface to help. +Type 'q()' to quit R. + +> # ARGUMENTS: +> # name = ceas +> # gene annotation table = galGal3.refGene +> # BED file = ceas_in.bed +> # WIG file = None +> # extra BED file = None +> # ChIP annotation = On +> # gene-centered annotation = On +> # average profiling = Off +> # dump profiles = Off +> # re-annotation for genome background (ChIP region annotation) = False +> # promoter sizes (ChIP region annotation) = 1000,2000,3000 bp +> # downstream sizes (ChIP region annotation) = 1000,2000,3000 bp +> # bidrectional promoter sizes (ChIP region annotation) = 2500,5000 bp +> # span size (gene-centered annotation) = 3000 bp +> pdf("ceas.pdf",height=11.5,width=8.5) +> +> # 09:12:22 Tue, 23 Jun 2015 +> # +> # ChIP annotation +> # +> +> +> # +> # Chromosomal Distribution +> # +> +> par(mar=c(4, 4, 5, 3.8),oma=c(4, 2, 4, 2)) +> r0<-c(100.0) +> r1<-c(100.0) +> height<-rbind(r0,r1) +> names=c("26") +> mp<-barplot(height=height,names=names,beside=TRUE,horiz=TRUE,col=c("#5FA1C1","#EB9D86"),main="Chromosomal Distribution of ChIP Regions",xlab="Percentage %",ylab="Chromosome",border=FALSE,xlim=c(0.000000,183.333333),cex.names=1) +> text(x=c(100.0),y=mp[1,],label=c("100.0 %"),pos=4,offset=0.2,cex=0.9) +> text(x=c(100.0),y=mp[2,],label=c("100.0 % (<=4.9e-324)"),pos=4,offset=0.2,cex=0.9) +> legend("right",legend=c("Genome","ChIP (p-value)"),col=c("#5FA1C1","#EB9D86"),pch=15,bty="n") +> +> # +> # Promoter,Bipromoter,Downstream, Gene and Regions of interest +> # +> +> par(mfrow=c(4, 1),mar=c(4, 4, 5, 3.8),oma=c(4, 2, 4, 2)) +> r0<-c(1.8532425688606797, 3.616851183410451, 5.322318854623416) +> r1<-c(0.0, 0.0, 0.0) +> height<-rbind(r0,r1) +> names=c("<=1000 bp","<=2000 bp","<=3000 bp") +> mp<-barplot(height=height,names=names,beside=TRUE,horiz=FALSE,col=c("#5FA1C1","#EB9D86"),main="Promoter",ylab="Percentage %",border=FALSE,ylim=c(0.000000,9.757585),cex.names=1) +> text(x=mp[1,],y=c(1.8532425688606797, 3.616851183410451, 5.322318854623416),label=c("1.9 %","3.6 %","5.3 %"),pos=3,offset=0.2) +> text(x=mp[2,],y=c(0.0, 0.0, 0.0),label=c("0.000 % ++ (0.981)","0.000 % ++ (0.964)","0.000 % ++ (0.947)"),pos=3,offset=0.2) +> legend("topleft",legend=c("Genome","ChIP (p-value)"),col=c("#5FA1C1","#EB9D86"),pch=15,bty="n") +> r0<-c(0.03876062889120376, 0.03876062889120376) +> r1<-c(0.0, 0.0) +> height<-rbind(r0,r1) +> names=c("<=2500 bp","<=5000 bp") +> mp<-barplot(height=height,names=names,beside=TRUE,horiz=FALSE,col=c("#5FA1C1","#EB9D86"),main="Bidirectional Promoter",ylab="Percentage %",border=FALSE,ylim=c(0.000000,0.071061),cex.names=1) +> text(x=mp[1,],y=c(0.03876062889120376, 0.03876062889120376),label=c("0.04 %","0.04 %"),pos=3,offset=0.2) +> text(x=mp[2,],y=c(0.0, 0.0),label=c("0.000 % ++ (1.000)","0.000 % ++ (1.000)"),pos=3,offset=0.2) +> legend("topleft",legend=c("Genome","ChIP (p-value)"),col=c("#5FA1C1","#EB9D86"),pch=15,bty="n") +> r0<-c(1.8290171758036773, 3.4690762857627364, 4.980740812519683) +> r1<-c(0.0, 0.0, 0.0) +> height<-rbind(r0,r1) +> names=c("<=1000 bp","<=2000 bp","<=3000 bp") +> mp<-barplot(height=height,names=names,beside=TRUE,horiz=FALSE,col=c("#5FA1C1","#EB9D86"),main="Downstream",ylab="Percentage %",border=FALSE,ylim=c(0.000000,9.131358),cex.names=1) +> text(x=mp[1,],y=c(1.8290171758036773, 3.4690762857627364, 4.980740812519683),label=c("1.8 %","3.5 %","5.0 %"),pos=3,offset=0.2) +> text(x=mp[2,],y=c(0.0, 0.0, 0.0),label=c("0.000 % ++ (0.982)","0.000 % ++ (0.965)","0.000 % ++ (0.950)"),pos=3,offset=0.2) +> legend("topleft",legend=c("Genome","ChIP (p-value)"),col=c("#5FA1C1","#EB9D86"),pch=15,bty="n") +> r0<-c(0.2034933016788197, 1.3978051793890356, 2.359553283752029, 19.734005184234114, 23.694856949054) +> r1<-c(0.0, 0.0, 0.0, 0.0, 0.0) +> height<-rbind(r0,r1) +> names=c("5'UTR","3'UTR","Coding Exon","Intron","All") +> mp<-barplot(height=height,names=names,beside=TRUE,horiz=FALSE,col=c("#5FA1C1","#EB9D86"),main="Gene",ylab="Percentage %",border=FALSE,ylim=c(0.000000,43.440571),cex.names=1) +> text(x=mp[1,],y=c(0.2034933016788197, 1.3978051793890356, 2.359553283752029, 19.734005184234114, 23.694856949054),label=c("0.2 %","1.4 %","2.4 %","19.7 %","23.7 %"),pos=3,offset=0.2) +> text(x=mp[2,],y=c(0.0, 0.0, 0.0, 0.0, 0.0),label=c("0.000 % ++ (0.998)","0.000 % ++ (0.986)","0.000 % ++ (0.976)","0.000 % ++ (0.803)","0.000 % ++ (0.763)"),pos=3,offset=0.2) +> legend("topleft",legend=c("Genome","ChIP (p-value)"),col=c("#5FA1C1","#EB9D86"),pch=15,bty="n") +> +> # +> # Distribution of Genome and ChIP regions over cis-regulatory element +> # Note that the x may be modified for better graphics in case a value is too small +> # Thus, look at the labels of the pie chart to get the real percentage values +> # +> +> par(mfcol=c(2, 2),mar=c(3, 3, 4, 2.8),oma=c(4, 2, 4, 2)) +> x<-c(0.018532,0.017055,0.016037,0.017830,0.015092,0.014051,0.010000,0.013833,0.023014,0.192592,0.670292) +> pie(x=x,labels=c("1.9 %","1.7 %","1.6 %","1.8 %","1.5 %","1.4 %","0.2 %","1.4 %","2.3 %","19.3 %","67.0 %"),main="Genome",col=c("#445FA2","#EB9D86","#799F7A","#6C527F","#5FA1C1","#E8BB77","#A8C5EF","#FDCDB9","#C6E6B5","#F1D5EE","#B4E1F6"),clockwise=TRUE,border=FALSE,radius=0.9,cex=0.8,init.angle=90,density=100) +> x<-c(0.000000,1.000000) +> y<-c(0.000000,1.000000) +> plot(x, y,type="n",main="",xlab="",ylab="",frame=FALSE,axes=FALSE,xaxt="s",yaxt="s") +> legend("top",legend=c("Promoter (<=1000 bp): 1.9 %","Promoter (1000-2000 bp): 1.7 %","Promoter (2000-3000 bp): 1.6 %","Downstream (<=1000 bp): 1.8 %","Downstream (1000-2000 bp): 1.5 %","Downstream (2000-3000 bp): 1.4 %","5'UTR: 0.2 %","3'UTR: 1.4 %","Coding exon: 2.3 %","Intron: 19.3 %","Distal intergenic: 67.0 %"),col=c("#445FA2","#EB9D86","#799F7A","#6C527F","#5FA1C1","#E8BB77","#A8C5EF","#FDCDB9","#C6E6B5","#F1D5EE","#B4E1F6"),pch=15,bty="n") +> x<-c(0.010000,0.010000,0.010000,0.010000,0.010000,0.010000,0.010000,0.010000,0.010000,0.010000,1.000000) +> pie(x=x,labels=c("0.000 %","0.000 %","0.000 %","0.000 %","0.000 %","0.000 %","0.000 %","0.000 %","0.000 %","0.000 %","100.0 %"),main="ChIP",col=c("#445FA2","#EB9D86","#799F7A","#6C527F","#5FA1C1","#E8BB77","#A8C5EF","#FDCDB9","#C6E6B5","#F1D5EE","#B4E1F6"),clockwise=TRUE,border=FALSE,radius=0.9,cex=0.8,init.angle=90,density=100) +> x<-c(0.000000,1.000000) +> y<-c(0.000000,1.000000) +> plot(x, y,type="n",main="",xlab="",ylab="",frame=FALSE,axes=FALSE,xaxt="s",yaxt="s") +> legend("top",legend=c("Promoter (<=1000 bp): 0.000 %","Promoter (1000-2000 bp): 0.000 %","Promoter (2000-3000 bp): 0.000 %","Downstream (<=1000 bp): 0.000 %","Downstream (1000-2000 bp): 0.000 %","Downstream (2000-3000 bp): 0.000 %","5'UTR: 0.000 %","3'UTR: 0.000 %","Coding exon: 0.000 %","Intron: 0.000 %","Distal intergenic: 100.0 %"),col=c("#445FA2","#EB9D86","#799F7A","#6C527F","#5FA1C1","#E8BB77","#A8C5EF","#FDCDB9","#C6E6B5","#F1D5EE","#B4E1F6"),pch=15,bty="n") +> +> # +> # ChIP regions over the genome +> # +> +> par(mar=c(4, 4, 5, 3.8),oma=c(4, 2, 4, 2)) +> layout(matrix(c(1, 0, 2, 2), 2, 2, byrow = TRUE),widths=c(1, 1),heights=c(1, 5)) +> x<-c(0.000000,2.515610) +> y<-c(0.000000,1.000000) +> plot(x, y,type="n",main="Distribution of Peak Heights",xlab="",ylab="",xlim=c(0.000000,2.515610),ylim=c(0.000000,1.000000),frame=FALSE,xaxt="s",yaxt="n",cex=0.9) +> x<-c(0.000000,2.515610,2.515610,0.000000) +> y<-c(0.000000,0.000000,1.000000,1.000000) +> polygon(x,y,col=c("black")) +> x <- c(0.000000,0.169726,0.339451,0.509177,0.678903,0.848628,1.018354,1.188079,1.357805,1.527531,1.697256,1.866982,2.036708,2.206433,2.376159) +> y<-c(0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.800000) +> lines(x, y,xlim=c(0, 2.51561),ylim=c(0, 1),type="l",col=c("cyan"),lwd=2) +> x<-c(4119129.000000,4119130.000000) +> y<-c(0.855556,1.144444) +> plot(x, y,type="n",main="ChIP Regions (Peaks) over Chromosomes",xlab="Chromosome Size (bp)",ylab="Chromosome",xlim=c(4119129.000000,4119130.000000),ylim=c(0.855556,1.144444),frame=FALSE,xaxt="s",yaxt="n") +> start <- c(4119129) +> end <- c(4119130) +> vals <- c(2.51561) +> vals[vals > 2.51561] <- 2.51561 +> vals[vals < 0] <- 0 +> heights <- 0.288889 * ((vals - 0)/(2.51561 - 0)) + 0.855555555556 +> for (i in 1:length(heights)) { ++ polygon(x=c(start[i], end[i], end[i], start[i]), y=c(0.855555555556, 0.855555555556, heights[i], heights[i]), col=c("#CC0000"), border=c("#CC0000")) ++ } +> mtext("26",side=2,line=0,outer=FALSE,at=1.0) +> dev.off() +null device + 1 +> +INFO @ Tue, 23 Jun 2015 09:12:22: #... cong! See ceas.pdf for the graphical results of CEAS! diff -r 000000000000 -r f411ce97a351 test-data/ceas_out1.log.re_match --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/ceas_out1.log.re_match Tue Jun 30 07:08:05 2015 -0400 @@ -0,0 +1,184 @@ +ceas\ \-\-\ 0\.9\.9\.7\ $package\ version\ 1\.0\.2$ +INFO\ \ \@\ .* +\#\ ARGUMENTS\:\ +\#\ name\ \=\ ceas +\#\ gene\ annotation\ table\ \=\ .*galGal3\.refGene +\#\ BED\ file\ \=\ .* +\#\ WIG\ file\ \=\ None +\#\ extra\ BED\ file\ \=\ None +\#\ ChIP\ annotation\ \=\ On +\#\ gene\-centered\ annotation\ \=\ \ On +\#\ average\ profiling\ \=\ Off +\#\ dump\ profiles\ \=\ Off +\#\ re\-annotation\ for\ genome\ background\ $ChIP\ region\ annotation$\ \=\ False +\#\ promoter\ sizes\ $ChIP\ region\ annotation$\ \=\ 1000\,2000\,3000\ bp +\#\ downstream\ sizes\ $ChIP\ region\ annotation$\ \=\ 1000\,2000\,3000\ bp +\#\ bidrectional\ promoter\ sizes\ $ChIP\ region\ annotation$\ \=\ 2500\,5000\ bp +\#\ span\ size\ $gene\-centered\ annotation$\ \=\ 3000\ bp\ +INFO\ \ \@\ .*\ \#1\ read\ the\ gene\ table\.\.\.\ +INFO\ \ \@\ .*\ \#2\ read\ the\ bed\ file\ of\ ChIP\ regions\.\.\.\ +INFO\ \ \@\ .*\ \#3\ perform\ gene\-centered\ annotation\.\.\.\ +INFO\ \ \@\ .*\ \#4\ See\ ceas\.xls\ for\ gene\-centered\ annotation\!\ +INFO\ \ \@\ .*\ \#5\ read\ the\ pre\-computed\ genome\ bg\ annotation\.\.\.\ +INFO\ \ \@\ .*\ \#6\ perform\ ChIP\ region\ annotation\.\.\.\ +INFO\ \ \@\ .*\ \#7\ write\ a\ R\ script\ of\ ChIP\ region\ annotation\.\.\.\ + +R\ version\ 3\.1\.2\ $2014\-10\-31$\ \-\-\ \"Pumpkin\ Helmet\" +Copyright\ $C$\ 2014\ The\ R\ Foundation\ for\ Statistical\ Computing +Platform\:\ .* + +R\ is\ free\ software\ and\ comes\ with\ ABSOLUTELY\ NO\ WARRANTY\. +You\ are\ welcome\ to\ redistribute\ it\ under\ certain\ conditions\. +Type\ \'license\'\ or\ \'licence\'\ for\ distribution\ details\. + +\ \ Natural\ language\ support\ but\ running\ in\ an\ English\ locale + +R\ is\ a\ collaborative\ project\ with\ many\ contributors\. +Type\ \'contributors\'\ for\ more\ information\ and +\'citation\'\ on\ how\ to\ cite\ R\ or\ R\ packages\ in\ publications\. + +Type\ \'demo\'\ for\ some\ demos\,\ \'help\'\ for\ on\-line\ help\,\ or +\'help\.start\'\ for\ an\ HTML\ browser\ interface\ to\ help\. +Type\ \'q\'\ to\ quit\ R\. + +\>\ \#\ ARGUMENTS\:\ +\>\ \#\ name\ \=\ ceas +\>\ \#\ gene\ annotation\ table\ \=\ .*galGal3\.refGene +\>\ \#\ BED\ file\ \=\ .* +\>\ \#\ WIG\ file\ \=\ None +\>\ \#\ extra\ BED\ file\ \=\ None +\>\ \#\ ChIP\ annotation\ \=\ On +\>\ \#\ gene\-centered\ annotation\ \=\ \ On +\>\ \#\ average\ profiling\ \=\ Off +\>\ \#\ dump\ profiles\ \=\ Off +\>\ \#\ re\-annotation\ for\ genome\ background\ $ChIP\ region\ annotation$\ \=\ False +\>\ \#\ promoter\ sizes\ $ChIP\ region\ annotation$\ \=\ 1000\,2000\,3000\ bp +\>\ \#\ downstream\ sizes\ $ChIP\ region\ annotation$\ \=\ 1000\,2000\,3000\ bp +\>\ \#\ bidrectional\ promoter\ sizes\ $ChIP\ region\ annotation$\ \=\ 2500\,5000\ bp +\>\ \#\ span\ size\ $gene\-centered\ annotation$\ \=\ 3000\ bp +\>\ pdf$\"ceas\.pdf\"\,height\=11\.5\,width\=8\.5$ +\>\ +\>\ \#\ .* +\>\ \#\ +\>\ \#\ ChIP\ annotation +\>\ \#\ +\>\ +\>\ +\>\ \#\ +\>\ \#\ Chromosomal\ Distribution +\>\ \#\ +\>\ +\>\ par$mar\=c\(4\,\ 4\,\ 5\,\ 3\.8$\,oma\=c$4\,\ 2\,\ 4\,\ 2$\) +\>\ r0\<\-c$100\.0$ +\>\ r1\<\-c$100\.0$ +\>\ height\<\-rbind$r0\,r1$ +\>\ names\=c$\"26\"$ +\>\ mp\<\-barplot$height\=height\,names\=names\,beside\=TRUE\,horiz\=TRUE\,col\=c\(\"\#5FA1C1\"\,\"\#EB9D86\"$\,main\=\"Chromosomal\ Distribution\ of\ ChIP\ Regions\"\,xlab\=\"Percentage\ \%\"\,ylab\=\"Chromosome\"\,border\=FALSE\,xlim\=c$0\.000000\,183\.333333$\,cex\.names\=1\) +\>\ text$x\=c\(100\.0$\,y\=mp\[1\,\]\,label\=c$\"100\.0\ \%\"$\,pos\=4\,offset\=0\.2\,cex\=0\.9\) +\>\ text$x\=c\(100\.0$\,y\=mp\[2\,\]\,label\=c$\"100\.0\ \%\ \(\<\=4\.9e\-324$\"\)\,pos\=4\,offset\=0\.2\,cex\=0\.9\) +\>\ legend$\"right\"\,legend\=c\(\"Genome\"\,\"ChIP\ \(p\-value$\"\)\,col\=c$\"\#5FA1C1\"\,\"\#EB9D86\"$\,pch\=15\,bty\=\"n\"\) +\>\ +\>\ \#\ +\>\ \#\ Promoter\,Bipromoter\,Downstream\,\ Gene\ and\ Regions\ of\ interest +\>\ \#\ +\>\ +\>\ par$mfrow\=c\(4\,\ 1$\,mar\=c$4\,\ 4\,\ 5\,\ 3\.8$\,oma\=c$4\,\ 2\,\ 4\,\ 2$\) +\>\ r0\<\-c$1\.8532425688606797\,\ 3\.616851183410451\,\ 5\.322318854623416$ +\>\ r1\<\-c$0\.0\,\ 0\.0\,\ 0\.0$ +\>\ height\<\-rbind$r0\,r1$ +\>\ names\=c$\"\<\=1000\ bp\"\,\"\<\=2000\ bp\"\,\"\<\=3000\ bp\"$ +\>\ mp\<\-barplot$height\=height\,names\=names\,beside\=TRUE\,horiz\=FALSE\,col\=c\(\"\#5FA1C1\"\,\"\#EB9D86\"$\,main\=\"Promoter\"\,ylab\=\"Percentage\ \%\"\,border\=FALSE\,ylim\=c$0\.000000\,9\.757585$\,cex\.names\=1\) +\>\ text$x\=mp\[1\,\]\,y\=c\(1\.8532425688606797\,\ 3\.616851183410451\,\ 5\.322318854623416$\,label\=c$\"1\.9\ \%\"\,\"3\.6\ \%\"\,\"5\.3\ \%\"$\,pos\=3\,offset\=0\.2\) +\>\ text$x\=mp\[2\,\]\,y\=c\(0\.0\,\ 0\.0\,\ 0\.0$\,label\=c$\"0\.000\ \% +\+\ \(0\.981$\"\,\"0\.000\ \% +\+\ $0\.964$\"\,\"0\.000\ \% +\+\ $0\.947$\"\)\,pos\=3\,offset\=0\.2\) +\>\ legend$\"topleft\"\,legend\=c\(\"Genome\"\,\"ChIP\ \(p\-value$\"\)\,col\=c$\"\#5FA1C1\"\,\"\#EB9D86\"$\,pch\=15\,bty\=\"n\"\) +\>\ r0\<\-c$0\.03876062889120376\,\ 0\.03876062889120376$ +\>\ r1\<\-c$0\.0\,\ 0\.0$ +\>\ height\<\-rbind$r0\,r1$ +\>\ names\=c$\"\<\=2500\ bp\"\,\"\<\=5000\ bp\"$ +\>\ mp\<\-barplot$height\=height\,names\=names\,beside\=TRUE\,horiz\=FALSE\,col\=c\(\"\#5FA1C1\"\,\"\#EB9D86\"$\,main\=\"Bidirectional\ Promoter\"\,ylab\=\"Percentage\ \%\"\,border\=FALSE\,ylim\=c$0\.000000\,0\.071061$\,cex\.names\=1\) +\>\ text$x\=mp\[1\,\]\,y\=c\(0\.03876062889120376\,\ 0\.03876062889120376$\,label\=c$\"0\.04\ \%\"\,\"0\.04\ \%\"$\,pos\=3\,offset\=0\.2\) +\>\ text$x\=mp\[2\,\]\,y\=c\(0\.0\,\ 0\.0$\,label\=c$\"0\.000\ \% +\+\ \(1\.000$\"\,\"0\.000\ \% +\+\ $1\.000$\"\)\,pos\=3\,offset\=0\.2\) +\>\ legend$\"topleft\"\,legend\=c\(\"Genome\"\,\"ChIP\ \(p\-value$\"\)\,col\=c$\"\#5FA1C1\"\,\"\#EB9D86\"$\,pch\=15\,bty\=\"n\"\) +\>\ r0\<\-c$1\.8290171758036773\,\ 3\.4690762857627364\,\ 4\.980740812519683$ +\>\ r1\<\-c$0\.0\,\ 0\.0\,\ 0\.0$ +\>\ height\<\-rbind$r0\,r1$ +\>\ names\=c$\"\<\=1000\ bp\"\,\"\<\=2000\ bp\"\,\"\<\=3000\ bp\"$ +\>\ mp\<\-barplot$height\=height\,names\=names\,beside\=TRUE\,horiz\=FALSE\,col\=c\(\"\#5FA1C1\"\,\"\#EB9D86\"$\,main\=\"Downstream\"\,ylab\=\"Percentage\ \%\"\,border\=FALSE\,ylim\=c$0\.000000\,9\.131358$\,cex\.names\=1\) +\>\ text$x\=mp\[1\,\]\,y\=c\(1\.8290171758036773\,\ 3\.4690762857627364\,\ 4\.980740812519683$\,label\=c$\"1\.8\ \%\"\,\"3\.5\ \%\"\,\"5\.0\ \%\"$\,pos\=3\,offset\=0\.2\) +\>\ text$x\=mp\[2\,\]\,y\=c\(0\.0\,\ 0\.0\,\ 0\.0$\,label\=c$\"0\.000\ \% +\+\ \(0\.982$\"\,\"0\.000\ \% +\+\ $0\.965$\"\,\"0\.000\ \% +\+\ $0\.950$\"\)\,pos\=3\,offset\=0\.2\) +\>\ legend$\"topleft\"\,legend\=c\(\"Genome\"\,\"ChIP\ \(p\-value$\"\)\,col\=c$\"\#5FA1C1\"\,\"\#EB9D86\"$\,pch\=15\,bty\=\"n\"\) +\>\ r0\<\-c$0\.2034933016788197\,\ 1\.3978051793890356\,\ 2\.359553283752029\,\ 19\.734005184234114\,\ 23\.694856949054$ +\>\ r1\<\-c$0\.0\,\ 0\.0\,\ 0\.0\,\ 0\.0\,\ 0\.0$ +\>\ height\<\-rbind$r0\,r1$ +\>\ names\=c$\"5\'UTR\"\,\"3\'UTR\"\,\"Coding\ Exon\"\,\"Intron\"\,\"All\"$ +\>\ mp\<\-barplot$height\=height\,names\=names\,beside\=TRUE\,horiz\=FALSE\,col\=c\(\"\#5FA1C1\"\,\"\#EB9D86\"$\,main\=\"Gene\"\,ylab\=\"Percentage\ \%\"\,border\=FALSE\,ylim\=c$0\.000000\,43\.440571$\,cex\.names\=1\) +\>\ text$x\=mp\[1\,\]\,y\=c\(0\.2034933016788197\,\ 1\.3978051793890356\,\ 2\.359553283752029\,\ 19\.734005184234114\,\ 23\.694856949054$\,label\=c$\"0\.2\ \%\"\,\"1\.4\ \%\"\,\"2\.4\ \%\"\,\"19\.7\ \%\"\,\"23\.7\ \%\"$\,pos\=3\,offset\=0\.2\) +\>\ text$x\=mp\[2\,\]\,y\=c\(0\.0\,\ 0\.0\,\ 0\.0\,\ 0\.0\,\ 0\.0$\,label\=c$\"0\.000\ \% +\+\ \(0\.998$\"\,\"0\.000\ \% +\+\ $0\.986$\"\,\"0\.000\ \% +\+\ $0\.976$\"\,\"0\.000\ \% +\+\ $0\.803$\"\,\"0\.000\ \% +\+\ $0\.763$\"\)\,pos\=3\,offset\=0\.2\) +\>\ legend$\"topleft\"\,legend\=c\(\"Genome\"\,\"ChIP\ \(p\-value$\"\)\,col\=c$\"\#5FA1C1\"\,\"\#EB9D86\"$\,pch\=15\,bty\=\"n\"\) +\>\ +\>\ \#\ +\>\ \#\ Distribution\ of\ Genome\ and\ ChIP\ regions\ over\ cis\-regulatory\ element +\>\ \#\ Note\ that\ the\ x\ may\ be\ modified\ for\ better\ graphics\ in\ case\ a\ value\ is\ too\ small +\>\ \#\ Thus\,\ look\ at\ the\ labels\ of\ the\ pie\ chart\ to\ get\ the\ real\ percentage\ values +\>\ \#\ +\>\ +\>\ par$mfcol\=c\(2\,\ 2$\,mar\=c$3\,\ 3\,\ 4\,\ 2\.8$\,oma\=c$4\,\ 2\,\ 4\,\ 2$\) +\>\ x\<\-c$0\.018532\,0\.017055\,0\.016037\,0\.017830\,0\.015092\,0\.014051\,0\.010000\,0\.013833\,0\.023014\,0\.192592\,0\.670292$ +\>\ pie$x\=x\,labels\=c\(\"1\.9\ \%\"\,\"1\.7\ \%\"\,\"1\.6\ \%\"\,\"1\.8\ \%\"\,\"1\.5\ \%\"\,\"1\.4\ \%\"\,\"0\.2\ \%\"\,\"1\.4\ \%\"\,\"2\.3\ \%\"\,\"19\.3\ \%\"\,\"67\.0\ \%\"$\,main\=\"Genome\"\,col\=c$\"\#445FA2\"\,\"\#EB9D86\"\,\"\#799F7A\"\,\"\#6C527F\"\,\"\#5FA1C1\"\,\"\#E8BB77\"\,\"\#A8C5EF\"\,\"\#FDCDB9\"\,\"\#C6E6B5\"\,\"\#F1D5EE\"\,\"\#B4E1F6\"$\,clockwise\=TRUE\,border\=FALSE\,radius\=0\.9\,cex\=0\.8\,init\.angle\=90\,density\=100\) +\>\ x\<\-c$0\.000000\,1\.000000$ +\>\ y\<\-c$0\.000000\,1\.000000$ +\>\ plot$x\,\ y\,type\=\"n\"\,main\=\"\"\,xlab\=\"\"\,ylab\=\"\"\,frame\=FALSE\,axes\=FALSE\,xaxt\=\"s\"\,yaxt\=\"s\"$ +\>\ legend$\"top\"\,legend\=c\(\"Promoter\ \(\<\=1000\ bp$\:\ 1\.9\ \%\"\,\"Promoter\ $1000\-2000\ bp$\:\ 1\.7\ \%\"\,\"Promoter\ $2000\-3000\ bp$\:\ 1\.6\ \%\"\,\"Downstream\ $\<\=1000\ bp$\:\ 1\.8\ \%\"\,\"Downstream\ $1000\-2000\ bp$\:\ 1\.5\ \%\"\,\"Downstream\ $2000\-3000\ bp$\:\ 1\.4\ \%\"\,\"5\'UTR\:\ 0\.2\ \%\"\,\"3\'UTR\:\ 1\.4\ \%\"\,\"Coding\ exon\:\ 2\.3\ \%\"\,\"Intron\:\ 19\.3\ \%\"\,\"Distal\ intergenic\:\ 67\.0\ \%\"\)\,col\=c$\"\#445FA2\"\,\"\#EB9D86\"\,\"\#799F7A\"\,\"\#6C527F\"\,\"\#5FA1C1\"\,\"\#E8BB77\"\,\"\#A8C5EF\"\,\"\#FDCDB9\"\,\"\#C6E6B5\"\,\"\#F1D5EE\"\,\"\#B4E1F6\"$\,pch\=15\,bty\=\"n\"\) +\>\ x\<\-c$0\.010000\,0\.010000\,0\.010000\,0\.010000\,0\.010000\,0\.010000\,0\.010000\,0\.010000\,0\.010000\,0\.010000\,1\.000000$ +\>\ pie$x\=x\,labels\=c\(\"0\.000\ \%\"\,\"0\.000\ \%\"\,\"0\.000\ \%\"\,\"0\.000\ \%\"\,\"0\.000\ \%\"\,\"0\.000\ \%\"\,\"0\.000\ \%\"\,\"0\.000\ \%\"\,\"0\.000\ \%\"\,\"0\.000\ \%\"\,\"100\.0\ \%\"$\,main\=\"ChIP\"\,col\=c$\"\#445FA2\"\,\"\#EB9D86\"\,\"\#799F7A\"\,\"\#6C527F\"\,\"\#5FA1C1\"\,\"\#E8BB77\"\,\"\#A8C5EF\"\,\"\#FDCDB9\"\,\"\#C6E6B5\"\,\"\#F1D5EE\"\,\"\#B4E1F6\"$\,clockwise\=TRUE\,border\=FALSE\,radius\=0\.9\,cex\=0\.8\,init\.angle\=90\,density\=100\) +\>\ x\<\-c$0\.000000\,1\.000000$ +\>\ y\<\-c$0\.000000\,1\.000000$ +\>\ plot$x\,\ y\,type\=\"n\"\,main\=\"\"\,xlab\=\"\"\,ylab\=\"\"\,frame\=FALSE\,axes\=FALSE\,xaxt\=\"s\"\,yaxt\=\"s\"$ +\>\ legend$\"top\"\,legend\=c\(\"Promoter\ \(\<\=1000\ bp$\:\ 0\.000\ \%\"\,\"Promoter\ $1000\-2000\ bp$\:\ 0\.000\ \%\"\,\"Promoter\ $2000\-3000\ bp$\:\ 0\.000\ \%\"\,\"Downstream\ $\<\=1000\ bp$\:\ 0\.000\ \%\"\,\"Downstream\ $1000\-2000\ bp$\:\ 0\.000\ \%\"\,\"Downstream\ $2000\-3000\ bp$\:\ 0\.000\ \%\"\,\"5\'UTR\:\ 0\.000\ \%\"\,\"3\'UTR\:\ 0\.000\ \%\"\,\"Coding\ exon\:\ 0\.000\ \%\"\,\"Intron\:\ 0\.000\ \%\"\,\"Distal\ intergenic\:\ 100\.0\ \%\"\)\,col\=c$\"\#445FA2\"\,\"\#EB9D86\"\,\"\#799F7A\"\,\"\#6C527F\"\,\"\#5FA1C1\"\,\"\#E8BB77\"\,\"\#A8C5EF\"\,\"\#FDCDB9\"\,\"\#C6E6B5\"\,\"\#F1D5EE\"\,\"\#B4E1F6\"$\,pch\=15\,bty\=\"n\"\) +\>\ +\>\ \#\ +\>\ \#\ ChIP\ regions\ over\ the\ genome +\>\ \#\ +\>\ +\>\ par$mar\=c\(4\,\ 4\,\ 5\,\ 3\.8$\,oma\=c$4\,\ 2\,\ 4\,\ 2$\) +\>\ layout$matrix\(c\(1\,\ 0\,\ 2\,\ 2$\,\ 2\,\ 2\,\ byrow\ \=\ TRUE\)\,widths\=c$1\,\ 1$\,heights\=c$1\,\ 5$\) +\>\ x\<\-c$0\.000000\,2\.515610$ +\>\ y\<\-c$0\.000000\,1\.000000$ +\>\ plot$x\,\ y\,type\=\"n\"\,main\=\"Distribution\ of\ Peak\ Heights\"\,xlab\=\"\"\,ylab\=\"\"\,xlim\=c\(0\.000000\,2\.515610$\,ylim\=c$0\.000000\,1\.000000$\,frame\=FALSE\,xaxt\=\"s\"\,yaxt\=\"n\"\,cex\=0\.9\) +\>\ x\<\-c$0\.000000\,2\.515610\,2\.515610\,0\.000000$ +\>\ y\<\-c$0\.000000\,0\.000000\,1\.000000\,1\.000000$ +\>\ polygon$x\,y\,col\=c\(\"black\"$\) +\>\ x\ \<\-\ c$0\.000000\,0\.169726\,0\.339451\,0\.509177\,0\.678903\,0\.848628\,1\.018354\,1\.188079\,1\.357805\,1\.527531\,1\.697256\,1\.866982\,2\.036708\,2\.206433\,2\.376159$ +\>\ y\<\-c$0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.800000$ +\>\ lines$x\,\ y\,xlim\=c\(0\,\ 2\.51561$\,ylim\=c$0\,\ 1$\,type\=\"l\"\,col\=c$\"cyan\"$\,lwd\=2\) +\>\ x\<\-c$4119129\.000000\,4119130\.000000$ +\>\ y\<\-c$0\.855556\,1\.144444$ +\>\ plot$x\,\ y\,type\=\"n\"\,main\=\"ChIP\ Regions\ \(Peaks$\ over\ Chromosomes\"\,xlab\=\"Chromosome\ Size\ $bp$\"\,ylab\=\"Chromosome\"\,xlim\=c$4119129\.000000\,4119130\.000000$\,ylim\=c$0\.855556\,1\.144444$\,frame\=FALSE\,xaxt\=\"s\"\,yaxt\=\"n\"\) +\>\ start\ \<\-\ c$4119129$ +\>\ end\ \<\-\ c$4119130$ +\>\ vals\ \<\-\ c$2\.51561$ +\>\ vals\[vals\ \>\ 2\.51561\]\ \<\-\ 2\.51561 +\>\ vals\[vals\ \<\ 0\]\ \<\-\ 0 +\>\ heights\ \<\-\ 0\.288889\ \*\ $\(vals\ \-\ 0$\/$2\.51561\ \-\ 0$\)\ \+\ 0\.855555555556 +\>\ for\ $i\ in\ 1\:length\(heights$\)\ \{ +\+\ \ polygon$x\=c\(start\[i\]\,\ end\[i\]\,\ end\[i\]\,\ start\[i\]$\,\ y\=c$0\.855555555556\,\ 0\.855555555556\,\ heights\[i\]\,\ heights\[i\]$\,\ col\=c$\"\#CC0000\"$\,\ border\=c$\"\#CC0000\"$\) +\+\ \} +\>\ mtext$\"26\"\,side\=2\,line\=0\,outer\=FALSE\,at\=1\.0$ +\>\ dev\.off +null\ device\ +\ \ \ \ \ \ \ \ \ \ 1\ +\>\ +INFO\ \ \@\ .*\ \#\.\.\.\ cong\!\ See\ ceas\.pdf\ for\ the\ graphical\ results\ of\ CEAS\!\ diff -r 000000000000 -r f411ce97a351 test-data/ceas_out1.pdf Binary file test-data/ceas_out1.pdf has changed diff -r 000000000000 -r f411ce97a351 test-data/ceas_out1.xls --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/ceas_out1.xls Tue Jun 30 07:08:05 2015 -0400 @@ -0,0 +1,133 @@ +# RefSeq: RefSeq ID +# chr: chromosome of a RefSeq gene +# txStart: 5' end of a RefSeq gene +# txEnd: 3' end site of a RefSeq gene +# strand: strand of a RefSeq gene +# dist u TSS: Distance to the nearest ChIP region's center upstream of transcription start site (bp) +# dist d TSS: Distance to the nearest ChIP region's center downstream of transcription start site (bp) +# dist u TTS: Distance to the nearest ChIP region's center upstream of transcription end site (bp) +# dist d TTS: Distance to the nearest ChIP region's center downstream of transcription end (bp) +# 3000bp u TSS: Occupancy rate of ChIP region in 3000bp upstream of transcription start site (0.0 - 1.0) +# 3000bp d TSS: Occupancy rate of ChIP region in 3000bp downstream of transcription start site (0.0 - 1.0) +# 1/3 gene: Occupancy rate of ChIP region in 1/3 gene (0.0 - 1.0) +# 2/3 gene: Occupancy rate of ChIP region in 2/3 gene (0.0 - 1.0) +# 3/3 gene: Occupancy rate of ChIP region in 3/3 gene (0.0 - 1.0) +# 3000bp d TTS: Occupancy rate of ChIP region in 3000bp downstream of transcriptino end (0.0 - 1.0) +# exons: Occupancy rate of ChIP regions in exons (0.0-1.0) +# Note that txStart and txEnd indicate 5' and 3' ends of genes whereas TSS and TTS transcription start and end sites in consideration of strand. +#name chr txStart txEnd strand dist u TSS dist d TSS dist u TTS dist d TTS 3000bp u TSS 3000bp d TSS 1/3 gene 2/3 gene 3/3 gene 3000bp d TTS exons +NM_001031576 chr26 19281 27136 + NA 4099848 NA 4091993 0 0 0 0 0 0 0 +NM_204615 chr26 57466 61594 - 4057535 NA 4061663 NA 0 0 0 0 0 0 0 +NM_001005431 chr26 65800 76175 - 4042954 NA 4053329 NA 0 0 0 0 0 0 0 +NM_001145491 chr26 91618 92166 - 4026963 NA 4027511 NA 0 0 0 0 0 0 0 +NM_204398 chr26 93069 97423 + NA 4026060 NA 4021706 0 0 0 0 0 0 0 +NM_001305147 chr26 254661 282571 + NA 3864468 NA 3836558 0 0 0 0 0 0 0 +NM_001305148 chr26 254661 282571 + NA 3864468 NA 3836558 0 0 0 0 0 0 0 +NM_001012868 chr26 350397 355252 - 3763877 NA 3768732 NA 0 0 0 0 0 0 0 +NM_001031030 chr26 479573 493561 + NA 3639556 NA 3625568 0 0 0 0 0 0 0 +NM_001305140 chr26 520705 526012 + NA 3598424 NA 3593117 0 0 0 0 0 0 0 +NM_001031029 chr26 537101 565572 + NA 3582028 NA 3553557 0 0 0 0 0 0 0 +NM_205248 chr26 537250 760479 + NA 3581879 NA 3358650 0 0 0 0 0 0 0 +NM_204727 chr26 662969 683066 - 3436063 NA 3456160 NA 0 0 0 0 0 0 0 +NR_105475 chr26 669012 669122 - 3450007 NA 3450117 NA 0 0 0 0 0 0 0 +NM_205449 chr26 785617 794076 + NA 3333512 NA 3325053 0 0 0 0 0 0 0 +NM_204681 chr26 897458 902049 - 3217080 NA 3221671 NA 0 0 0 0 0 0 0 +NM_001278156 chr26 905313 917094 - 3202035 NA 3213816 NA 0 0 0 0 0 0 0 +NM_204184 chr26 960209 964268 - 3154861 NA 3158920 NA 0 0 0 0 0 0 0 +NM_204316 chr26 974223 991244 + NA 3144906 NA 3127885 0 0 0 0 0 0 0 +NM_001031028 chr26 993815 1003847 - 3115282 NA 3125314 NA 0 0 0 0 0 0 0 +NM_001006392 chr26 1024606 1047756 - 3071373 NA 3094523 NA 0 0 0 0 0 0 0 +NM_001039596 chr26 1073550 1080033 - 3039096 NA 3045579 NA 0 0 0 0 0 0 0 +NM_001031027 chr26 1090460 1096137 + NA 3028669 NA 3022992 0 0 0 0 0 0 0 +NM_001031026 chr26 1096566 1104751 - 3014378 NA 3022563 NA 0 0 0 0 0 0 0 +NM_001030913 chr26 1122296 1132596 + NA 2996833 NA 2986533 0 0 0 0 0 0 0 +NM_001171886 chr26 1220031 1222791 - 2896338 NA 2899098 NA 0 0 0 0 0 0 0 +NM_205054 chr26 1229703 1232833 + NA 2889426 NA 2886296 0 0 0 0 0 0 0 +NM_204462 chr26 1234686 1236536 - 2882593 NA 2884443 NA 0 0 0 0 0 0 0 +NM_204463 chr26 1265724 1267989 - 2851140 NA 2853405 NA 0 0 0 0 0 0 0 +NM_001030378 chr26 1289091 1290386 - 2828743 NA 2830038 NA 0 0 0 0 0 0 0 +NM_001195554 chr26 1382510 1388447 + NA 2736619 NA 2730682 0 0 0 0 0 0 0 +NM_001012548 chr26 1406905 1428443 + NA 2712224 NA 2690686 0 0 0 0 0 0 0 +NR_031486 chr26 1442696 1442779 - 2676350 NA 2676433 NA 0 0 0 0 0 0 0 +NR_031487 chr26 1442896 1442979 - 2676150 NA 2676233 NA 0 0 0 0 0 0 0 +NM_205250 chr26 1472137 1474003 + NA 2646992 NA 2645126 0 0 0 0 0 0 0 +NR_105486 chr26 1566398 1566508 - 2552621 NA 2552731 NA 0 0 0 0 0 0 0 +NM_001160320 chr26 1697226 1773801 + NA 2421903 NA 2345328 0 0 0 0 0 0 0 +NM_001004709 chr26 1697226 1773801 + NA 2421903 NA 2345328 0 0 0 0 0 0 0 +NM_001160324 chr26 1697226 1773801 + NA 2421903 NA 2345328 0 0 0 0 0 0 0 +NM_001004493 chr26 1697226 1773801 + NA 2421903 NA 2345328 0 0 0 0 0 0 0 +NM_001160323 chr26 1697226 1773801 + NA 2421903 NA 2345328 0 0 0 0 0 0 0 +NM_001160322 chr26 1697226 1773801 + NA 2421903 NA 2345328 0 0 0 0 0 0 0 +NM_001160321 chr26 1697226 1773801 + NA 2421903 NA 2345328 0 0 0 0 0 0 0 +NM_001004395 chr26 1776431 1800083 + NA 2342698 NA 2319046 0 0 0 0 0 0 0 +NM_001030914 chr26 1811042 1820368 - 2298761 NA 2308087 NA 0 0 0 0 0 0 0 +NM_204506 chr26 1823407 1843085 - 2276044 NA 2295722 NA 0 0 0 0 0 0 0 +NR_031488 chr26 1925941 1926037 - 2193092 NA 2193188 NA 0 0 0 0 0 0 0 +NM_213581 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07:08:05 2015 -0400 @@ -0,0 +1,236 @@ +ceas -- 0.9.9.7 (package version 1.0.2) +INFO @ Tue, 23 Jun 2015 11:24:09: +# ARGUMENTS: +# name = ceas +# gene annotation table = galGal3.refGene +# BED file = ceas_in.bed +# WIG file = ceas_in_stp1000.wig +# extra BED file = None +# ChIP annotation = On +# gene-centered annotation = On +# average profiling = On +# dump profiles = Off +# re-annotation for genome background (ChIP region annotation) = False +# promoter sizes (ChIP region annotation) = 1000,2000,3000 bp +# downstream sizes (ChIP region annotation) = 1000,2000,3000 bp +# bidrectional promoter sizes (ChIP region annotation) = 2500,5000 bp +# span size (gene-centered annotation) = 3000 bp +# profiling resolution (average profiling) = 50 bp +# relative distance wrt TSS and TTS (average profiling) = 3000 bp +INFO @ Tue, 23 Jun 2015 11:24:09: #1 read the gene table... +INFO @ Tue, 23 Jun 2015 11:24:09: #2 read the bed file of ChIP regions... +INFO @ Tue, 23 Jun 2015 11:24:09: #3 perform gene-centered annotation... +INFO @ Tue, 23 Jun 2015 11:24:09: #4 See ceas.xls for gene-centered annotation! +INFO @ Tue, 23 Jun 2015 11:24:09: #5 read the pre-computed genome bg annotation... +INFO @ Tue, 23 Jun 2015 11:24:09: #6 perform ChIP region annotation... +INFO @ Tue, 23 Jun 2015 11:24:09: #7 write a R script of ChIP region annotation... +INFO @ Tue, 23 Jun 2015 11:24:09: #8-1 run wig profiling of chr26... +INFO @ Tue, 23 Jun 2015 11:24:09: #9 append an R script of wig profiling... + +R version 3.1.2 (2014-10-31) -- "Pumpkin Helmet" +Copyright (C) 2014 The R Foundation for Statistical Computing +Platform: x86_64-redhat-linux-gnu (64-bit) + +R is free software and comes with ABSOLUTELY NO WARRANTY. +You are welcome to redistribute it under certain conditions. +Type 'license()' or 'licence()' for distribution details. + + Natural language support but running in an English locale + +R is a collaborative project with many contributors. +Type 'contributors()' for more information and +'citation()' on how to cite R or R packages in publications. + +Type 'demo()' for some demos, 'help()' for on-line help, or +'help.start()' for an HTML browser interface to help. +Type 'q()' to quit R. + +> # ARGUMENTS: +> # name = ceas +> # gene annotation table = galGal3.refGene +> # BED file = ceas_in.bed +> # WIG file = ceas_in_stp1000.wig +> # extra BED file = None +> # ChIP annotation = On +> # gene-centered annotation = On +> # average profiling = On +> # dump profiles = Off +> # re-annotation for genome background (ChIP region annotation) = False +> # promoter sizes (ChIP region annotation) = 1000,2000,3000 bp +> # downstream sizes (ChIP region annotation) = 1000,2000,3000 bp +> # bidrectional promoter sizes (ChIP region annotation) = 2500,5000 bp +> # span size (gene-centered annotation) = 3000 bp +> # profiling resolution (average profiling) = 50 bp +> # relative distance wrt TSS and TTS (average profiling) = 3000 bp +> pdf("ceas.pdf",height=11.5,width=8.5) +> +> # 11:24:09 Tue, 23 Jun 2015 +> # +> # ChIP annotation +> # +> +> +> # +> # Chromosomal Distribution +> # +> +> par(mar=c(4, 4, 5, 3.8),oma=c(4, 2, 4, 2)) +> r0<-c(100.0) +> r1<-c(100.0) +> height<-rbind(r0,r1) +> names=c("26") +> mp<-barplot(height=height,names=names,beside=TRUE,horiz=TRUE,col=c("#5FA1C1","#EB9D86"),main="Chromosomal Distribution of ChIP Regions",xlab="Percentage %",ylab="Chromosome",border=FALSE,xlim=c(0.000000,183.333333),cex.names=1) +> text(x=c(100.0),y=mp[1,],label=c("100.0 %"),pos=4,offset=0.2,cex=0.9) +> text(x=c(100.0),y=mp[2,],label=c("100.0 % (<=4.9e-324)"),pos=4,offset=0.2,cex=0.9) +> legend("right",legend=c("Genome","ChIP (p-value)"),col=c("#5FA1C1","#EB9D86"),pch=15,bty="n") +> +> # +> # Promoter,Bipromoter,Downstream, Gene and Regions of interest +> # +> +> par(mfrow=c(4, 1),mar=c(4, 4, 5, 3.8),oma=c(4, 2, 4, 2)) +> r0<-c(1.8532425688606797, 3.616851183410451, 5.322318854623416) +> r1<-c(0.0, 0.0, 0.0) +> height<-rbind(r0,r1) +> names=c("<=1000 bp","<=2000 bp","<=3000 bp") +> mp<-barplot(height=height,names=names,beside=TRUE,horiz=FALSE,col=c("#5FA1C1","#EB9D86"),main="Promoter",ylab="Percentage %",border=FALSE,ylim=c(0.000000,9.757585),cex.names=1) +> text(x=mp[1,],y=c(1.8532425688606797, 3.616851183410451, 5.322318854623416),label=c("1.9 %","3.6 %","5.3 %"),pos=3,offset=0.2) +> text(x=mp[2,],y=c(0.0, 0.0, 0.0),label=c("0.000 % ++ (0.981)","0.000 % ++ (0.964)","0.000 % ++ (0.947)"),pos=3,offset=0.2) +> legend("topleft",legend=c("Genome","ChIP (p-value)"),col=c("#5FA1C1","#EB9D86"),pch=15,bty="n") +> r0<-c(0.03876062889120376, 0.03876062889120376) +> r1<-c(0.0, 0.0) +> height<-rbind(r0,r1) +> names=c("<=2500 bp","<=5000 bp") +> mp<-barplot(height=height,names=names,beside=TRUE,horiz=FALSE,col=c("#5FA1C1","#EB9D86"),main="Bidirectional Promoter",ylab="Percentage %",border=FALSE,ylim=c(0.000000,0.071061),cex.names=1) +> text(x=mp[1,],y=c(0.03876062889120376, 0.03876062889120376),label=c("0.04 %","0.04 %"),pos=3,offset=0.2) +> text(x=mp[2,],y=c(0.0, 0.0),label=c("0.000 % ++ (1.000)","0.000 % ++ (1.000)"),pos=3,offset=0.2) +> legend("topleft",legend=c("Genome","ChIP (p-value)"),col=c("#5FA1C1","#EB9D86"),pch=15,bty="n") +> r0<-c(1.8290171758036773, 3.4690762857627364, 4.980740812519683) +> r1<-c(0.0, 0.0, 0.0) +> height<-rbind(r0,r1) +> names=c("<=1000 bp","<=2000 bp","<=3000 bp") +> mp<-barplot(height=height,names=names,beside=TRUE,horiz=FALSE,col=c("#5FA1C1","#EB9D86"),main="Downstream",ylab="Percentage %",border=FALSE,ylim=c(0.000000,9.131358),cex.names=1) +> text(x=mp[1,],y=c(1.8290171758036773, 3.4690762857627364, 4.980740812519683),label=c("1.8 %","3.5 %","5.0 %"),pos=3,offset=0.2) +> text(x=mp[2,],y=c(0.0, 0.0, 0.0),label=c("0.000 % ++ (0.982)","0.000 % ++ (0.965)","0.000 % ++ (0.950)"),pos=3,offset=0.2) +> legend("topleft",legend=c("Genome","ChIP (p-value)"),col=c("#5FA1C1","#EB9D86"),pch=15,bty="n") +> r0<-c(0.2034933016788197, 1.3978051793890356, 2.359553283752029, 19.734005184234114, 23.694856949054) +> r1<-c(0.0, 0.0, 0.0, 0.0, 0.0) +> height<-rbind(r0,r1) +> names=c("5'UTR","3'UTR","Coding Exon","Intron","All") +> mp<-barplot(height=height,names=names,beside=TRUE,horiz=FALSE,col=c("#5FA1C1","#EB9D86"),main="Gene",ylab="Percentage %",border=FALSE,ylim=c(0.000000,43.440571),cex.names=1) +> text(x=mp[1,],y=c(0.2034933016788197, 1.3978051793890356, 2.359553283752029, 19.734005184234114, 23.694856949054),label=c("0.2 %","1.4 %","2.4 %","19.7 %","23.7 %"),pos=3,offset=0.2) +> text(x=mp[2,],y=c(0.0, 0.0, 0.0, 0.0, 0.0),label=c("0.000 % ++ (0.998)","0.000 % ++ (0.986)","0.000 % ++ (0.976)","0.000 % ++ (0.803)","0.000 % ++ (0.763)"),pos=3,offset=0.2) +> legend("topleft",legend=c("Genome","ChIP (p-value)"),col=c("#5FA1C1","#EB9D86"),pch=15,bty="n") +> +> # +> # Distribution of Genome and ChIP regions over cis-regulatory element +> # Note that the x may be modified for better graphics in case a value is too small +> # Thus, look at the labels of the pie chart to get the real percentage values +> # +> +> par(mfcol=c(2, 2),mar=c(3, 3, 4, 2.8),oma=c(4, 2, 4, 2)) +> x<-c(0.018532,0.017055,0.016037,0.017830,0.015092,0.014051,0.010000,0.013833,0.023014,0.192592,0.670292) +> pie(x=x,labels=c("1.9 %","1.7 %","1.6 %","1.8 %","1.5 %","1.4 %","0.2 %","1.4 %","2.3 %","19.3 %","67.0 %"),main="Genome",col=c("#445FA2","#EB9D86","#799F7A","#6C527F","#5FA1C1","#E8BB77","#A8C5EF","#FDCDB9","#C6E6B5","#F1D5EE","#B4E1F6"),clockwise=TRUE,border=FALSE,radius=0.9,cex=0.8,init.angle=90,density=100) +> x<-c(0.000000,1.000000) +> y<-c(0.000000,1.000000) +> plot(x, y,type="n",main="",xlab="",ylab="",frame=FALSE,axes=FALSE,xaxt="s",yaxt="s") +> legend("top",legend=c("Promoter (<=1000 bp): 1.9 %","Promoter (1000-2000 bp): 1.7 %","Promoter (2000-3000 bp): 1.6 %","Downstream (<=1000 bp): 1.8 %","Downstream (1000-2000 bp): 1.5 %","Downstream (2000-3000 bp): 1.4 %","5'UTR: 0.2 %","3'UTR: 1.4 %","Coding exon: 2.3 %","Intron: 19.3 %","Distal intergenic: 67.0 %"),col=c("#445FA2","#EB9D86","#799F7A","#6C527F","#5FA1C1","#E8BB77","#A8C5EF","#FDCDB9","#C6E6B5","#F1D5EE","#B4E1F6"),pch=15,bty="n") +> x<-c(0.010000,0.010000,0.010000,0.010000,0.010000,0.010000,0.010000,0.010000,0.010000,0.010000,1.000000) +> pie(x=x,labels=c("0.000 %","0.000 %","0.000 %","0.000 %","0.000 %","0.000 %","0.000 %","0.000 %","0.000 %","0.000 %","100.0 %"),main="ChIP",col=c("#445FA2","#EB9D86","#799F7A","#6C527F","#5FA1C1","#E8BB77","#A8C5EF","#FDCDB9","#C6E6B5","#F1D5EE","#B4E1F6"),clockwise=TRUE,border=FALSE,radius=0.9,cex=0.8,init.angle=90,density=100) +> x<-c(0.000000,1.000000) +> y<-c(0.000000,1.000000) +> plot(x, y,type="n",main="",xlab="",ylab="",frame=FALSE,axes=FALSE,xaxt="s",yaxt="s") +> legend("top",legend=c("Promoter (<=1000 bp): 0.000 %","Promoter (1000-2000 bp): 0.000 %","Promoter (2000-3000 bp): 0.000 %","Downstream (<=1000 bp): 0.000 %","Downstream (1000-2000 bp): 0.000 %","Downstream (2000-3000 bp): 0.000 %","5'UTR: 0.000 %","3'UTR: 0.000 %","Coding exon: 0.000 %","Intron: 0.000 %","Distal intergenic: 100.0 %"),col=c("#445FA2","#EB9D86","#799F7A","#6C527F","#5FA1C1","#E8BB77","#A8C5EF","#FDCDB9","#C6E6B5","#F1D5EE","#B4E1F6"),pch=15,bty="n") +> +> # +> # ChIP regions over the genome +> # +> +> par(mar=c(4, 4, 5, 3.8),oma=c(4, 2, 4, 2)) +> layout(matrix(c(1, 0, 2, 2), 2, 2, byrow = TRUE),widths=c(1, 1),heights=c(1, 5)) +> x<-c(0.000000,0.000000) +> y<-c(0.000000,1.000000) +> plot(x, y,type="n",main="Distribution of Peak Heights",xlab="",ylab="",xlim=c(0.000000,0.000000),ylim=c(0.000000,1.000000),frame=FALSE,xaxt="s",yaxt="n",cex=0.9) +> x<-c(0.000000,0.000000,0.000000,0.000000) +> y<-c(0.000000,0.000000,1.000000,1.000000) +> polygon(x,y,col=c("black")) +> x <- c(0.000000) +> y<-c(0.800000) +> lines(x, y,xlim=c(0, 0.0),ylim=c(0, 1),type="l",col=c("cyan"),lwd=2) +> x<-c(0.000000,4127518.000000) +> y<-c(0.855556,1.144444) +> plot(x, y,type="n",main="ChIP Regions (Peaks) over Chromosomes",xlab="Chromosome Size (bp)",ylab="Chromosome",xlim=c(0.000000,4127518.000000),ylim=c(0.855556,1.144444),frame=FALSE,xaxt="s",yaxt="n") +> start <- c(4119129) +> end <- c(4119130) +> vals <- c(0.0) +> vals[vals > 0.0] <- 0.0 +> vals[vals < 0] <- 0 +> heights <- 0.288889 * ((vals - 0)/(0.0 - 0)) + 0.855555555556 +> for (i in 1:length(heights)) { ++ polygon(x=c(start[i], end[i], end[i], start[i]), y=c(0.855555555556, 0.855555555556, heights[i], heights[i]), col=c("#CC0000"), border=c("#CC0000")) ++ } +> mtext("26",side=2,line=0,outer=FALSE,at=1.0) +> par(mar=c(4, 4, 5, 3.8),oma=c(4, 2, 4, 2)) +> layout(matrix(c(1, 2, 3, 3, 4, 5), 3, 2, byrow = TRUE),widths=c(1, 1),heights=c(1, 1, 1)) +> x<-c(-3000.000000,-2950.000000,-2900.000000,-2850.000000,-2800.000000,-2750.000000,-2700.000000,-2650.000000,-2600.000000,-2550.000000,-2500.000000,-2450.000000,-2400.000000,-2350.000000,-2300.000000,-2250.000000,-2200.000000,-2150.000000,-2100.000000,-2050.000000,-2000.000000,-1950.000000,-1900.000000,-1850.000000,-1800.000000,-1750.000000,-1700.000000,-1650.000000,-1600.000000,-1550.000000,-1500.000000,-1450.000000,-1400.000000,-1350.000000,-1300.000000,-1250.000000,-1200.000000,-1150.000000,-1100.000000,-1050.000000,-1000.000000,-950.000000,-900.000000,-850.000000,-800.000000,-750.000000,-700.000000,-650.000000,-600.000000,-550.000000,-500.000000,-450.000000,-400.000000,-350.000000,-300.000000,-250.000000,-200.000000,-150.000000,-100.000000,-50.000000,0.000000,50.000000,100.000000,150.000000,200.000000,250.000000,300.000000,350.000000,400.000000,450.000000,500.000000,550.000000,600.000000,650.000000,700.000000,750.000000,800.000000,850.000000,900.000000,950.000000,1000.000000,1050.000000,1100.000000,1150.000000,1200.000000,1250.000000,1300.000000,1350.000000,1400.000000,1450.000000,1500.000000,1550.000000,1600.000000,1650.000000,1700.000000,1750.000000,1800.000000,1850.000000,1900.000000,1950.000000,2000.000000,2050.000000,2100.000000,2150.000000,2200.000000,2250.000000,2300.000000,2350.000000,2400.000000,2450.000000,2500.000000,2550.000000,2600.000000,2650.000000,2700.000000,2750.000000,2800.000000,2850.000000,2900.000000,2950.000000,3000.000000) +> y<-c(0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,217.391304,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000) +> plot(x, y,type="l",main="Average Profile near TSS",xlab="Relative Distance to TSS (bp)",ylab="Average Profile",col=c("#C8524D"),xaxt="s",yaxt="s",lwd=2) +> abline(v=0.000000,lty=2,col=c("black")) +> x<-c(-3000.000000,-2950.000000,-2900.000000,-2850.000000,-2800.000000,-2750.000000,-2700.000000,-2650.000000,-2600.000000,-2550.000000,-2500.000000,-2450.000000,-2400.000000,-2350.000000,-2300.000000,-2250.000000,-2200.000000,-2150.000000,-2100.000000,-2050.000000,-2000.000000,-1950.000000,-1900.000000,-1850.000000,-1800.000000,-1750.000000,-1700.000000,-1650.000000,-1600.000000,-1550.000000,-1500.000000,-1450.000000,-1400.000000,-1350.000000,-1300.000000,-1250.000000,-1200.000000,-1150.000000,-1100.000000,-1050.000000,-1000.000000,-950.000000,-900.000000,-850.000000,-800.000000,-750.000000,-700.000000,-650.000000,-600.000000,-550.000000,-500.000000,-450.000000,-400.000000,-350.000000,-300.000000,-250.000000,-200.000000,-150.000000,-100.000000,-50.000000,0.000000,50.000000,100.000000,150.000000,200.000000,250.000000,300.000000,350.000000,400.000000,450.000000,500.000000,550.000000,600.000000,650.000000,700.000000,750.000000,800.000000,850.000000,900.000000,950.000000,1000.000000,1050.000000,1100.000000,1150.000000,1200.000000,1250.000000,1300.000000,1350.000000,1400.000000,1450.000000,1500.000000,1550.000000,1600.000000,1650.000000,1700.000000,1750.000000,1800.000000,1850.000000,1900.000000,1950.000000,2000.000000,2050.000000,2100.000000,2150.000000,2200.000000,2250.000000,2300.000000,2350.000000,2400.000000,2450.000000,2500.000000,2550.000000,2600.000000,2650.000000,2700.000000,2750.000000,2800.000000,2850.000000,2900.000000,2950.000000,3000.000000) +> y<-c(0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,217.391304,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,217.391304,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,217.391304,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,217.391304,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,217.391304,0.000000,0.000000,0.000000,0.000000,217.391304,0.000000,0.000000,0.000000,0.000000,0.000000,217.391304,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,217.391304,0.000000,0.000000) +> plot(x, y,type="l",main="Average Profile near TTS",xlab="Relative Distance to TTS (bp)",ylab="Average Profile",col=c("#C8524D"),xaxt="s",yaxt="s",lwd=2) +> abline(v=0.000000,lty=2,col=c("black")) +> x<-c(-1000.000000,-950.000000,-900.000000,-850.000000,-800.000000,-750.000000,-700.000000,-650.000000,-600.000000,-550.000000,-500.000000,-450.000000,-400.000000,-350.000000,-300.000000,-250.000000,-200.000000,-150.000000,-100.000000,-50.000000,0.000000,50.000000,100.000000,150.000000,200.000000,250.000000,300.000000,350.000000,400.000000,450.000000,500.000000,550.000000,600.000000,650.000000,700.000000,750.000000,800.000000,850.000000,900.000000,950.000000,1000.000000,1050.000000,1100.000000,1150.000000,1200.000000,1250.000000,1300.000000,1350.000000,1400.000000,1450.000000,1500.000000,1550.000000,1600.000000,1650.000000,1700.000000,1750.000000,1800.000000,1850.000000,1900.000000,1950.000000,2000.000000,2050.000000,2100.000000,2150.000000,2200.000000,2250.000000,2300.000000,2350.000000,2400.000000,2450.000000,2500.000000,2550.000000,2600.000000,2650.000000,2700.000000,2750.000000,2800.000000,2850.000000,2900.000000,2950.000000,3000.000000,3050.000000,3100.000000,3150.000000,3200.000000,3250.000000,3300.000000,3350.000000,3400.000000,3450.000000,3500.000000,3550.000000,3600.000000,3650.000000,3700.000000,3750.000000,3800.000000,3850.000000,3900.000000,3950.000000,4000.000000) +> y<-c(0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,238.095238,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,217.391304,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,217.391304,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000) +> plot(x, y,type="l",main="Average Gene Profile",xlab="Upstream (bp), 3000 bp of Meta-gene, Downstream (bp)",ylab="Average Profile",col=c("#C8524D"),xaxt="s",yaxt="s",lwd=2) +> abline(v=0.000000,lty=2,col=c("black")) +> abline(v=3000.000000,lty=2,col=c("black")) +> x<-c(0.000000,3.333333,6.666667,10.000000,13.333333,16.666667,20.000000,23.333333,26.666667,30.000000,33.333333,36.666667,40.000000,43.333333,46.666667,50.000000,53.333333,56.666667,60.000000,63.333333,66.666667,70.000000,73.333333,76.666667,80.000000,83.333333,86.666667,90.000000,93.333333,96.666667,100.000000) +> y<-c(0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,250.000000,0.000000,0.000000,0.000000,0.000000) +> plot(x, y,type="l",main="Average Concatenated Exon Profile",xlab="Relative Location (%)",ylab="Average Profile",col=c("#C8524D"),ylim=c(0.000000,250.000000),xaxt="s",yaxt="s",lwd=2) +> x<-c(0.000000,3.333333,6.666667,10.000000,13.333333,16.666667,20.000000,23.333333,26.666667,30.000000,33.333333,36.666667,40.000000,43.333333,46.666667,50.000000,53.333333,56.666667,60.000000,63.333333,66.666667,70.000000,73.333333,76.666667,80.000000,83.333333,86.666667,90.000000,93.333333,96.666667,100.000000) +> y<-c(0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000) +> plot(x, y,type="l",main="Average Concatenated Intron Profile",xlab="Relative Location (%)",ylab="Average Profile",col=c("#C8524D"),ylim=c(0.000000,250.000000),xaxt="s",yaxt="s",lwd=2) +> par(mfrow=c(3, 2),mar=c(4, 4, 5, 3.8),oma=c(4, 2, 4, 2)) +> x<-c(0.000000,50.000000,100.000000) +> y<-c(0.000000,0.000000,0.000000) +> plot(x, y,type="l",main="Average Exon Profile ++ (56 <= length < 109 bp)",xlab="Relative Location (%)",ylab="Average Profile",col=c("#C8524D"),ylim=c(0.000000,132.596685),xaxt="s",yaxt="s",lwd=2) +> x<-c(0.000000,25.000000,50.000000,75.000000,100.000000) +> y<-c(0.000000,0.000000,0.000000,0.000000,0.000000) +> plot(x, y,type="l",main="Average Intron Profile ++ (110 <= length < 345 bp)",xlab="Relative Location (%)",ylab="Average Profile",col=c("#C8524D"),ylim=c(0.000000,132.596685),xaxt="s",yaxt="s",lwd=2) +> x<-c(0.000000,50.000000,100.000000) +> y<-c(0.000000,0.000000,0.000000) +> plot(x, y,type="l",main="Average Exon Profile ++ (109 <= length < 160 bp)",xlab="Relative Location (%)",ylab="Average Profile",col=c("#C8524D"),ylim=c(0.000000,132.596685),xaxt="s",yaxt="s",lwd=2) +> x<-c(0.000000,11.111111,22.222222,33.333333,44.444444,55.555556,66.666667,77.777778,88.888889,100.000000) +> y<-c(0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000) +> plot(x, y,type="l",main="Average Intron Profile ++ (344 <= length < 686 bp)",xlab="Relative Location (%)",ylab="Average Profile",col=c("#C8524D"),ylim=c(0.000000,132.596685),xaxt="s",yaxt="s",lwd=2) +> x<-c(0.000000,33.333333,66.666667,100.000000) +> y<-c(0.000000,0.000000,0.000000,0.000000) +> plot(x, y,type="l",main="Average Exon Profile ++ (160 <= length < 375 bp)",xlab="Relative Location (%)",ylab="Average Profile",col=c("#C8524D"),ylim=c(0.000000,132.596685),xaxt="s",yaxt="s",lwd=2) +> x<-c(0.000000,4.761905,9.523810,14.285714,19.047619,23.809524,28.571429,33.333333,38.095238,42.857143,47.619048,52.380952,57.142857,61.904762,66.666667,71.428571,76.190476,80.952381,85.714286,90.476190,95.238095,100.000000) +> y<-c(0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,110.497238,0.000000) +> plot(x, y,type="l",main="Average Intron Profile ++ (685 <= length < 2653 bp)",xlab="Relative Location (%)",ylab="Average Profile",col=c("#C8524D"),ylim=c(0.000000,132.596685),xaxt="s",yaxt="s",lwd=2) +> dev.off() +null device + 1 +> +INFO @ Tue, 23 Jun 2015 11:24:09: #... cong! See ceas.pdf for the graphical results of CEAS! diff -r 000000000000 -r f411ce97a351 test-data/ceas_out2.log.re_match --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/ceas_out2.log.re_match Tue Jun 30 07:08:05 2015 -0400 @@ -0,0 +1,236 @@ +ceas\ \-\-\ 0\.9\.9\.7\ $package\ version\ 1\.0\.2$ +INFO\ \ \@\ .* +\#\ ARGUMENTS\:\ +\#\ name\ \=\ ceas +\#\ gene\ annotation\ table\ \=\ .*galGal3\.refGene +\#\ BED\ file\ \=\ .* +\#\ WIG\ file\ \=\ .* +\#\ extra\ BED\ file\ \=\ None +\#\ ChIP\ annotation\ \=\ On +\#\ gene\-centered\ annotation\ \=\ \ On +\#\ average\ profiling\ \=\ On +\#\ dump\ profiles\ \=\ Off +\#\ re\-annotation\ for\ genome\ background\ $ChIP\ region\ annotation$\ \=\ False +\#\ promoter\ sizes\ $ChIP\ region\ annotation$\ \=\ 1000\,2000\,3000\ bp +\#\ downstream\ sizes\ $ChIP\ region\ annotation$\ \=\ 1000\,2000\,3000\ bp +\#\ bidrectional\ promoter\ sizes\ $ChIP\ region\ annotation$\ \=\ 2500\,5000\ bp +\#\ span\ size\ $gene\-centered\ annotation$\ \=\ 3000\ bp +\#\ profiling\ resolution\ $average\ profiling$\ \=\ 50\ bp +\#\ relative\ distance\ wrt\ TSS\ and\ TTS\ $average\ profiling$\ \=\ 3000\ bp\ +INFO\ \ \@\ .*\ \#1\ read\ the\ gene\ table\.\.\.\ +INFO\ \ \@\ .*\ \#2\ read\ the\ bed\ file\ of\ ChIP\ regions\.\.\.\ +INFO\ \ \@\ .*\ \#3\ perform\ gene\-centered\ annotation\.\.\.\ +INFO\ \ \@\ .*\ \#4\ See\ ceas\.xls\ for\ gene\-centered\ annotation\!\ +INFO\ \ \@\ .*\ \#5\ read\ the\ pre\-computed\ genome\ bg\ annotation\.\.\.\ +INFO\ \ \@\ .*\ \#6\ perform\ ChIP\ region\ annotation\.\.\.\ +INFO\ \ \@\ .*\ \#7\ write\ a\ R\ script\ of\ ChIP\ region\ annotation\.\.\.\ +INFO\ \ \@\ .*\ \#8\-1\ run\ wig\ profiling\ of\ chr26\.\.\.\ +INFO\ \ \@\ .*\ \#9\ append\ an\ R\ script\ of\ wig\ profiling\.\.\.\ + +R\ version\ 3\.1\.2\ $2014\-10\-31$\ \-\-\ \"Pumpkin\ Helmet\" +Copyright\ $C$\ 2014\ The\ R\ Foundation\ for\ Statistical\ Computing +Platform\:\ .* + +R\ is\ free\ software\ and\ comes\ with\ ABSOLUTELY\ NO\ WARRANTY\. +You\ are\ welcome\ to\ redistribute\ it\ under\ certain\ conditions\. +Type\ \'license\'\ or\ \'licence\'\ for\ distribution\ details\. + +\ \ Natural\ language\ support\ but\ running\ in\ an\ English\ locale + +R\ is\ a\ collaborative\ project\ with\ many\ contributors\. +Type\ \'contributors\'\ for\ more\ information\ and +\'citation\'\ on\ how\ to\ cite\ R\ or\ R\ packages\ in\ publications\. + +Type\ \'demo\'\ for\ some\ demos\,\ \'help\'\ for\ on\-line\ help\,\ or +\'help\.start\'\ for\ an\ HTML\ browser\ interface\ to\ help\. +Type\ \'q\'\ to\ quit\ R\. + +\>\ \#\ ARGUMENTS\:\ +\>\ \#\ name\ \=\ ceas +\>\ \#\ gene\ annotation\ table\ \=\ .*galGal3\.refGene +\>\ \#\ BED\ file\ \=\ .* +\>\ \#\ WIG\ file\ \=\ .* +\>\ \#\ extra\ BED\ file\ \=\ None +\>\ \#\ ChIP\ annotation\ \=\ On +\>\ \#\ gene\-centered\ annotation\ \=\ \ On +\>\ \#\ average\ profiling\ \=\ On +\>\ \#\ dump\ profiles\ \=\ Off +\>\ \#\ re\-annotation\ for\ genome\ background\ $ChIP\ region\ annotation$\ \=\ False +\>\ \#\ promoter\ sizes\ $ChIP\ region\ annotation$\ \=\ 1000\,2000\,3000\ bp +\>\ \#\ downstream\ sizes\ $ChIP\ region\ annotation$\ \=\ 1000\,2000\,3000\ bp +\>\ \#\ bidrectional\ promoter\ sizes\ $ChIP\ region\ annotation$\ \=\ 2500\,5000\ bp +\>\ \#\ span\ size\ $gene\-centered\ annotation$\ \=\ 3000\ bp +\>\ \#\ profiling\ resolution\ $average\ profiling$\ \=\ 50\ bp +\>\ \#\ relative\ distance\ wrt\ TSS\ and\ TTS\ $average\ profiling$\ \=\ 3000\ bp +\>\ pdf$\"ceas\.pdf\"\,height\=11\.5\,width\=8\.5$ +\>\ +\>\ \#\ .* +\>\ \#\ +\>\ \#\ ChIP\ annotation +\>\ \#\ +\>\ +\>\ +\>\ \#\ +\>\ \#\ Chromosomal\ Distribution +\>\ \#\ +\>\ +\>\ par$mar\=c\(4\,\ 4\,\ 5\,\ 3\.8$\,oma\=c$4\,\ 2\,\ 4\,\ 2$\) +\>\ r0\<\-c$100\.0$ +\>\ r1\<\-c$100\.0$ +\>\ height\<\-rbind$r0\,r1$ +\>\ names\=c$\"26\"$ +\>\ mp\<\-barplot$height\=height\,names\=names\,beside\=TRUE\,horiz\=TRUE\,col\=c\(\"\#5FA1C1\"\,\"\#EB9D86\"$\,main\=\"Chromosomal\ Distribution\ of\ ChIP\ Regions\"\,xlab\=\"Percentage\ \%\"\,ylab\=\"Chromosome\"\,border\=FALSE\,xlim\=c$0\.000000\,183\.333333$\,cex\.names\=1\) +\>\ text$x\=c\(100\.0$\,y\=mp\[1\,\]\,label\=c$\"100\.0\ \%\"$\,pos\=4\,offset\=0\.2\,cex\=0\.9\) +\>\ text$x\=c\(100\.0$\,y\=mp\[2\,\]\,label\=c$\"100\.0\ \%\ \(\<\=4\.9e\-324$\"\)\,pos\=4\,offset\=0\.2\,cex\=0\.9\) +\>\ legend$\"right\"\,legend\=c\(\"Genome\"\,\"ChIP\ \(p\-value$\"\)\,col\=c$\"\#5FA1C1\"\,\"\#EB9D86\"$\,pch\=15\,bty\=\"n\"\) +\>\ +\>\ \#\ +\>\ \#\ Promoter\,Bipromoter\,Downstream\,\ Gene\ and\ Regions\ of\ interest +\>\ \#\ +\>\ +\>\ par$mfrow\=c\(4\,\ 1$\,mar\=c$4\,\ 4\,\ 5\,\ 3\.8$\,oma\=c$4\,\ 2\,\ 4\,\ 2$\) +\>\ r0\<\-c$1\.8532425688606797\,\ 3\.616851183410451\,\ 5\.322318854623416$ +\>\ r1\<\-c$0\.0\,\ 0\.0\,\ 0\.0$ +\>\ height\<\-rbind$r0\,r1$ +\>\ names\=c$\"\<\=1000\ bp\"\,\"\<\=2000\ bp\"\,\"\<\=3000\ bp\"$ +\>\ mp\<\-barplot$height\=height\,names\=names\,beside\=TRUE\,horiz\=FALSE\,col\=c\(\"\#5FA1C1\"\,\"\#EB9D86\"$\,main\=\"Promoter\"\,ylab\=\"Percentage\ \%\"\,border\=FALSE\,ylim\=c$0\.000000\,9\.757585$\,cex\.names\=1\) +\>\ text$x\=mp\[1\,\]\,y\=c\(1\.8532425688606797\,\ 3\.616851183410451\,\ 5\.322318854623416$\,label\=c$\"1\.9\ \%\"\,\"3\.6\ \%\"\,\"5\.3\ \%\"$\,pos\=3\,offset\=0\.2\) +\>\ text$x\=mp\[2\,\]\,y\=c\(0\.0\,\ 0\.0\,\ 0\.0$\,label\=c$\"0\.000\ \% +\+\ \(0\.981$\"\,\"0\.000\ \% +\+\ $0\.964$\"\,\"0\.000\ \% +\+\ $0\.947$\"\)\,pos\=3\,offset\=0\.2\) +\>\ legend$\"topleft\"\,legend\=c\(\"Genome\"\,\"ChIP\ \(p\-value$\"\)\,col\=c$\"\#5FA1C1\"\,\"\#EB9D86\"$\,pch\=15\,bty\=\"n\"\) +\>\ r0\<\-c$0\.03876062889120376\,\ 0\.03876062889120376$ +\>\ r1\<\-c$0\.0\,\ 0\.0$ +\>\ height\<\-rbind$r0\,r1$ +\>\ names\=c$\"\<\=2500\ bp\"\,\"\<\=5000\ bp\"$ +\>\ mp\<\-barplot$height\=height\,names\=names\,beside\=TRUE\,horiz\=FALSE\,col\=c\(\"\#5FA1C1\"\,\"\#EB9D86\"$\,main\=\"Bidirectional\ Promoter\"\,ylab\=\"Percentage\ \%\"\,border\=FALSE\,ylim\=c$0\.000000\,0\.071061$\,cex\.names\=1\) +\>\ text$x\=mp\[1\,\]\,y\=c\(0\.03876062889120376\,\ 0\.03876062889120376$\,label\=c$\"0\.04\ \%\"\,\"0\.04\ \%\"$\,pos\=3\,offset\=0\.2\) +\>\ text$x\=mp\[2\,\]\,y\=c\(0\.0\,\ 0\.0$\,label\=c$\"0\.000\ \% +\+\ \(1\.000$\"\,\"0\.000\ \% +\+\ $1\.000$\"\)\,pos\=3\,offset\=0\.2\) +\>\ legend$\"topleft\"\,legend\=c\(\"Genome\"\,\"ChIP\ \(p\-value$\"\)\,col\=c$\"\#5FA1C1\"\,\"\#EB9D86\"$\,pch\=15\,bty\=\"n\"\) +\>\ r0\<\-c$1\.8290171758036773\,\ 3\.4690762857627364\,\ 4\.980740812519683$ +\>\ r1\<\-c$0\.0\,\ 0\.0\,\ 0\.0$ +\>\ height\<\-rbind$r0\,r1$ +\>\ names\=c$\"\<\=1000\ bp\"\,\"\<\=2000\ bp\"\,\"\<\=3000\ bp\"$ +\>\ mp\<\-barplot$height\=height\,names\=names\,beside\=TRUE\,horiz\=FALSE\,col\=c\(\"\#5FA1C1\"\,\"\#EB9D86\"$\,main\=\"Downstream\"\,ylab\=\"Percentage\ \%\"\,border\=FALSE\,ylim\=c$0\.000000\,9\.131358$\,cex\.names\=1\) +\>\ text$x\=mp\[1\,\]\,y\=c\(1\.8290171758036773\,\ 3\.4690762857627364\,\ 4\.980740812519683$\,label\=c$\"1\.8\ \%\"\,\"3\.5\ \%\"\,\"5\.0\ \%\"$\,pos\=3\,offset\=0\.2\) +\>\ text$x\=mp\[2\,\]\,y\=c\(0\.0\,\ 0\.0\,\ 0\.0$\,label\=c$\"0\.000\ \% +\+\ \(0\.982$\"\,\"0\.000\ \% +\+\ $0\.965$\"\,\"0\.000\ \% +\+\ $0\.950$\"\)\,pos\=3\,offset\=0\.2\) +\>\ legend$\"topleft\"\,legend\=c\(\"Genome\"\,\"ChIP\ \(p\-value$\"\)\,col\=c$\"\#5FA1C1\"\,\"\#EB9D86\"$\,pch\=15\,bty\=\"n\"\) +\>\ r0\<\-c$0\.2034933016788197\,\ 1\.3978051793890356\,\ 2\.359553283752029\,\ 19\.734005184234114\,\ 23\.694856949054$ +\>\ r1\<\-c$0\.0\,\ 0\.0\,\ 0\.0\,\ 0\.0\,\ 0\.0$ +\>\ height\<\-rbind$r0\,r1$ +\>\ names\=c$\"5\'UTR\"\,\"3\'UTR\"\,\"Coding\ Exon\"\,\"Intron\"\,\"All\"$ +\>\ mp\<\-barplot$height\=height\,names\=names\,beside\=TRUE\,horiz\=FALSE\,col\=c\(\"\#5FA1C1\"\,\"\#EB9D86\"$\,main\=\"Gene\"\,ylab\=\"Percentage\ \%\"\,border\=FALSE\,ylim\=c$0\.000000\,43\.440571$\,cex\.names\=1\) +\>\ text$x\=mp\[1\,\]\,y\=c\(0\.2034933016788197\,\ 1\.3978051793890356\,\ 2\.359553283752029\,\ 19\.734005184234114\,\ 23\.694856949054$\,label\=c$\"0\.2\ \%\"\,\"1\.4\ \%\"\,\"2\.4\ \%\"\,\"19\.7\ \%\"\,\"23\.7\ \%\"$\,pos\=3\,offset\=0\.2\) +\>\ text$x\=mp\[2\,\]\,y\=c\(0\.0\,\ 0\.0\,\ 0\.0\,\ 0\.0\,\ 0\.0$\,label\=c$\"0\.000\ \% +\+\ \(0\.998$\"\,\"0\.000\ \% +\+\ $0\.986$\"\,\"0\.000\ \% +\+\ $0\.976$\"\,\"0\.000\ \% +\+\ $0\.803$\"\,\"0\.000\ \% +\+\ $0\.763$\"\)\,pos\=3\,offset\=0\.2\) +\>\ legend$\"topleft\"\,legend\=c\(\"Genome\"\,\"ChIP\ \(p\-value$\"\)\,col\=c$\"\#5FA1C1\"\,\"\#EB9D86\"$\,pch\=15\,bty\=\"n\"\) +\>\ +\>\ \#\ +\>\ \#\ Distribution\ of\ Genome\ and\ ChIP\ regions\ over\ cis\-regulatory\ element +\>\ \#\ Note\ that\ the\ x\ may\ be\ modified\ for\ better\ graphics\ in\ case\ a\ value\ is\ too\ small +\>\ \#\ Thus\,\ look\ at\ the\ labels\ of\ the\ pie\ chart\ to\ get\ the\ real\ percentage\ values +\>\ \#\ +\>\ +\>\ par$mfcol\=c\(2\,\ 2$\,mar\=c$3\,\ 3\,\ 4\,\ 2\.8$\,oma\=c$4\,\ 2\,\ 4\,\ 2$\) +\>\ x\<\-c$0\.018532\,0\.017055\,0\.016037\,0\.017830\,0\.015092\,0\.014051\,0\.010000\,0\.013833\,0\.023014\,0\.192592\,0\.670292$ +\>\ pie$x\=x\,labels\=c\(\"1\.9\ \%\"\,\"1\.7\ \%\"\,\"1\.6\ \%\"\,\"1\.8\ \%\"\,\"1\.5\ \%\"\,\"1\.4\ \%\"\,\"0\.2\ \%\"\,\"1\.4\ \%\"\,\"2\.3\ \%\"\,\"19\.3\ \%\"\,\"67\.0\ \%\"$\,main\=\"Genome\"\,col\=c$\"\#445FA2\"\,\"\#EB9D86\"\,\"\#799F7A\"\,\"\#6C527F\"\,\"\#5FA1C1\"\,\"\#E8BB77\"\,\"\#A8C5EF\"\,\"\#FDCDB9\"\,\"\#C6E6B5\"\,\"\#F1D5EE\"\,\"\#B4E1F6\"$\,clockwise\=TRUE\,border\=FALSE\,radius\=0\.9\,cex\=0\.8\,init\.angle\=90\,density\=100\) +\>\ x\<\-c$0\.000000\,1\.000000$ +\>\ y\<\-c$0\.000000\,1\.000000$ +\>\ plot$x\,\ y\,type\=\"n\"\,main\=\"\"\,xlab\=\"\"\,ylab\=\"\"\,frame\=FALSE\,axes\=FALSE\,xaxt\=\"s\"\,yaxt\=\"s\"$ +\>\ legend$\"top\"\,legend\=c\(\"Promoter\ \(\<\=1000\ bp$\:\ 1\.9\ \%\"\,\"Promoter\ $1000\-2000\ bp$\:\ 1\.7\ \%\"\,\"Promoter\ $2000\-3000\ bp$\:\ 1\.6\ \%\"\,\"Downstream\ $\<\=1000\ bp$\:\ 1\.8\ \%\"\,\"Downstream\ $1000\-2000\ bp$\:\ 1\.5\ \%\"\,\"Downstream\ $2000\-3000\ bp$\:\ 1\.4\ \%\"\,\"5\'UTR\:\ 0\.2\ \%\"\,\"3\'UTR\:\ 1\.4\ \%\"\,\"Coding\ exon\:\ 2\.3\ \%\"\,\"Intron\:\ 19\.3\ \%\"\,\"Distal\ intergenic\:\ 67\.0\ \%\"\)\,col\=c$\"\#445FA2\"\,\"\#EB9D86\"\,\"\#799F7A\"\,\"\#6C527F\"\,\"\#5FA1C1\"\,\"\#E8BB77\"\,\"\#A8C5EF\"\,\"\#FDCDB9\"\,\"\#C6E6B5\"\,\"\#F1D5EE\"\,\"\#B4E1F6\"$\,pch\=15\,bty\=\"n\"\) +\>\ x\<\-c$0\.010000\,0\.010000\,0\.010000\,0\.010000\,0\.010000\,0\.010000\,0\.010000\,0\.010000\,0\.010000\,0\.010000\,1\.000000$ +\>\ pie$x\=x\,labels\=c\(\"0\.000\ \%\"\,\"0\.000\ \%\"\,\"0\.000\ \%\"\,\"0\.000\ \%\"\,\"0\.000\ \%\"\,\"0\.000\ \%\"\,\"0\.000\ \%\"\,\"0\.000\ \%\"\,\"0\.000\ \%\"\,\"0\.000\ \%\"\,\"100\.0\ \%\"$\,main\=\"ChIP\"\,col\=c$\"\#445FA2\"\,\"\#EB9D86\"\,\"\#799F7A\"\,\"\#6C527F\"\,\"\#5FA1C1\"\,\"\#E8BB77\"\,\"\#A8C5EF\"\,\"\#FDCDB9\"\,\"\#C6E6B5\"\,\"\#F1D5EE\"\,\"\#B4E1F6\"$\,clockwise\=TRUE\,border\=FALSE\,radius\=0\.9\,cex\=0\.8\,init\.angle\=90\,density\=100\) +\>\ x\<\-c$0\.000000\,1\.000000$ +\>\ y\<\-c$0\.000000\,1\.000000$ +\>\ plot$x\,\ y\,type\=\"n\"\,main\=\"\"\,xlab\=\"\"\,ylab\=\"\"\,frame\=FALSE\,axes\=FALSE\,xaxt\=\"s\"\,yaxt\=\"s\"$ +\>\ legend$\"top\"\,legend\=c\(\"Promoter\ \(\<\=1000\ bp$\:\ 0\.000\ \%\"\,\"Promoter\ $1000\-2000\ bp$\:\ 0\.000\ \%\"\,\"Promoter\ $2000\-3000\ bp$\:\ 0\.000\ \%\"\,\"Downstream\ $\<\=1000\ bp$\:\ 0\.000\ \%\"\,\"Downstream\ $1000\-2000\ bp$\:\ 0\.000\ \%\"\,\"Downstream\ $2000\-3000\ bp$\:\ 0\.000\ \%\"\,\"5\'UTR\:\ 0\.000\ \%\"\,\"3\'UTR\:\ 0\.000\ \%\"\,\"Coding\ exon\:\ 0\.000\ \%\"\,\"Intron\:\ 0\.000\ \%\"\,\"Distal\ intergenic\:\ 100\.0\ \%\"\)\,col\=c$\"\#445FA2\"\,\"\#EB9D86\"\,\"\#799F7A\"\,\"\#6C527F\"\,\"\#5FA1C1\"\,\"\#E8BB77\"\,\"\#A8C5EF\"\,\"\#FDCDB9\"\,\"\#C6E6B5\"\,\"\#F1D5EE\"\,\"\#B4E1F6\"$\,pch\=15\,bty\=\"n\"\) +\>\ +\>\ \#\ +\>\ \#\ ChIP\ regions\ over\ the\ genome +\>\ \#\ +\>\ +\>\ par$mar\=c\(4\,\ 4\,\ 5\,\ 3\.8$\,oma\=c$4\,\ 2\,\ 4\,\ 2$\) +\>\ layout$matrix\(c\(1\,\ 0\,\ 2\,\ 2$\,\ 2\,\ 2\,\ byrow\ \=\ TRUE\)\,widths\=c$1\,\ 1$\,heights\=c$1\,\ 5$\) +\>\ x\<\-c$0\.000000\,0\.000000$ +\>\ y\<\-c$0\.000000\,1\.000000$ +\>\ plot$x\,\ y\,type\=\"n\"\,main\=\"Distribution\ of\ Peak\ Heights\"\,xlab\=\"\"\,ylab\=\"\"\,xlim\=c\(0\.000000\,0\.000000$\,ylim\=c$0\.000000\,1\.000000$\,frame\=FALSE\,xaxt\=\"s\"\,yaxt\=\"n\"\,cex\=0\.9\) +\>\ x\<\-c$0\.000000\,0\.000000\,0\.000000\,0\.000000$ +\>\ y\<\-c$0\.000000\,0\.000000\,1\.000000\,1\.000000$ +\>\ polygon$x\,y\,col\=c\(\"black\"$\) +\>\ x\ \<\-\ c$0\.000000$ +\>\ y\<\-c$0\.800000$ +\>\ lines$x\,\ y\,xlim\=c\(0\,\ 0\.0$\,ylim\=c$0\,\ 1$\,type\=\"l\"\,col\=c$\"cyan\"$\,lwd\=2\) +\>\ x\<\-c$0\.000000\,4127518\.000000$ +\>\ y\<\-c$0\.855556\,1\.144444$ +\>\ plot$x\,\ y\,type\=\"n\"\,main\=\"ChIP\ Regions\ \(Peaks$\ over\ Chromosomes\"\,xlab\=\"Chromosome\ Size\ $bp$\"\,ylab\=\"Chromosome\"\,xlim\=c$0\.000000\,4127518\.000000$\,ylim\=c$0\.855556\,1\.144444$\,frame\=FALSE\,xaxt\=\"s\"\,yaxt\=\"n\"\) +\>\ start\ \<\-\ c$4119129$ +\>\ end\ \<\-\ c$4119130$ +\>\ vals\ \<\-\ c$0\.0$ +\>\ vals\[vals\ \>\ 0\.0\]\ \<\-\ 0\.0 +\>\ vals\[vals\ \<\ 0\]\ \<\-\ 0 +\>\ heights\ \<\-\ 0\.288889\ \*\ $\(vals\ \-\ 0$\/$0\.0\ \-\ 0$\)\ \+\ 0\.855555555556 +\>\ for\ $i\ in\ 1\:length\(heights$\)\ \{ +\+\ \ polygon$x\=c\(start\[i\]\,\ end\[i\]\,\ end\[i\]\,\ start\[i\]$\,\ y\=c$0\.855555555556\,\ 0\.855555555556\,\ heights\[i\]\,\ heights\[i\]$\,\ col\=c$\"\#CC0000\"$\,\ border\=c$\"\#CC0000\"$\) +\+\ \} +\>\ mtext$\"26\"\,side\=2\,line\=0\,outer\=FALSE\,at\=1\.0$ +\>\ par$mar\=c\(4\,\ 4\,\ 5\,\ 3\.8$\,oma\=c$4\,\ 2\,\ 4\,\ 2$\) +\>\ layout$matrix\(c\(1\,\ 2\,\ 3\,\ 3\,\ 4\,\ 5$\,\ 3\,\ 2\,\ byrow\ \=\ TRUE\)\,widths\=c$1\,\ 1$\,heights\=c$1\,\ 1\,\ 1$\) +\>\ 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y\<\-c$0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,250\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000$ +\>\ plot$x\,\ y\,type\=\"l\"\,main\=\"Average\ Concatenated\ Exon\ Profile\"\,xlab\=\"Relative\ Location\ \(\%$\"\,ylab\=\"Average\ Profile\"\,col\=c$\"\#C8524D\"$\,ylim\=c$0\.000000\,250\.000000$\,xaxt\=\"s\"\,yaxt\=\"s\"\,lwd\=2\) +\>\ x\<\-c$0\.000000\,3\.333333\,6\.666667\,10\.000000\,13\.333333\,16\.666667\,20\.000000\,23\.333333\,26\.666667\,30\.000000\,33\.333333\,36\.666667\,40\.000000\,43\.333333\,46\.666667\,50\.000000\,53\.333333\,56\.666667\,60\.000000\,63\.333333\,66\.666667\,70\.000000\,73\.333333\,76\.666667\,80\.000000\,83\.333333\,86\.666667\,90\.000000\,93\.333333\,96\.666667\,100\.000000$ +\>\ y\<\-c$0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000$ +\>\ plot$x\,\ y\,type\=\"l\"\,main\=\"Average\ Concatenated\ Intron\ Profile\"\,xlab\=\"Relative\ Location\ \(\%$\"\,ylab\=\"Average\ Profile\"\,col\=c$\"\#C8524D\"$\,ylim\=c$0\.000000\,250\.000000$\,xaxt\=\"s\"\,yaxt\=\"s\"\,lwd\=2\) +\>\ par$mfrow\=c\(3\,\ 2$\,mar\=c$4\,\ 4\,\ 5\,\ 3\.8$\,oma\=c$4\,\ 2\,\ 4\,\ 2$\) +\>\ x\<\-c$0\.000000\,50\.000000\,100\.000000$ +\>\ y\<\-c$0\.000000\,0\.000000\,0\.000000$ +\>\ plot$x\,\ y\,type\=\"l\"\,main\=\"Average\ Exon\ Profile +\+\ \(56\ \<\=\ length\ \<\ 109\ bp$\"\,xlab\=\"Relative\ Location\ $\%$\"\,ylab\=\"Average\ Profile\"\,col\=c$\"\#C8524D\"$\,ylim\=c$0\.000000\,132\.596685$\,xaxt\=\"s\"\,yaxt\=\"s\"\,lwd\=2\) +\>\ x\<\-c$0\.000000\,25\.000000\,50\.000000\,75\.000000\,100\.000000$ +\>\ y\<\-c$0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000$ +\>\ plot$x\,\ y\,type\=\"l\"\,main\=\"Average\ Intron\ Profile +\+\ \(110\ \<\=\ length\ \<\ 345\ bp$\"\,xlab\=\"Relative\ Location\ $\%$\"\,ylab\=\"Average\ Profile\"\,col\=c$\"\#C8524D\"$\,ylim\=c$0\.000000\,132\.596685$\,xaxt\=\"s\"\,yaxt\=\"s\"\,lwd\=2\) +\>\ x\<\-c$0\.000000\,50\.000000\,100\.000000$ +\>\ y\<\-c$0\.000000\,0\.000000\,0\.000000$ +\>\ plot$x\,\ y\,type\=\"l\"\,main\=\"Average\ Exon\ Profile +\+\ \(109\ \<\=\ length\ \<\ 160\ bp$\"\,xlab\=\"Relative\ Location\ $\%$\"\,ylab\=\"Average\ Profile\"\,col\=c$\"\#C8524D\"$\,ylim\=c$0\.000000\,132\.596685$\,xaxt\=\"s\"\,yaxt\=\"s\"\,lwd\=2\) +\>\ x\<\-c$0\.000000\,11\.111111\,22\.222222\,33\.333333\,44\.444444\,55\.555556\,66\.666667\,77\.777778\,88\.888889\,100\.000000$ +\>\ y\<\-c$0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000$ +\>\ plot$x\,\ y\,type\=\"l\"\,main\=\"Average\ Intron\ Profile +\+\ \(344\ \<\=\ length\ \<\ 686\ bp$\"\,xlab\=\"Relative\ Location\ $\%$\"\,ylab\=\"Average\ Profile\"\,col\=c$\"\#C8524D\"$\,ylim\=c$0\.000000\,132\.596685$\,xaxt\=\"s\"\,yaxt\=\"s\"\,lwd\=2\) +\>\ x\<\-c$0\.000000\,33\.333333\,66\.666667\,100\.000000$ +\>\ y\<\-c$0\.000000\,0\.000000\,0\.000000\,0\.000000$ +\>\ plot$x\,\ y\,type\=\"l\"\,main\=\"Average\ Exon\ Profile +\+\ \(160\ \<\=\ length\ \<\ 375\ bp$\"\,xlab\=\"Relative\ Location\ $\%$\"\,ylab\=\"Average\ Profile\"\,col\=c$\"\#C8524D\"$\,ylim\=c$0\.000000\,132\.596685$\,xaxt\=\"s\"\,yaxt\=\"s\"\,lwd\=2\) +\>\ x\<\-c$0\.000000\,4\.761905\,9\.523810\,14\.285714\,19\.047619\,23\.809524\,28\.571429\,33\.333333\,38\.095238\,42\.857143\,47\.619048\,52\.380952\,57\.142857\,61\.904762\,66\.666667\,71\.428571\,76\.190476\,80\.952381\,85\.714286\,90\.476190\,95\.238095\,100\.000000$ +\>\ y\<\-c$0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,110\.497238\,0\.000000$ +\>\ plot$x\,\ y\,type\=\"l\"\,main\=\"Average\ Intron\ Profile +\+\ \(685\ \<\=\ length\ \<\ 2653\ bp$\"\,xlab\=\"Relative\ Location\ $\%$\"\,ylab\=\"Average\ Profile\"\,col\=c$\"\#C8524D\"$\,ylim\=c$0\.000000\,132\.596685$\,xaxt\=\"s\"\,yaxt\=\"s\"\,lwd\=2\) +\>\ dev\.off +null\ device\ +\ \ \ \ \ \ \ \ \ \ 1\ +\>\ +INFO\ \ \@\ .*\ \#\.\.\.\ cong\!\ See\ ceas\.pdf\ for\ the\ graphical\ results\ of\ CEAS\!\ diff -r 000000000000 -r f411ce97a351 test-data/ceas_out2.pdf Binary file test-data/ceas_out2.pdf has changed diff -r 000000000000 -r f411ce97a351 test-data/ceas_out2.xls --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/ceas_out2.xls Tue Jun 30 07:08:05 2015 -0400 @@ -0,0 +1,133 @@ +# RefSeq: RefSeq ID +# chr: chromosome of a RefSeq gene +# txStart: 5' end of a RefSeq gene +# txEnd: 3' end site of a RefSeq gene +# strand: strand of a RefSeq gene +# dist u TSS: Distance to the nearest ChIP region's center upstream of transcription start site (bp) +# dist d TSS: Distance to the nearest ChIP region's center downstream of transcription start site (bp) +# dist u TTS: Distance to the nearest ChIP region's center upstream of transcription end site (bp) +# dist d TTS: Distance to the nearest ChIP region's center downstream of transcription end (bp) +# 3000bp u TSS: Occupancy rate of ChIP region in 3000bp upstream of transcription start site (0.0 - 1.0) +# 3000bp d TSS: Occupancy rate of ChIP region in 3000bp downstream of transcription start site (0.0 - 1.0) +# 1/3 gene: Occupancy rate of ChIP region in 1/3 gene (0.0 - 1.0) +# 2/3 gene: Occupancy rate of ChIP region in 2/3 gene (0.0 - 1.0) +# 3/3 gene: Occupancy rate of ChIP region in 3/3 gene (0.0 - 1.0) +# 3000bp d TTS: Occupancy rate of ChIP region in 3000bp downstream of transcriptino end (0.0 - 1.0) +# exons: Occupancy rate of ChIP regions in exons (0.0-1.0) +# Note that txStart and txEnd indicate 5' and 3' ends of genes whereas TSS and TTS transcription start and end sites in consideration of strand. +#name chr txStart txEnd strand dist u TSS dist d TSS dist u TTS dist d TTS 3000bp u TSS 3000bp d TSS 1/3 gene 2/3 gene 3/3 gene 3000bp d TTS exons +NM_001031576 chr26 19281 27136 + NA 4099848 NA 4091993 0 0 0 0 0 0 0 +NM_204615 chr26 57466 61594 - 4057535 NA 4061663 NA 0 0 0 0 0 0 0 +NM_001005431 chr26 65800 76175 - 4042954 NA 4053329 NA 0 0 0 0 0 0 0 +NM_001145491 chr26 91618 92166 - 4026963 NA 4027511 NA 0 0 0 0 0 0 0 +NM_204398 chr26 93069 97423 + NA 4026060 NA 4021706 0 0 0 0 0 0 0 +NM_001305147 chr26 254661 282571 + NA 3864468 NA 3836558 0 0 0 0 0 0 0 +NM_001305148 chr26 254661 282571 + NA 3864468 NA 3836558 0 0 0 0 0 0 0 +NM_001012868 chr26 350397 355252 - 3763877 NA 3768732 NA 0 0 0 0 0 0 0 +NM_001031030 chr26 479573 493561 + NA 3639556 NA 3625568 0 0 0 0 0 0 0 +NM_001305140 chr26 520705 526012 + NA 3598424 NA 3593117 0 0 0 0 0 0 0 +NM_001031029 chr26 537101 565572 + NA 3582028 NA 3553557 0 0 0 0 0 0 0 +NM_205248 chr26 537250 760479 + NA 3581879 NA 3358650 0 0 0 0 0 0 0 +NM_204727 chr26 662969 683066 - 3436063 NA 3456160 NA 0 0 0 0 0 0 0 +NR_105475 chr26 669012 669122 - 3450007 NA 3450117 NA 0 0 0 0 0 0 0 +NM_205449 chr26 785617 794076 + NA 3333512 NA 3325053 0 0 0 0 0 0 0 +NM_204681 chr26 897458 902049 - 3217080 NA 3221671 NA 0 0 0 0 0 0 0 +NM_001278156 chr26 905313 917094 - 3202035 NA 3213816 NA 0 0 0 0 0 0 0 +NM_204184 chr26 960209 964268 - 3154861 NA 3158920 NA 0 0 0 0 0 0 0 +NM_204316 chr26 974223 991244 + NA 3144906 NA 3127885 0 0 0 0 0 0 0 +NM_001031028 chr26 993815 1003847 - 3115282 NA 3125314 NA 0 0 0 0 0 0 0 +NM_001006392 chr26 1024606 1047756 - 3071373 NA 3094523 NA 0 0 0 0 0 0 0 +NM_001039596 chr26 1073550 1080033 - 3039096 NA 3045579 NA 0 0 0 0 0 0 0 +NM_001031027 chr26 1090460 1096137 + NA 3028669 NA 3022992 0 0 0 0 0 0 0 +NM_001031026 chr26 1096566 1104751 - 3014378 NA 3022563 NA 0 0 0 0 0 0 0 +NM_001030913 chr26 1122296 1132596 + NA 2996833 NA 2986533 0 0 0 0 0 0 0 +NM_001171886 chr26 1220031 1222791 - 2896338 NA 2899098 NA 0 0 0 0 0 0 0 +NM_205054 chr26 1229703 1232833 + NA 2889426 NA 2886296 0 0 0 0 0 0 0 +NM_204462 chr26 1234686 1236536 - 2882593 NA 2884443 NA 0 0 0 0 0 0 0 +NM_204463 chr26 1265724 1267989 - 2851140 NA 2853405 NA 0 0 0 0 0 0 0 +NM_001030378 chr26 1289091 1290386 - 2828743 NA 2830038 NA 0 0 0 0 0 0 0 +NM_001195554 chr26 1382510 1388447 + NA 2736619 NA 2730682 0 0 0 0 0 0 0 +NM_001012548 chr26 1406905 1428443 + NA 2712224 NA 2690686 0 0 0 0 0 0 0 +NR_031486 chr26 1442696 1442779 - 2676350 NA 2676433 NA 0 0 0 0 0 0 0 +NR_031487 chr26 1442896 1442979 - 2676150 NA 2676233 NA 0 0 0 0 0 0 0 +NM_205250 chr26 1472137 1474003 + NA 2646992 NA 2645126 0 0 0 0 0 0 0 +NR_105486 chr26 1566398 1566508 - 2552621 NA 2552731 NA 0 0 0 0 0 0 0 +NM_001160320 chr26 1697226 1773801 + NA 2421903 NA 2345328 0 0 0 0 0 0 0 +NM_001004709 chr26 1697226 1773801 + NA 2421903 NA 2345328 0 0 0 0 0 0 0 +NM_001160324 chr26 1697226 1773801 + NA 2421903 NA 2345328 0 0 0 0 0 0 0 +NM_001004493 chr26 1697226 1773801 + NA 2421903 NA 2345328 0 0 0 0 0 0 0 +NM_001160323 chr26 1697226 1773801 + NA 2421903 NA 2345328 0 0 0 0 0 0 0 +NM_001160322 chr26 1697226 1773801 + NA 2421903 NA 2345328 0 0 0 0 0 0 0 +NM_001160321 chr26 1697226 1773801 + NA 2421903 NA 2345328 0 0 0 0 0 0 0 +NM_001004395 chr26 1776431 1800083 + NA 2342698 NA 2319046 0 0 0 0 0 0 0 +NM_001030914 chr26 1811042 1820368 - 2298761 NA 2308087 NA 0 0 0 0 0 0 0 +NM_204506 chr26 1823407 1843085 - 2276044 NA 2295722 NA 0 0 0 0 0 0 0 +NR_031488 chr26 1925941 1926037 - 2193092 NA 2193188 NA 0 0 0 0 0 0 0 +NM_213581 chr26 2070404 2084478 - 2034651 NA 2048725 NA 0 0 0 0 0 0 0 +NR_035298 chr26 2086590 2086691 - 2032438 NA 2032539 NA 0 0 0 0 0 0 0 +NR_105470 chr26 2094750 2094860 - 2024269 NA 2024379 NA 0 0 0 0 0 0 0 +NM_001030915 chr26 2117140 2128322 - 1990807 NA 2001989 NA 0 0 0 0 0 0 0 +NM_001031498 chr26 2175178 2177159 - 1941970 NA 1943951 NA 0 0 0 0 0 0 0 +NM_001008452 chr26 2305308 2315138 + NA 1813821 NA 1803991 0 0 0 0 0 0 0 +NM_001006322 chr26 2315293 2325130 - 1793999 NA 1803836 NA 0 0 0 0 0 0 0 +NM_001004414 chr26 2373245 2375480 - 1743649 NA 1745884 NA 0 0 0 0 0 0 0 +NM_001044644 chr26 2390696 2401255 - 1717874 NA 1728433 NA 0 0 0 0 0 0 0 +NM_001031499 chr26 2425841 2429413 - 1689716 NA 1693288 NA 0 0 0 0 0 0 0 +NM_001033642 chr26 2445710 2453125 + NA 1673419 NA 1666004 0 0 0 0 0 0 0 +NM_001033643 chr26 2469318 2475028 + NA 1649811 NA 1644101 0 0 0 0 0 0 0 +NM_204664 chr26 2498398 2509349 + NA 1620731 NA 1609780 0 0 0 0 0 0 0 +NR_031489 chr26 2511657 2511746 - 1607383 NA 1607472 NA 0 0 0 0 0 0 0 +NR_031490 chr26 2512568 2512648 - 1606481 NA 1606561 NA 0 0 0 0 0 0 0 +NR_105523 chr26 2669792 2669902 - 1449227 NA 1449337 NA 0 0 0 0 0 0 0 +NR_031491 chr26 2896046 2896142 + NA 1223083 NA 1222987 0 0 0 0 0 0 0 +NM_001190924 chr26 2961382 2962268 + NA 1157747 NA 1156861 0 0 0 0 0 0 0 +NM_001007881 chr26 2999189 3002725 + NA 1119940 NA 1116404 0 0 0 0 0 0 0 +NM_204320 chr26 3006741 3011817 - 1107312 NA 1112388 NA 0 0 0 0 0 0 0 +NM_001030916 chr26 3035271 3039335 - 1079794 NA 1083858 NA 0 0 0 0 0 0 0 +NM_204151 chr26 3047964 3050306 - 1068823 NA 1071165 NA 0 0 0 0 0 0 0 +NM_204326 chr26 3124816 3214381 - 904748 NA 994313 NA 0 0 0 0 0 0 0 +NM_204336 chr26 3320769 3332327 + NA 798360 NA 786802 0 0 0 0 0 0 0 +NM_204622 chr26 3339753 3358863 - 760266 NA 779376 NA 0 0 0 0 0 0 0 +NM_205515 chr26 3359016 3368964 + NA 760113 NA 750165 0 0 0 0 0 0 0 +NM_001012843 chr26 3370712 3377196 + NA 748417 NA 741933 0 0 0 0 0 0 0 +NM_001029849 chr26 3377655 3382628 - 736501 NA 741474 NA 0 0 0 0 0 0 0 +NM_001006323 chr26 3439841 3454783 - 664346 NA 679288 NA 0 0 0 0 0 0 0 +NR_035162 chr26 3455233 3455324 + NA 663896 NA 663805 0 0 0 0 0 0 0 +NM_001012697 chr26 3516478 3545774 + NA 602651 NA 573355 0 0 0 0 0 0 0 +NM_001030917 chr26 3590932 3597509 - 521620 NA 528197 NA 0 0 0 0 0 0 0 +NM_001031500 chr26 3597231 3600802 + NA 521898 NA 518327 0 0 0 0 0 0 0 +NM_001040018 chr26 3629575 3631171 + NA 489554 NA 487958 0 0 0 0 0 0 0 +NM_001257295 chr26 3698350 3701362 - 417767 NA 420779 NA 0 0 0 0 0 0 0 +NM_001257296 chr26 3701377 3715857 - 403272 NA 417752 NA 0 0 0 0 0 0 0 +NM_001012549 chr26 3735643 3742472 - 376657 NA 383486 NA 0 0 0 0 0 0 0 +NM_001030918 chr26 3742618 3760175 - 358954 NA 376511 NA 0 0 0 0 0 0 0 +NM_001006324 chr26 3760758 3765368 - 353761 NA 358371 NA 0 0 0 0 0 0 0 +NM_205063 chr26 3809805 3812700 + NA 309324 NA 306429 0 0 0 0 0 0 0 +NM_001293109 chr26 3859074 3879130 - 239999 NA 260055 NA 0 0 0 0 0 0 0 +NM_001293108 chr26 3859074 3882051 - 237078 NA 260055 NA 0 0 0 0 0 0 0 +NR_102328 chr26 3916006 3918143 - 200986 NA 203123 NA 0 0 0 0 0 0 0 +NM_204728 chr26 3920817 3937442 - 181687 NA 198312 NA 0 0 0 0 0 0 0 +NM_001244905 chr26 4104910 4108376 + NA 14219 NA 10753 0 0 0 0 0 0 0 +NM_001293166 chr26 4138324 4142325 - NA 23196 NA 19195 0 0 0 0 0 0 0 +NM_001030919 chr26 4144091 4175943 + 24962 NA 56814 NA 0 0 0 0 0 0 0 +NM_001257297 chr26 4209891 4216177 + 90762 NA 97048 NA 0 0 0 0 0 0 0 +NM_001257298 chr26 4218028 4238067 + 98899 NA 118938 NA 0 0 0 0 0 0 0 +NM_205490 chr26 4375371 4380959 - NA 261830 NA 256242 0 0 0 0 0 0 0 +NM_001305129 chr26 4391940 4397490 + 272811 NA 278361 NA 0 0 0 0 0 0 0 +NM_001271612 chr26 4433568 4438784 + 314439 NA 319655 NA 0 0 0 0 0 0 0 +NM_001030920 chr26 4498991 4730550 + 379862 NA 611421 NA 0 0 0 0 0 0 0 +NM_001030921 chr26 4541748 4544997 - NA 425868 NA 422619 0 0 0 0 0 0 0 +NM_001006325 chr26 4548211 4559974 + 429082 NA 440845 NA 0 0 0 0 0 0 0 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Jan 01 00:00:00 1970 +0000 +++ b/test-data/ceas_out3.log Tue Jun 30 07:08:05 2015 -0400 @@ -0,0 +1,235 @@ +/home/pjb/galaxy-tools/ceas/test.tool_dependencies.ceas/bx_python/0.7.1/lib/python2.7/site-packages/pkg_resources.py:1054: UserWarning: /home/pjb/.python-eggs is writable by group/others and vulnerable to attack when used with get_resource_filename. Consider a more secure location (set with .set_extraction_path or the PYTHON_EGG_CACHE environment variable). + warnings.warn(msg, UserWarning) +ceasBW -- 0.9.9.7 (package version 1.0.2) +/home/pjb/galaxy-tools/ceas/test.tool_dependencies.ceas/bx_python/0.7.1/lib/python2.7/site-packages/pkg_resources.py:1054: UserWarning: /home/pjb/.python-eggs is writable by group/others and vulnerable to attack when used with get_resource_filename. Consider a more secure location (set with .set_extraction_path or the PYTHON_EGG_CACHE environment variable). + warnings.warn(msg, UserWarning) +INFO @ Tue, 23 Jun 2015 13:03:32: +# ARGUMENTS: +# name = ceas +# gene annotation table = galGal3.refGene +# BED file = ceas_in.bed +# WIG file = ceas_in.bigwig +# extra BED file = None +# ChIP annotation = On +# gene-centered annotation = On +# average profiling = On +# dump profiles = Off +# re-annotation for genome background (ChIP region annotation) = False +# promoter sizes (ChIP region annotation) = 1000,2000,3000 bp +# downstream sizes (ChIP region annotation) = 1000,2000,3000 bp +# bidrectional promoter sizes (ChIP region annotation) = 2500,5000 bp +# span size (gene-centered annotation) = 3000 bp +# profiling resolution (average profiling) = 50 bp +# relative distance wrt TSS and TTS (average profiling) = 3000 bp +INFO @ Tue, 23 Jun 2015 13:03:32: #1 read the gene table... +INFO @ Tue, 23 Jun 2015 13:03:32: #2 read the bed file of ChIP regions... +INFO @ Tue, 23 Jun 2015 13:03:32: #3 perform gene-centered annotation... +INFO @ Tue, 23 Jun 2015 13:03:32: #4 See ceas.xls for gene-centered annotation! +INFO @ Tue, 23 Jun 2015 13:03:32: #5 read the pre-computed genome bg annotation... +INFO @ Tue, 23 Jun 2015 13:03:32: #6 perform ChIP region annotation... +INFO @ Tue, 23 Jun 2015 13:03:32: #7 write a R script of ChIP region annotation... +INFO @ Tue, 23 Jun 2015 13:03:32: #8-1 run wig profiling of chr26... +INFO @ Tue, 23 Jun 2015 13:03:32: #9 append an R script of wig profiling... + +R version 3.1.2 (2014-10-31) -- "Pumpkin Helmet" +Copyright (C) 2014 The R Foundation for Statistical Computing +Platform: x86_64-redhat-linux-gnu (64-bit) + +R is free software and comes with ABSOLUTELY NO WARRANTY. +You are welcome to redistribute it under certain conditions. +Type 'license()' or 'licence()' for distribution details. + + Natural language support but running in an English locale + +R is a collaborative project with many contributors. +Type 'contributors()' for more information and +'citation()' on how to cite R or R packages in publications. + +Type 'demo()' for some demos, 'help()' for on-line help, or +'help.start()' for an HTML browser interface to help. +Type 'q()' to quit R. + +> # ARGUMENTS: +> # name = ceas +> # gene annotation table = galGal3.refGene +> # BED file = ceas_in.bed +> # WIG file = ceas_in.bigwig +> # extra BED file = None +> # ChIP annotation = On +> # gene-centered annotation = On +> # average profiling = On +> # dump profiles = Off +> # re-annotation for genome background (ChIP region annotation) = False +> # promoter sizes (ChIP region annotation) = 1000,2000,3000 bp +> # downstream sizes (ChIP region annotation) = 1000,2000,3000 bp +> # bidrectional promoter sizes (ChIP region annotation) = 2500,5000 bp +> # span size (gene-centered annotation) = 3000 bp +> # profiling resolution (average profiling) = 50 bp +> # relative distance wrt TSS and TTS (average profiling) = 3000 bp +> pdf("ceas.pdf",height=11.5,width=8.5) +> +> # 13:03:32 Tue, 23 Jun 2015 +> # +> # ChIP annotation +> # +> +> +> # +> # Chromosomal Distribution +> # +> +> par(mar=c(4, 4, 5, 3.8),oma=c(4, 2, 4, 2)) +> r0<-c(100.0) +> r1<-c(100.0) +> height<-rbind(r0,r1) +> names=c("26") +> mp<-barplot(height=height,names=names,beside=TRUE,horiz=TRUE,col=c("#5FA1C1","#EB9D86"),main="Chromosomal Distribution of ChIP Regions",xlab="Percentage %",ylab="Chromosome",border=FALSE,xlim=c(0.000000,183.333333),cex.names=1) +> text(x=c(100.0),y=mp[1,],label=c("100.0 %"),pos=4,offset=0.2,cex=0.9) +> text(x=c(100.0),y=mp[2,],label=c("100.0 % (<=4.9e-324)"),pos=4,offset=0.2,cex=0.9) +> legend("right",legend=c("Genome","ChIP (p-value)"),col=c("#5FA1C1","#EB9D86"),pch=15,bty="n") +> +> # +> # Promoter,Bipromoter,Downstream, Gene and Regions of interest +> # +> +> par(mfrow=c(4, 1),mar=c(4, 4, 5, 3.8),oma=c(4, 2, 4, 2)) +> r0<-c(1.8532425688606797, 3.616851183410451, 5.322318854623416) +> r1<-c(0.0, 0.0, 0.0) +> height<-rbind(r0,r1) +> names=c("<=1000 bp","<=2000 bp","<=3000 bp") +> mp<-barplot(height=height,names=names,beside=TRUE,horiz=FALSE,col=c("#5FA1C1","#EB9D86"),main="Promoter",ylab="Percentage %",border=FALSE,ylim=c(0.000000,9.757585),cex.names=1) +> text(x=mp[1,],y=c(1.8532425688606797, 3.616851183410451, 5.322318854623416),label=c("1.9 %","3.6 %","5.3 %"),pos=3,offset=0.2) +> text(x=mp[2,],y=c(0.0, 0.0, 0.0),label=c("0.000 % ++ (0.981)","0.000 % ++ (0.964)","0.000 % ++ (0.947)"),pos=3,offset=0.2) +> legend("topleft",legend=c("Genome","ChIP (p-value)"),col=c("#5FA1C1","#EB9D86"),pch=15,bty="n") +> r0<-c(0.03876062889120376, 0.03876062889120376) +> r1<-c(0.0, 0.0) +> height<-rbind(r0,r1) +> names=c("<=2500 bp","<=5000 bp") +> mp<-barplot(height=height,names=names,beside=TRUE,horiz=FALSE,col=c("#5FA1C1","#EB9D86"),main="Bidirectional Promoter",ylab="Percentage %",border=FALSE,ylim=c(0.000000,0.071061),cex.names=1) +> text(x=mp[1,],y=c(0.03876062889120376, 0.03876062889120376),label=c("0.04 %","0.04 %"),pos=3,offset=0.2) +> text(x=mp[2,],y=c(0.0, 0.0),label=c("0.000 % ++ (1.000)","0.000 % ++ (1.000)"),pos=3,offset=0.2) +> legend("topleft",legend=c("Genome","ChIP (p-value)"),col=c("#5FA1C1","#EB9D86"),pch=15,bty="n") +> r0<-c(1.8290171758036773, 3.4690762857627364, 4.980740812519683) +> r1<-c(0.0, 0.0, 0.0) +> height<-rbind(r0,r1) +> names=c("<=1000 bp","<=2000 bp","<=3000 bp") +> mp<-barplot(height=height,names=names,beside=TRUE,horiz=FALSE,col=c("#5FA1C1","#EB9D86"),main="Downstream",ylab="Percentage %",border=FALSE,ylim=c(0.000000,9.131358),cex.names=1) +> text(x=mp[1,],y=c(1.8290171758036773, 3.4690762857627364, 4.980740812519683),label=c("1.8 %","3.5 %","5.0 %"),pos=3,offset=0.2) +> text(x=mp[2,],y=c(0.0, 0.0, 0.0),label=c("0.000 % ++ (0.982)","0.000 % ++ (0.965)","0.000 % ++ (0.950)"),pos=3,offset=0.2) +> legend("topleft",legend=c("Genome","ChIP (p-value)"),col=c("#5FA1C1","#EB9D86"),pch=15,bty="n") +> r0<-c(0.2034933016788197, 1.3978051793890356, 2.359553283752029, 19.734005184234114, 23.694856949054) +> r1<-c(0.0, 0.0, 0.0, 0.0, 0.0) +> height<-rbind(r0,r1) +> names=c("5'UTR","3'UTR","Coding Exon","Intron","All") +> mp<-barplot(height=height,names=names,beside=TRUE,horiz=FALSE,col=c("#5FA1C1","#EB9D86"),main="Gene",ylab="Percentage %",border=FALSE,ylim=c(0.000000,43.440571),cex.names=1) +> text(x=mp[1,],y=c(0.2034933016788197, 1.3978051793890356, 2.359553283752029, 19.734005184234114, 23.694856949054),label=c("0.2 %","1.4 %","2.4 %","19.7 %","23.7 %"),pos=3,offset=0.2) +> text(x=mp[2,],y=c(0.0, 0.0, 0.0, 0.0, 0.0),label=c("0.000 % ++ (0.998)","0.000 % ++ (0.986)","0.000 % ++ (0.976)","0.000 % ++ (0.803)","0.000 % ++ (0.763)"),pos=3,offset=0.2) +> legend("topleft",legend=c("Genome","ChIP (p-value)"),col=c("#5FA1C1","#EB9D86"),pch=15,bty="n") +> +> # +> # Distribution of Genome and ChIP regions over cis-regulatory element +> # Note that the x may be modified for better graphics in case a value is too small +> # Thus, look at the labels of the pie chart to get the real percentage values +> # +> +> par(mfcol=c(2, 2),mar=c(3, 3, 4, 2.8),oma=c(4, 2, 4, 2)) +> x<-c(0.018532,0.017055,0.016037,0.017830,0.015092,0.014051,0.010000,0.013833,0.023014,0.192592,0.670292) +> pie(x=x,labels=c("1.9 %","1.7 %","1.6 %","1.8 %","1.5 %","1.4 %","0.2 %","1.4 %","2.3 %","19.3 %","67.0 %"),main="Genome",col=c("#445FA2","#EB9D86","#799F7A","#6C527F","#5FA1C1","#E8BB77","#A8C5EF","#FDCDB9","#C6E6B5","#F1D5EE","#B4E1F6"),clockwise=TRUE,border=FALSE,radius=0.9,cex=0.8,init.angle=90,density=100) +> x<-c(0.000000,1.000000) +> y<-c(0.000000,1.000000) +> plot(x, y,type="n",main="",xlab="",ylab="",frame=FALSE,axes=FALSE,xaxt="s",yaxt="s") +> legend("top",legend=c("Promoter (<=1000 bp): 1.9 %","Promoter (1000-2000 bp): 1.7 %","Promoter (2000-3000 bp): 1.6 %","Downstream (<=1000 bp): 1.8 %","Downstream (1000-2000 bp): 1.5 %","Downstream (2000-3000 bp): 1.4 %","5'UTR: 0.2 %","3'UTR: 1.4 %","Coding exon: 2.3 %","Intron: 19.3 %","Distal intergenic: 67.0 %"),col=c("#445FA2","#EB9D86","#799F7A","#6C527F","#5FA1C1","#E8BB77","#A8C5EF","#FDCDB9","#C6E6B5","#F1D5EE","#B4E1F6"),pch=15,bty="n") +> x<-c(0.010000,0.010000,0.010000,0.010000,0.010000,0.010000,0.010000,0.010000,0.010000,0.010000,1.000000) +> pie(x=x,labels=c("0.000 %","0.000 %","0.000 %","0.000 %","0.000 %","0.000 %","0.000 %","0.000 %","0.000 %","0.000 %","100.0 %"),main="ChIP",col=c("#445FA2","#EB9D86","#799F7A","#6C527F","#5FA1C1","#E8BB77","#A8C5EF","#FDCDB9","#C6E6B5","#F1D5EE","#B4E1F6"),clockwise=TRUE,border=FALSE,radius=0.9,cex=0.8,init.angle=90,density=100) +> x<-c(0.000000,1.000000) +> y<-c(0.000000,1.000000) +> plot(x, y,type="n",main="",xlab="",ylab="",frame=FALSE,axes=FALSE,xaxt="s",yaxt="s") +> legend("top",legend=c("Promoter (<=1000 bp): 0.000 %","Promoter (1000-2000 bp): 0.000 %","Promoter (2000-3000 bp): 0.000 %","Downstream (<=1000 bp): 0.000 %","Downstream (1000-2000 bp): 0.000 %","Downstream (2000-3000 bp): 0.000 %","5'UTR: 0.000 %","3'UTR: 0.000 %","Coding exon: 0.000 %","Intron: 0.000 %","Distal intergenic: 100.0 %"),col=c("#445FA2","#EB9D86","#799F7A","#6C527F","#5FA1C1","#E8BB77","#A8C5EF","#FDCDB9","#C6E6B5","#F1D5EE","#B4E1F6"),pch=15,bty="n") +> +> # +> # ChIP regions over the genome +> # +> +> par(mar=c(4, 4, 5, 3.8),oma=c(4, 2, 4, 2)) +> layout(matrix(c(1, 0, 2, 2), 2, 2, byrow = TRUE),widths=c(1, 1),heights=c(1, 5)) +> x<-c(0.000000,0.000000) +> y<-c(0.000000,1.000000) +> plot(x, y,type="n",main="Distribution of Peak Heights",xlab="",ylab="",xlim=c(0.000000,0.000000),ylim=c(0.000000,1.000000),frame=FALSE,xaxt="s",yaxt="n",cex=0.9) +> x<-c(0.000000,0.000000,0.000000,0.000000) +> y<-c(0.000000,0.000000,1.000000,1.000000) +> polygon(x,y,col=c("black")) +> x <- c(0.000000) +> y<-c(0.800000) +> lines(x, y,xlim=c(0, 0.0),ylim=c(0, 1),type="l",col=c("cyan"),lwd=2) +> x<-c(0.000000,4127518.000000) +> y<-c(0.855556,1.144444) +> plot(x, y,type="n",main="ChIP Regions (Peaks) over Chromosomes",xlab="Chromosome Size (bp)",ylab="Chromosome",xlim=c(0.000000,4127518.000000),ylim=c(0.855556,1.144444),frame=FALSE,xaxt="s",yaxt="n") +> start <- c(4119129) +> end <- c(4119130) +> vals <- c(0.0) +> vals[vals > 0.0] <- 0.0 +> vals[vals < 0] <- 0 +> heights <- 0.288889 * ((vals - 0)/(0.0 - 0)) + 0.855555555556 +> for (i in 1:length(heights)) { ++ polygon(x=c(start[i], end[i], end[i], start[i]), y=c(0.855555555556, 0.855555555556, heights[i], heights[i]), col=c("#CC0000"), border=c("#CC0000")) ++ } +> mtext("26",side=2,line=0,outer=FALSE,at=1.0) +> par(mar=c(4, 4, 5, 3.8),oma=c(4, 2, 4, 2)) +> layout(matrix(c(1, 2, 3, 3, 4, 5), 3, 2, byrow = TRUE),widths=c(1, 1),heights=c(1, 1, 1)) +> x<-c(-3000.000000,-2950.000000,-2900.000000,-2850.000000,-2800.000000,-2750.000000,-2700.000000,-2650.000000,-2600.000000,-2550.000000,-2500.000000,-2450.000000,-2400.000000,-2350.000000,-2300.000000,-2250.000000,-2200.000000,-2150.000000,-2100.000000,-2050.000000,-2000.000000,-1950.000000,-1900.000000,-1850.000000,-1800.000000,-1750.000000,-1700.000000,-1650.000000,-1600.000000,-1550.000000,-1500.000000,-1450.000000,-1400.000000,-1350.000000,-1300.000000,-1250.000000,-1200.000000,-1150.000000,-1100.000000,-1050.000000,-1000.000000,-950.000000,-900.000000,-850.000000,-800.000000,-750.000000,-700.000000,-650.000000,-600.000000,-550.000000,-500.000000,-450.000000,-400.000000,-350.000000,-300.000000,-250.000000,-200.000000,-150.000000,-100.000000,-50.000000,0.000000,50.000000,100.000000,150.000000,200.000000,250.000000,300.000000,350.000000,400.000000,450.000000,500.000000,550.000000,600.000000,650.000000,700.000000,750.000000,800.000000,850.000000,900.000000,950.000000,1000.000000,1050.000000,1100.000000,1150.000000,1200.000000,1250.000000,1300.000000,1350.000000,1400.000000,1450.000000,1500.000000,1550.000000,1600.000000,1650.000000,1700.000000,1750.000000,1800.000000,1850.000000,1900.000000,1950.000000,2000.000000,2050.000000,2100.000000,2150.000000,2200.000000,2250.000000,2300.000000,2350.000000,2400.000000,2450.000000,2500.000000,2550.000000,2600.000000,2650.000000,2700.000000,2750.000000,2800.000000,2850.000000,2900.000000,2950.000000,3000.000000) +> y<-c(0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,20000.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000) +> plot(x, y,type="l",main="Average Profile near TSS",xlab="Relative Distance to TSS (bp)",ylab="Average Profile",col=c("#C8524D"),xaxt="s",yaxt="s",lwd=2) +> abline(v=0.000000,lty=2,col=c("black")) +> x<-c(-3000.000000,-2950.000000,-2900.000000,-2850.000000,-2800.000000,-2750.000000,-2700.000000,-2650.000000,-2600.000000,-2550.000000,-2500.000000,-2450.000000,-2400.000000,-2350.000000,-2300.000000,-2250.000000,-2200.000000,-2150.000000,-2100.000000,-2050.000000,-2000.000000,-1950.000000,-1900.000000,-1850.000000,-1800.000000,-1750.000000,-1700.000000,-1650.000000,-1600.000000,-1550.000000,-1500.000000,-1450.000000,-1400.000000,-1350.000000,-1300.000000,-1250.000000,-1200.000000,-1150.000000,-1100.000000,-1050.000000,-1000.000000,-950.000000,-900.000000,-850.000000,-800.000000,-750.000000,-700.000000,-650.000000,-600.000000,-550.000000,-500.000000,-450.000000,-400.000000,-350.000000,-300.000000,-250.000000,-200.000000,-150.000000,-100.000000,-50.000000,0.000000,50.000000,100.000000,150.000000,200.000000,250.000000,300.000000,350.000000,400.000000,450.000000,500.000000,550.000000,600.000000,650.000000,700.000000,750.000000,800.000000,850.000000,900.000000,950.000000,1000.000000,1050.000000,1100.000000,1150.000000,1200.000000,1250.000000,1300.000000,1350.000000,1400.000000,1450.000000,1500.000000,1550.000000,1600.000000,1650.000000,1700.000000,1750.000000,1800.000000,1850.000000,1900.000000,1950.000000,2000.000000,2050.000000,2100.000000,2150.000000,2200.000000,2250.000000,2300.000000,2350.000000,2400.000000,2450.000000,2500.000000,2550.000000,2600.000000,2650.000000,2700.000000,2750.000000,2800.000000,2850.000000,2900.000000,2950.000000,3000.000000) +> y<-c(0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,20000.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,20000.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,20000.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,20000.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,20000.000000,0.000000,0.000000,0.000000,0.000000,20000.000000,0.000000,0.000000,0.000000,0.000000,0.000000,20000.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,20000.000000,0.000000,0.000000) +> plot(x, y,type="l",main="Average Profile near TTS",xlab="Relative Distance to TTS (bp)",ylab="Average Profile",col=c("#C8524D"),xaxt="s",yaxt="s",lwd=2) +> abline(v=0.000000,lty=2,col=c("black")) +> x<-c(-1000.000000,-950.000000,-900.000000,-850.000000,-800.000000,-750.000000,-700.000000,-650.000000,-600.000000,-550.000000,-500.000000,-450.000000,-400.000000,-350.000000,-300.000000,-250.000000,-200.000000,-150.000000,-100.000000,-50.000000,0.000000,50.000000,100.000000,150.000000,200.000000,250.000000,300.000000,350.000000,400.000000,450.000000,500.000000,550.000000,600.000000,650.000000,700.000000,750.000000,800.000000,850.000000,900.000000,950.000000,1000.000000,1050.000000,1100.000000,1150.000000,1200.000000,1250.000000,1300.000000,1350.000000,1400.000000,1450.000000,1500.000000,1550.000000,1600.000000,1650.000000,1700.000000,1750.000000,1800.000000,1850.000000,1900.000000,1950.000000,2000.000000,2050.000000,2100.000000,2150.000000,2200.000000,2250.000000,2300.000000,2350.000000,2400.000000,2450.000000,2500.000000,2550.000000,2600.000000,2650.000000,2700.000000,2750.000000,2800.000000,2850.000000,2900.000000,2950.000000,3000.000000,3050.000000,3100.000000,3150.000000,3200.000000,3250.000000,3300.000000,3350.000000,3400.000000,3450.000000,3500.000000,3550.000000,3600.000000,3650.000000,3700.000000,3750.000000,3800.000000,3850.000000,3900.000000,3950.000000,4000.000000) +> y<-c(0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,20000.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,20000.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,20000.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000) +> plot(x, y,type="l",main="Average Gene Profile",xlab="Upstream (bp), 3000 bp of Meta-gene, Downstream (bp)",ylab="Average Profile",col=c("#C8524D"),xaxt="s",yaxt="s",lwd=2) +> abline(v=0.000000,lty=2,col=c("black")) +> abline(v=3000.000000,lty=2,col=c("black")) +> x<-c(0.000000,3.333333,6.666667,10.000000,13.333333,16.666667,20.000000,23.333333,26.666667,30.000000,33.333333,36.666667,40.000000,43.333333,46.666667,50.000000,53.333333,56.666667,60.000000,63.333333,66.666667,70.000000,73.333333,76.666667,80.000000,83.333333,86.666667,90.000000,93.333333,96.666667,100.000000) +> y<-c(0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,20000.000000,0.000000,0.000000,0.000000,0.000000) +> plot(x, y,type="l",main="Average Concatenated Exon Profile",xlab="Relative Location (%)",ylab="Average Profile",col=c("#C8524D"),ylim=c(0.000000,20000.000000),xaxt="s",yaxt="s",lwd=2) +> x<-c(0.000000,3.333333,6.666667,10.000000,13.333333,16.666667,20.000000,23.333333,26.666667,30.000000,33.333333,36.666667,40.000000,43.333333,46.666667,50.000000,53.333333,56.666667,60.000000,63.333333,66.666667,70.000000,73.333333,76.666667,80.000000,83.333333,86.666667,90.000000,93.333333,96.666667,100.000000) +> y<-c(0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000) +> plot(x, y,type="l",main="Average Concatenated Intron Profile",xlab="Relative Location (%)",ylab="Average Profile",col=c("#C8524D"),ylim=c(0.000000,20000.000000),xaxt="s",yaxt="s",lwd=2) +> par(mfrow=c(3, 2),mar=c(4, 4, 5, 3.8),oma=c(4, 2, 4, 2)) +> x<-c(-3.000000,3.000000) +> y<-c(0.000000,1.000000) +> plot(x, y,type="n",main="",xlab="",ylab="",xlim=c(-3.000000,3.000000),ylim=c(0.000000,1.000000),axes=FALSE,xaxt="s",yaxt="s") +> x<-c(-3.000000,3.000000) +> y<-c(0.000000,1.000000) +> plot(x, y,type="n",main="",xlab="",ylab="",xlim=c(-3.000000,3.000000),ylim=c(0.000000,1.000000),axes=FALSE,xaxt="s",yaxt="s") +> x<-c(-3.000000,3.000000) +> y<-c(0.000000,1.000000) +> plot(x, y,type="n",main="",xlab="",ylab="",xlim=c(-3.000000,3.000000),ylim=c(0.000000,1.000000),axes=FALSE,xaxt="s",yaxt="s") +> x<-c(-3.000000,3.000000) +> y<-c(0.000000,1.000000) +> plot(x, y,type="n",main="",xlab="",ylab="",xlim=c(-3.000000,3.000000),ylim=c(0.000000,1.000000),axes=FALSE,xaxt="s",yaxt="s") +> x<-c(-3.000000,3.000000) +> y<-c(0.000000,1.000000) +> plot(x, y,type="n",main="",xlab="",ylab="",xlim=c(-3.000000,3.000000),ylim=c(0.000000,1.000000),axes=FALSE,xaxt="s",yaxt="s") +> x<-c(0.000000,4.761905,9.523810,14.285714,19.047619,23.809524,28.571429,33.333333,38.095238,42.857143,47.619048,52.380952,57.142857,61.904762,66.666667,71.428571,76.190476,80.952381,85.714286,90.476190,95.238095,100.000000) +> y<-c(0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,20000.000000,0.000000) +> plot(x, y,type="l",main="Average Intron Profile ++ (685 <= length < 2653 bp)",xlab="Relative Location (%)",ylab="Average Profile",col=c("#C8524D"),ylim=c(0.000000,24000.000000),xaxt="s",yaxt="s",lwd=2) +> dev.off() +null device + 1 +> +INFO @ Tue, 23 Jun 2015 13:03:33: #... cong! See ceas.pdf for the graphical results of CEAS! diff -r 000000000000 -r f411ce97a351 test-data/ceas_out3.log.re_match --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/ceas_out3.log.re_match Tue Jun 30 07:08:05 2015 -0400 @@ -0,0 +1,231 @@ +ceasBW\ \-\-\ 0\.9\.9\.7\ $package\ version\ 1\.0\.2$ +INFO\ \ \@\ .*\ +\#\ ARGUMENTS\:\ +\#\ name\ \=\ ceas +\#\ gene\ annotation\ table\ \=\ .*galGal3\.refGene +\#\ BED\ file\ \=\ .* +\#\ WIG\ file\ \=\ .* +\#\ extra\ BED\ file\ \=\ None +\#\ ChIP\ annotation\ \=\ On +\#\ gene\-centered\ annotation\ \=\ \ On +\#\ average\ profiling\ \=\ On +\#\ dump\ profiles\ \=\ Off +\#\ re\-annotation\ for\ genome\ background\ $ChIP\ region\ annotation$\ \=\ False +\#\ promoter\ sizes\ $ChIP\ region\ annotation$\ \=\ 1000\,2000\,3000\ bp +\#\ downstream\ sizes\ $ChIP\ region\ annotation$\ \=\ 1000\,2000\,3000\ bp +\#\ bidrectional\ promoter\ sizes\ $ChIP\ region\ annotation$\ \=\ 2500\,5000\ bp +\#\ span\ size\ $gene\-centered\ annotation$\ \=\ 3000\ bp +\#\ profiling\ resolution\ $average\ profiling$\ \=\ 50\ bp +\#\ relative\ distance\ wrt\ TSS\ and\ TTS\ $average\ profiling$\ \=\ 3000\ bp\ +INFO\ \ \@\ .*\ \#1\ read\ the\ gene\ table\.\.\.\ +INFO\ \ \@\ .*\ \#2\ read\ the\ bed\ file\ of\ ChIP\ regions\.\.\.\ +INFO\ \ \@\ .*\ \#3\ perform\ gene\-centered\ annotation\.\.\.\ +INFO\ \ \@\ .*\ \#4\ See\ ceas\.xls\ for\ gene\-centered\ annotation\!\ +INFO\ \ \@\ .*\ \#5\ read\ the\ pre\-computed\ genome\ bg\ annotation\.\.\.\ +INFO\ \ \@\ .*\ \#6\ perform\ ChIP\ region\ annotation\.\.\.\ +INFO\ \ \@\ .*\ \#7\ write\ a\ R\ script\ of\ ChIP\ region\ annotation\.\.\.\ +INFO\ \ \@\ .*\ \#8\-1\ run\ wig\ profiling\ of\ chr26\.\.\.\ +INFO\ \ \@\ .*\ \#9\ append\ an\ R\ script\ of\ wig\ profiling\.\.\.\ + +R\ version\ 3\.1\.2\ $2014\-10\-31$\ \-\-\ \"Pumpkin\ Helmet\" +Copyright\ $C$\ 2014\ The\ R\ Foundation\ for\ Statistical\ Computing +Platform\:\ .* + +R\ is\ free\ software\ and\ comes\ with\ ABSOLUTELY\ NO\ WARRANTY\. +You\ are\ welcome\ to\ redistribute\ it\ under\ certain\ conditions\. +Type\ \'license\'\ or\ \'licence\'\ for\ distribution\ details\. + +\ \ Natural\ language\ support\ but\ running\ in\ an\ English\ locale + +R\ is\ a\ collaborative\ project\ with\ many\ contributors\. +Type\ \'contributors\'\ for\ more\ information\ and +\'citation\'\ on\ how\ to\ cite\ R\ or\ R\ packages\ in\ publications\. + +Type\ \'demo\'\ for\ some\ demos\,\ \'help\'\ for\ on\-line\ help\,\ or +\'help\.start\'\ for\ an\ HTML\ browser\ interface\ to\ help\. +Type\ \'q\'\ to\ quit\ R\. + +\>\ \#\ ARGUMENTS\:\ +\>\ \#\ name\ \=\ ceas +\>\ \#\ gene\ annotation\ table\ \=\ .*galGal3\.refGene +\>\ \#\ BED\ file\ \=\ .* +\>\ \#\ WIG\ file\ \=\ .* +\>\ \#\ extra\ BED\ file\ \=\ None +\>\ \#\ ChIP\ annotation\ \=\ On +\>\ \#\ gene\-centered\ annotation\ \=\ \ On +\>\ \#\ average\ profiling\ \=\ On +\>\ \#\ dump\ profiles\ \=\ Off +\>\ \#\ re\-annotation\ for\ genome\ background\ $ChIP\ region\ annotation$\ \=\ False +\>\ \#\ promoter\ sizes\ $ChIP\ region\ annotation$\ \=\ 1000\,2000\,3000\ bp +\>\ \#\ downstream\ sizes\ $ChIP\ region\ annotation$\ \=\ 1000\,2000\,3000\ bp +\>\ \#\ bidrectional\ promoter\ sizes\ $ChIP\ region\ annotation$\ \=\ 2500\,5000\ bp +\>\ \#\ span\ size\ $gene\-centered\ annotation$\ \=\ 3000\ bp +\>\ \#\ profiling\ resolution\ $average\ profiling$\ \=\ 50\ bp +\>\ \#\ relative\ distance\ wrt\ TSS\ and\ TTS\ $average\ profiling$\ \=\ 3000\ bp +\>\ pdf$\"ceas\.pdf\"\,height\=11\.5\,width\=8\.5$ +\>\ +\>\ \#\ .* +\>\ \#\ +\>\ \#\ ChIP\ annotation +\>\ \#\ +\>\ +\>\ +\>\ \#\ +\>\ \#\ Chromosomal\ Distribution +\>\ \#\ +\>\ +\>\ par$mar\=c\(4\,\ 4\,\ 5\,\ 3\.8$\,oma\=c$4\,\ 2\,\ 4\,\ 2$\) +\>\ r0\<\-c$100\.0$ +\>\ r1\<\-c$100\.0$ +\>\ height\<\-rbind$r0\,r1$ +\>\ names\=c$\"26\"$ +\>\ mp\<\-barplot$height\=height\,names\=names\,beside\=TRUE\,horiz\=TRUE\,col\=c\(\"\#5FA1C1\"\,\"\#EB9D86\"$\,main\=\"Chromosomal\ Distribution\ of\ ChIP\ Regions\"\,xlab\=\"Percentage\ \%\"\,ylab\=\"Chromosome\"\,border\=FALSE\,xlim\=c$0\.000000\,183\.333333$\,cex\.names\=1\) +\>\ text$x\=c\(100\.0$\,y\=mp\[1\,\]\,label\=c$\"100\.0\ \%\"$\,pos\=4\,offset\=0\.2\,cex\=0\.9\) +\>\ text$x\=c\(100\.0$\,y\=mp\[2\,\]\,label\=c$\"100\.0\ \%\ \(\<\=4\.9e\-324$\"\)\,pos\=4\,offset\=0\.2\,cex\=0\.9\) +\>\ legend$\"right\"\,legend\=c\(\"Genome\"\,\"ChIP\ \(p\-value$\"\)\,col\=c$\"\#5FA1C1\"\,\"\#EB9D86\"$\,pch\=15\,bty\=\"n\"\) +\>\ +\>\ \#\ +\>\ \#\ Promoter\,Bipromoter\,Downstream\,\ Gene\ and\ Regions\ of\ interest +\>\ \#\ +\>\ +\>\ par$mfrow\=c\(4\,\ 1$\,mar\=c$4\,\ 4\,\ 5\,\ 3\.8$\,oma\=c$4\,\ 2\,\ 4\,\ 2$\) +\>\ r0\<\-c$1\.8532425688606797\,\ 3\.616851183410451\,\ 5\.322318854623416$ +\>\ r1\<\-c$0\.0\,\ 0\.0\,\ 0\.0$ +\>\ height\<\-rbind$r0\,r1$ +\>\ names\=c$\"\<\=1000\ bp\"\,\"\<\=2000\ bp\"\,\"\<\=3000\ bp\"$ +\>\ mp\<\-barplot$height\=height\,names\=names\,beside\=TRUE\,horiz\=FALSE\,col\=c\(\"\#5FA1C1\"\,\"\#EB9D86\"$\,main\=\"Promoter\"\,ylab\=\"Percentage\ \%\"\,border\=FALSE\,ylim\=c$0\.000000\,9\.757585$\,cex\.names\=1\) +\>\ text$x\=mp\[1\,\]\,y\=c\(1\.8532425688606797\,\ 3\.616851183410451\,\ 5\.322318854623416$\,label\=c$\"1\.9\ \%\"\,\"3\.6\ \%\"\,\"5\.3\ \%\"$\,pos\=3\,offset\=0\.2\) +\>\ text$x\=mp\[2\,\]\,y\=c\(0\.0\,\ 0\.0\,\ 0\.0$\,label\=c$\"0\.000\ \% +\+\ \(0\.981$\"\,\"0\.000\ \% +\+\ $0\.964$\"\,\"0\.000\ \% +\+\ $0\.947$\"\)\,pos\=3\,offset\=0\.2\) +\>\ legend$\"topleft\"\,legend\=c\(\"Genome\"\,\"ChIP\ \(p\-value$\"\)\,col\=c$\"\#5FA1C1\"\,\"\#EB9D86\"$\,pch\=15\,bty\=\"n\"\) +\>\ r0\<\-c$0\.03876062889120376\,\ 0\.03876062889120376$ +\>\ r1\<\-c$0\.0\,\ 0\.0$ +\>\ height\<\-rbind$r0\,r1$ +\>\ names\=c$\"\<\=2500\ bp\"\,\"\<\=5000\ bp\"$ +\>\ mp\<\-barplot$height\=height\,names\=names\,beside\=TRUE\,horiz\=FALSE\,col\=c\(\"\#5FA1C1\"\,\"\#EB9D86\"$\,main\=\"Bidirectional\ Promoter\"\,ylab\=\"Percentage\ \%\"\,border\=FALSE\,ylim\=c$0\.000000\,0\.071061$\,cex\.names\=1\) +\>\ text$x\=mp\[1\,\]\,y\=c\(0\.03876062889120376\,\ 0\.03876062889120376$\,label\=c$\"0\.04\ \%\"\,\"0\.04\ \%\"$\,pos\=3\,offset\=0\.2\) +\>\ text$x\=mp\[2\,\]\,y\=c\(0\.0\,\ 0\.0$\,label\=c$\"0\.000\ \% +\+\ \(1\.000$\"\,\"0\.000\ \% +\+\ $1\.000$\"\)\,pos\=3\,offset\=0\.2\) +\>\ legend$\"topleft\"\,legend\=c\(\"Genome\"\,\"ChIP\ \(p\-value$\"\)\,col\=c$\"\#5FA1C1\"\,\"\#EB9D86\"$\,pch\=15\,bty\=\"n\"\) +\>\ r0\<\-c$1\.8290171758036773\,\ 3\.4690762857627364\,\ 4\.980740812519683$ +\>\ r1\<\-c$0\.0\,\ 0\.0\,\ 0\.0$ +\>\ height\<\-rbind$r0\,r1$ +\>\ names\=c$\"\<\=1000\ bp\"\,\"\<\=2000\ bp\"\,\"\<\=3000\ bp\"$ +\>\ mp\<\-barplot$height\=height\,names\=names\,beside\=TRUE\,horiz\=FALSE\,col\=c\(\"\#5FA1C1\"\,\"\#EB9D86\"$\,main\=\"Downstream\"\,ylab\=\"Percentage\ \%\"\,border\=FALSE\,ylim\=c$0\.000000\,9\.131358$\,cex\.names\=1\) +\>\ text$x\=mp\[1\,\]\,y\=c\(1\.8290171758036773\,\ 3\.4690762857627364\,\ 4\.980740812519683$\,label\=c$\"1\.8\ \%\"\,\"3\.5\ \%\"\,\"5\.0\ \%\"$\,pos\=3\,offset\=0\.2\) +\>\ text$x\=mp\[2\,\]\,y\=c\(0\.0\,\ 0\.0\,\ 0\.0$\,label\=c$\"0\.000\ \% +\+\ \(0\.982$\"\,\"0\.000\ \% +\+\ $0\.965$\"\,\"0\.000\ \% +\+\ $0\.950$\"\)\,pos\=3\,offset\=0\.2\) +\>\ legend$\"topleft\"\,legend\=c\(\"Genome\"\,\"ChIP\ \(p\-value$\"\)\,col\=c$\"\#5FA1C1\"\,\"\#EB9D86\"$\,pch\=15\,bty\=\"n\"\) +\>\ r0\<\-c$0\.2034933016788197\,\ 1\.3978051793890356\,\ 2\.359553283752029\,\ 19\.734005184234114\,\ 23\.694856949054$ +\>\ r1\<\-c$0\.0\,\ 0\.0\,\ 0\.0\,\ 0\.0\,\ 0\.0$ +\>\ height\<\-rbind$r0\,r1$ +\>\ names\=c$\"5\'UTR\"\,\"3\'UTR\"\,\"Coding\ Exon\"\,\"Intron\"\,\"All\"$ +\>\ mp\<\-barplot$height\=height\,names\=names\,beside\=TRUE\,horiz\=FALSE\,col\=c\(\"\#5FA1C1\"\,\"\#EB9D86\"$\,main\=\"Gene\"\,ylab\=\"Percentage\ \%\"\,border\=FALSE\,ylim\=c$0\.000000\,43\.440571$\,cex\.names\=1\) +\>\ text$x\=mp\[1\,\]\,y\=c\(0\.2034933016788197\,\ 1\.3978051793890356\,\ 2\.359553283752029\,\ 19\.734005184234114\,\ 23\.694856949054$\,label\=c$\"0\.2\ \%\"\,\"1\.4\ \%\"\,\"2\.4\ \%\"\,\"19\.7\ \%\"\,\"23\.7\ \%\"$\,pos\=3\,offset\=0\.2\) +\>\ text$x\=mp\[2\,\]\,y\=c\(0\.0\,\ 0\.0\,\ 0\.0\,\ 0\.0\,\ 0\.0$\,label\=c$\"0\.000\ \% +\+\ \(0\.998$\"\,\"0\.000\ \% +\+\ $0\.986$\"\,\"0\.000\ \% +\+\ $0\.976$\"\,\"0\.000\ \% +\+\ $0\.803$\"\,\"0\.000\ \% +\+\ $0\.763$\"\)\,pos\=3\,offset\=0\.2\) +\>\ legend$\"topleft\"\,legend\=c\(\"Genome\"\,\"ChIP\ \(p\-value$\"\)\,col\=c$\"\#5FA1C1\"\,\"\#EB9D86\"$\,pch\=15\,bty\=\"n\"\) +\>\ +\>\ \#\ +\>\ \#\ Distribution\ of\ Genome\ and\ ChIP\ regions\ over\ cis\-regulatory\ element +\>\ \#\ Note\ that\ the\ x\ may\ be\ modified\ for\ better\ graphics\ in\ case\ a\ value\ is\ too\ small +\>\ \#\ Thus\,\ look\ at\ the\ labels\ of\ the\ pie\ chart\ to\ get\ the\ real\ percentage\ values +\>\ \#\ +\>\ +\>\ par$mfcol\=c\(2\,\ 2$\,mar\=c$3\,\ 3\,\ 4\,\ 2\.8$\,oma\=c$4\,\ 2\,\ 4\,\ 2$\) +\>\ x\<\-c$0\.018532\,0\.017055\,0\.016037\,0\.017830\,0\.015092\,0\.014051\,0\.010000\,0\.013833\,0\.023014\,0\.192592\,0\.670292$ +\>\ pie$x\=x\,labels\=c\(\"1\.9\ \%\"\,\"1\.7\ \%\"\,\"1\.6\ \%\"\,\"1\.8\ \%\"\,\"1\.5\ \%\"\,\"1\.4\ \%\"\,\"0\.2\ \%\"\,\"1\.4\ \%\"\,\"2\.3\ \%\"\,\"19\.3\ \%\"\,\"67\.0\ \%\"$\,main\=\"Genome\"\,col\=c$\"\#445FA2\"\,\"\#EB9D86\"\,\"\#799F7A\"\,\"\#6C527F\"\,\"\#5FA1C1\"\,\"\#E8BB77\"\,\"\#A8C5EF\"\,\"\#FDCDB9\"\,\"\#C6E6B5\"\,\"\#F1D5EE\"\,\"\#B4E1F6\"$\,clockwise\=TRUE\,border\=FALSE\,radius\=0\.9\,cex\=0\.8\,init\.angle\=90\,density\=100\) +\>\ x\<\-c$0\.000000\,1\.000000$ +\>\ y\<\-c$0\.000000\,1\.000000$ +\>\ plot$x\,\ y\,type\=\"n\"\,main\=\"\"\,xlab\=\"\"\,ylab\=\"\"\,frame\=FALSE\,axes\=FALSE\,xaxt\=\"s\"\,yaxt\=\"s\"$ +\>\ legend$\"top\"\,legend\=c\(\"Promoter\ \(\<\=1000\ bp$\:\ 1\.9\ \%\"\,\"Promoter\ $1000\-2000\ bp$\:\ 1\.7\ \%\"\,\"Promoter\ $2000\-3000\ bp$\:\ 1\.6\ \%\"\,\"Downstream\ $\<\=1000\ bp$\:\ 1\.8\ \%\"\,\"Downstream\ $1000\-2000\ bp$\:\ 1\.5\ \%\"\,\"Downstream\ $2000\-3000\ bp$\:\ 1\.4\ \%\"\,\"5\'UTR\:\ 0\.2\ \%\"\,\"3\'UTR\:\ 1\.4\ \%\"\,\"Coding\ exon\:\ 2\.3\ \%\"\,\"Intron\:\ 19\.3\ \%\"\,\"Distal\ intergenic\:\ 67\.0\ \%\"\)\,col\=c$\"\#445FA2\"\,\"\#EB9D86\"\,\"\#799F7A\"\,\"\#6C527F\"\,\"\#5FA1C1\"\,\"\#E8BB77\"\,\"\#A8C5EF\"\,\"\#FDCDB9\"\,\"\#C6E6B5\"\,\"\#F1D5EE\"\,\"\#B4E1F6\"$\,pch\=15\,bty\=\"n\"\) +\>\ x\<\-c$0\.010000\,0\.010000\,0\.010000\,0\.010000\,0\.010000\,0\.010000\,0\.010000\,0\.010000\,0\.010000\,0\.010000\,1\.000000$ +\>\ pie$x\=x\,labels\=c\(\"0\.000\ \%\"\,\"0\.000\ \%\"\,\"0\.000\ \%\"\,\"0\.000\ \%\"\,\"0\.000\ \%\"\,\"0\.000\ \%\"\,\"0\.000\ \%\"\,\"0\.000\ \%\"\,\"0\.000\ \%\"\,\"0\.000\ \%\"\,\"100\.0\ \%\"$\,main\=\"ChIP\"\,col\=c$\"\#445FA2\"\,\"\#EB9D86\"\,\"\#799F7A\"\,\"\#6C527F\"\,\"\#5FA1C1\"\,\"\#E8BB77\"\,\"\#A8C5EF\"\,\"\#FDCDB9\"\,\"\#C6E6B5\"\,\"\#F1D5EE\"\,\"\#B4E1F6\"$\,clockwise\=TRUE\,border\=FALSE\,radius\=0\.9\,cex\=0\.8\,init\.angle\=90\,density\=100\) +\>\ x\<\-c$0\.000000\,1\.000000$ +\>\ y\<\-c$0\.000000\,1\.000000$ +\>\ plot$x\,\ y\,type\=\"n\"\,main\=\"\"\,xlab\=\"\"\,ylab\=\"\"\,frame\=FALSE\,axes\=FALSE\,xaxt\=\"s\"\,yaxt\=\"s\"$ +\>\ legend$\"top\"\,legend\=c\(\"Promoter\ \(\<\=1000\ bp$\:\ 0\.000\ \%\"\,\"Promoter\ $1000\-2000\ bp$\:\ 0\.000\ \%\"\,\"Promoter\ $2000\-3000\ bp$\:\ 0\.000\ \%\"\,\"Downstream\ $\<\=1000\ bp$\:\ 0\.000\ \%\"\,\"Downstream\ $1000\-2000\ bp$\:\ 0\.000\ \%\"\,\"Downstream\ $2000\-3000\ bp$\:\ 0\.000\ \%\"\,\"5\'UTR\:\ 0\.000\ \%\"\,\"3\'UTR\:\ 0\.000\ \%\"\,\"Coding\ exon\:\ 0\.000\ \%\"\,\"Intron\:\ 0\.000\ \%\"\,\"Distal\ intergenic\:\ 100\.0\ \%\"\)\,col\=c$\"\#445FA2\"\,\"\#EB9D86\"\,\"\#799F7A\"\,\"\#6C527F\"\,\"\#5FA1C1\"\,\"\#E8BB77\"\,\"\#A8C5EF\"\,\"\#FDCDB9\"\,\"\#C6E6B5\"\,\"\#F1D5EE\"\,\"\#B4E1F6\"$\,pch\=15\,bty\=\"n\"\) +\>\ +\>\ \#\ +\>\ \#\ ChIP\ regions\ over\ the\ genome +\>\ \#\ +\>\ +\>\ par$mar\=c\(4\,\ 4\,\ 5\,\ 3\.8$\,oma\=c$4\,\ 2\,\ 4\,\ 2$\) +\>\ layout$matrix\(c\(1\,\ 0\,\ 2\,\ 2$\,\ 2\,\ 2\,\ byrow\ \=\ TRUE\)\,widths\=c$1\,\ 1$\,heights\=c$1\,\ 5$\) +\>\ x\<\-c$0\.000000\,0\.000000$ +\>\ y\<\-c$0\.000000\,1\.000000$ +\>\ plot$x\,\ y\,type\=\"n\"\,main\=\"Distribution\ of\ Peak\ Heights\"\,xlab\=\"\"\,ylab\=\"\"\,xlim\=c\(0\.000000\,0\.000000$\,ylim\=c$0\.000000\,1\.000000$\,frame\=FALSE\,xaxt\=\"s\"\,yaxt\=\"n\"\,cex\=0\.9\) +\>\ x\<\-c$0\.000000\,0\.000000\,0\.000000\,0\.000000$ +\>\ y\<\-c$0\.000000\,0\.000000\,1\.000000\,1\.000000$ +\>\ polygon$x\,y\,col\=c\(\"black\"$\) +\>\ x\ \<\-\ c$0\.000000$ +\>\ y\<\-c$0\.800000$ +\>\ lines$x\,\ y\,xlim\=c\(0\,\ 0\.0$\,ylim\=c$0\,\ 1$\,type\=\"l\"\,col\=c$\"cyan\"$\,lwd\=2\) +\>\ x\<\-c$0\.000000\,4127518\.000000$ +\>\ y\<\-c$0\.855556\,1\.144444$ +\>\ plot$x\,\ y\,type\=\"n\"\,main\=\"ChIP\ Regions\ \(Peaks$\ over\ Chromosomes\"\,xlab\=\"Chromosome\ Size\ $bp$\"\,ylab\=\"Chromosome\"\,xlim\=c$0\.000000\,4127518\.000000$\,ylim\=c$0\.855556\,1\.144444$\,frame\=FALSE\,xaxt\=\"s\"\,yaxt\=\"n\"\) +\>\ start\ \<\-\ c$4119129$ +\>\ end\ \<\-\ c$4119130$ +\>\ vals\ \<\-\ c$0\.0$ +\>\ vals\[vals\ \>\ 0\.0\]\ \<\-\ 0\.0 +\>\ vals\[vals\ \<\ 0\]\ \<\-\ 0 +\>\ heights\ \<\-\ 0\.288889\ \*\ $\(vals\ \-\ 0$\/$0\.0\ \-\ 0$\)\ \+\ 0\.855555555556 +\>\ for\ $i\ in\ 1\:length\(heights$\)\ \{ +\+\ \ polygon$x\=c\(start\[i\]\,\ end\[i\]\,\ end\[i\]\,\ start\[i\]$\,\ y\=c$0\.855555555556\,\ 0\.855555555556\,\ heights\[i\]\,\ heights\[i\]$\,\ col\=c$\"\#CC0000\"$\,\ border\=c$\"\#CC0000\"$\) +\+\ \} +\>\ mtext$\"26\"\,side\=2\,line\=0\,outer\=FALSE\,at\=1\.0$ +\>\ par$mar\=c\(4\,\ 4\,\ 5\,\ 3\.8$\,oma\=c$4\,\ 2\,\ 4\,\ 2$\) +\>\ layout$matrix\(c\(1\,\ 2\,\ 3\,\ 3\,\ 4\,\ 5$\,\ 3\,\ 2\,\ byrow\ \=\ TRUE\)\,widths\=c$1\,\ 1$\,heights\=c$1\,\ 1\,\ 1$\) +\>\ x\<\-c\(\-3000\.000000\,\-2950\.000000\,\-2900\.000000\,\-2850\.000000\,\-2800\.000000\,\-2750\.000000\,\-2700\.000000\,\-2650\.000000\,\-2600\.000000\,\-2550\.000000\,\-2500\.000000\,\-2450\.000000\,\-2400\.000000\,\-2350\.000000\,\-2300\.000000\,\-2250\.000000\,\-2200\.000000\,\-2150\.000000\,\-2100\.000000\,\-2050\.000000\,\-2000\.000000\,\-1950\.000000\,\-1900\.000000\,\-1850\.000000\,\-1800\.000000\,\-1750\.000000\,\-1700\.000000\,\-1650\.000000\,\-1600\.000000\,\-1550\.000000\,\-1500\.000000\,\-1450\.000000\,\-1400\.000000\,\-1350\.000000\,\-1300\.000000\,\-1250\.000000\,\-1200\.000000\,\-1150\.000000\,\-1100\.000000\,\-1050\.000000\,\-1000\.000000\,\-950\.000000\,\-900\.000000\,\-850\.000000\,\-800\.000000\,\-750\.000000\,\-700\.000000\,\-650\.000000\,\-600\.000000\,\-550\.000000\,\-500\.000000\,\-450\.000000\,\-400\.000000\,\-350\.000000\,\-300\.000000\,\-250\.000000\,\-200\.000000\,\-150\.000000\,\-100\.000000\,\-50\.000000\,0\.000000\,50\.000000\,100\.000000\,150\.000000\,200\.000000\,250\.000000\,300\.000000\,350\.000000\,400\.000000\,450\.000000\,500\.000000\,550\.000000\,600\.000000\,650\.000000\,700\.000000\,750\.000000\,800\.000000\,850\.000000\,900\.000000\,950\.000000\,1000\.000000\,1050\.000000\,1100\.000000\,1150\.000000\,1200\.000000\,1250\.000000\,1300\.000000\,1350\.000000\,1400\.000000\,1450\.000000\,1500\.000000\,1550\.000000\,1600\.000000\,1650\.000000\,1700\.000000\,1750\.000000\,1800\.000000\,1850\.000000\,1900\.000000\,1950\.000000\,2000\.000000\,2050\.000000\,2100\.000000\,2150\.000000\,2200\.000000\,2250\.000000\,2300\.000000\,2350\.000000\,2400\.000000\,2450\.000000\,2500\.000000\,2550\.000000\,2600\.000000\,2650\.000000\,2700\.000000\,2750\.000000\,2800\.000000\,2850\.000000\,2900\.000000\,2950\.000000\,3000\.000000\) 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y\<\-c\(0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,20000\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\) +\>\ plot$x\,\ y\,type\=\"l\"\,main\=\"Average\ Profile\ near\ TSS\"\,xlab\=\"Relative\ Distance\ to\ TSS\ \(bp$\"\,ylab\=\"Average\ Profile\"\,col\=c$\"\#C8524D\"$\,xaxt\=\"s\"\,yaxt\=\"s\"\,lwd\=2\) +\>\ abline$v\=0\.000000\,lty\=2\,col\=c\(\"black\"$\) +\>\ x\<\-c\(\-3000\.000000\,\-2950\.000000\,\-2900\.000000\,\-2850\.000000\,\-2800\.000000\,\-2750\.000000\,\-2700\.000000\,\-2650\.000000\,\-2600\.000000\,\-2550\.000000\,\-2500\.000000\,\-2450\.000000\,\-2400\.000000\,\-2350\.000000\,\-2300\.000000\,\-2250\.000000\,\-2200\.000000\,\-2150\.000000\,\-2100\.000000\,\-2050\.000000\,\-2000\.000000\,\-1950\.000000\,\-1900\.000000\,\-1850\.000000\,\-1800\.000000\,\-1750\.000000\,\-1700\.000000\,\-1650\.000000\,\-1600\.000000\,\-1550\.000000\,\-1500\.000000\,\-1450\.000000\,\-1400\.000000\,\-1350\.000000\,\-1300\.000000\,\-1250\.000000\,\-1200\.000000\,\-1150\.000000\,\-1100\.000000\,\-1050\.000000\,\-1000\.000000\,\-950\.000000\,\-900\.000000\,\-850\.000000\,\-800\.000000\,\-750\.000000\,\-700\.000000\,\-650\.000000\,\-600\.000000\,\-550\.000000\,\-500\.000000\,\-450\.000000\,\-400\.000000\,\-350\.000000\,\-300\.000000\,\-250\.000000\,\-200\.000000\,\-150\.000000\,\-100\.000000\,\-50\.000000\,0\.000000\,50\.000000\,100\.000000\,150\.000000\,200\.000000\,250\.000000\,300\.000000\,350\.000000\,400\.000000\,450\.000000\,500\.000000\,550\.000000\,600\.000000\,650\.000000\,700\.000000\,750\.000000\,800\.000000\,850\.000000\,900\.000000\,950\.000000\,1000\.000000\,1050\.000000\,1100\.000000\,1150\.000000\,1200\.000000\,1250\.000000\,1300\.000000\,1350\.000000\,1400\.000000\,1450\.000000\,1500\.000000\,1550\.000000\,1600\.000000\,1650\.000000\,1700\.000000\,1750\.000000\,1800\.000000\,1850\.000000\,1900\.000000\,1950\.000000\,2000\.000000\,2050\.000000\,2100\.000000\,2150\.000000\,2200\.000000\,2250\.000000\,2300\.000000\,2350\.000000\,2400\.000000\,2450\.000000\,2500\.000000\,2550\.000000\,2600\.000000\,2650\.000000\,2700\.000000\,2750\.000000\,2800\.000000\,2850\.000000\,2900\.000000\,2950\.000000\,3000\.000000\) 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y\<\-c\(0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,20000\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,20000\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,20000\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,20000\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,20000\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,20000\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,20000\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,20000\.000000\,0\.000000\,0\.000000\) +\>\ plot$x\,\ y\,type\=\"l\"\,main\=\"Average\ Profile\ near\ TTS\"\,xlab\=\"Relative\ Distance\ to\ TTS\ \(bp$\"\,ylab\=\"Average\ Profile\"\,col\=c$\"\#C8524D\"$\,xaxt\=\"s\"\,yaxt\=\"s\"\,lwd\=2\) +\>\ abline$v\=0\.000000\,lty\=2\,col\=c\(\"black\"$\) +\>\ x\<\-c\(\-1000\.000000\,\-950\.000000\,\-900\.000000\,\-850\.000000\,\-800\.000000\,\-750\.000000\,\-700\.000000\,\-650\.000000\,\-600\.000000\,\-550\.000000\,\-500\.000000\,\-450\.000000\,\-400\.000000\,\-350\.000000\,\-300\.000000\,\-250\.000000\,\-200\.000000\,\-150\.000000\,\-100\.000000\,\-50\.000000\,0\.000000\,50\.000000\,100\.000000\,150\.000000\,200\.000000\,250\.000000\,300\.000000\,350\.000000\,400\.000000\,450\.000000\,500\.000000\,550\.000000\,600\.000000\,650\.000000\,700\.000000\,750\.000000\,800\.000000\,850\.000000\,900\.000000\,950\.000000\,1000\.000000\,1050\.000000\,1100\.000000\,1150\.000000\,1200\.000000\,1250\.000000\,1300\.000000\,1350\.000000\,1400\.000000\,1450\.000000\,1500\.000000\,1550\.000000\,1600\.000000\,1650\.000000\,1700\.000000\,1750\.000000\,1800\.000000\,1850\.000000\,1900\.000000\,1950\.000000\,2000\.000000\,2050\.000000\,2100\.000000\,2150\.000000\,2200\.000000\,2250\.000000\,2300\.000000\,2350\.000000\,2400\.000000\,2450\.000000\,2500\.000000\,2550\.000000\,2600\.000000\,2650\.000000\,2700\.000000\,2750\.000000\,2800\.000000\,2850\.000000\,2900\.000000\,2950\.000000\,3000\.000000\,3050\.000000\,3100\.000000\,3150\.000000\,3200\.000000\,3250\.000000\,3300\.000000\,3350\.000000\,3400\.000000\,3450\.000000\,3500\.000000\,3550\.000000\,3600\.000000\,3650\.000000\,3700\.000000\,3750\.000000\,3800\.000000\,3850\.000000\,3900\.000000\,3950\.000000\,4000\.000000\) 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y\<\-c\(0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,20000\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,20000\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,20000\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\) +\>\ plot$x\,\ y\,type\=\"l\"\,main\=\"Average\ Gene\ Profile\"\,xlab\=\"Upstream\ \(bp$\,\ 3000\ bp\ of\ Meta\-gene\,\ Downstream\ $bp$\"\,ylab\=\"Average\ Profile\"\,col\=c$\"\#C8524D\"$\,xaxt\=\"s\"\,yaxt\=\"s\"\,lwd\=2\) +\>\ abline$v\=0\.000000\,lty\=2\,col\=c\(\"black\"$\) +\>\ abline$v\=3000\.000000\,lty\=2\,col\=c\(\"black\"$\) +\>\ x\<\-c$0\.000000\,3\.333333\,6\.666667\,10\.000000\,13\.333333\,16\.666667\,20\.000000\,23\.333333\,26\.666667\,30\.000000\,33\.333333\,36\.666667\,40\.000000\,43\.333333\,46\.666667\,50\.000000\,53\.333333\,56\.666667\,60\.000000\,63\.333333\,66\.666667\,70\.000000\,73\.333333\,76\.666667\,80\.000000\,83\.333333\,86\.666667\,90\.000000\,93\.333333\,96\.666667\,100\.000000$ +\>\ y\<\-c$0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,20000\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000$ +\>\ plot$x\,\ y\,type\=\"l\"\,main\=\"Average\ Concatenated\ Exon\ Profile\"\,xlab\=\"Relative\ Location\ \(\%$\"\,ylab\=\"Average\ Profile\"\,col\=c$\"\#C8524D\"$\,ylim\=c$0\.000000\,20000\.000000$\,xaxt\=\"s\"\,yaxt\=\"s\"\,lwd\=2\) +\>\ x\<\-c$0\.000000\,3\.333333\,6\.666667\,10\.000000\,13\.333333\,16\.666667\,20\.000000\,23\.333333\,26\.666667\,30\.000000\,33\.333333\,36\.666667\,40\.000000\,43\.333333\,46\.666667\,50\.000000\,53\.333333\,56\.666667\,60\.000000\,63\.333333\,66\.666667\,70\.000000\,73\.333333\,76\.666667\,80\.000000\,83\.333333\,86\.666667\,90\.000000\,93\.333333\,96\.666667\,100\.000000$ +\>\ y\<\-c$0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000$ +\>\ plot$x\,\ y\,type\=\"l\"\,main\=\"Average\ Concatenated\ Intron\ Profile\"\,xlab\=\"Relative\ Location\ \(\%$\"\,ylab\=\"Average\ Profile\"\,col\=c$\"\#C8524D\"$\,ylim\=c$0\.000000\,20000\.000000$\,xaxt\=\"s\"\,yaxt\=\"s\"\,lwd\=2\) +\>\ par$mfrow\=c\(3\,\ 2$\,mar\=c$4\,\ 4\,\ 5\,\ 3\.8$\,oma\=c$4\,\ 2\,\ 4\,\ 2$\) +\>\ x\<\-c$\-3\.000000\,3\.000000$ +\>\ y\<\-c$0\.000000\,1\.000000$ +\>\ plot$x\,\ y\,type\=\"n\"\,main\=\"\"\,xlab\=\"\"\,ylab\=\"\"\,xlim\=c\(\-3\.000000\,3\.000000$\,ylim\=c$0\.000000\,1\.000000$\,axes\=FALSE\,xaxt\=\"s\"\,yaxt\=\"s\"\) +\>\ x\<\-c$\-3\.000000\,3\.000000$ +\>\ y\<\-c$0\.000000\,1\.000000$ +\>\ plot$x\,\ y\,type\=\"n\"\,main\=\"\"\,xlab\=\"\"\,ylab\=\"\"\,xlim\=c\(\-3\.000000\,3\.000000$\,ylim\=c$0\.000000\,1\.000000$\,axes\=FALSE\,xaxt\=\"s\"\,yaxt\=\"s\"\) +\>\ x\<\-c$\-3\.000000\,3\.000000$ +\>\ y\<\-c$0\.000000\,1\.000000$ +\>\ plot$x\,\ y\,type\=\"n\"\,main\=\"\"\,xlab\=\"\"\,ylab\=\"\"\,xlim\=c\(\-3\.000000\,3\.000000$\,ylim\=c$0\.000000\,1\.000000$\,axes\=FALSE\,xaxt\=\"s\"\,yaxt\=\"s\"\) +\>\ x\<\-c$\-3\.000000\,3\.000000$ +\>\ y\<\-c$0\.000000\,1\.000000$ +\>\ plot$x\,\ y\,type\=\"n\"\,main\=\"\"\,xlab\=\"\"\,ylab\=\"\"\,xlim\=c\(\-3\.000000\,3\.000000$\,ylim\=c$0\.000000\,1\.000000$\,axes\=FALSE\,xaxt\=\"s\"\,yaxt\=\"s\"\) +\>\ x\<\-c$\-3\.000000\,3\.000000$ +\>\ y\<\-c$0\.000000\,1\.000000$ +\>\ plot$x\,\ y\,type\=\"n\"\,main\=\"\"\,xlab\=\"\"\,ylab\=\"\"\,xlim\=c\(\-3\.000000\,3\.000000$\,ylim\=c$0\.000000\,1\.000000$\,axes\=FALSE\,xaxt\=\"s\"\,yaxt\=\"s\"\) +\>\ x\<\-c$0\.000000\,4\.761905\,9\.523810\,14\.285714\,19\.047619\,23\.809524\,28\.571429\,33\.333333\,38\.095238\,42\.857143\,47\.619048\,52\.380952\,57\.142857\,61\.904762\,66\.666667\,71\.428571\,76\.190476\,80\.952381\,85\.714286\,90\.476190\,95\.238095\,100\.000000$ +\>\ y\<\-c$0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,0\.000000\,20000\.000000\,0\.000000$ +\>\ plot$x\,\ y\,type\=\"l\"\,main\=\"Average\ Intron\ Profile +\+\ \(685\ \<\=\ length\ \<\ 2653\ bp$\"\,xlab\=\"Relative\ Location\ $\%$\"\,ylab\=\"Average\ Profile\"\,col\=c$\"\#C8524D\"$\,ylim\=c$0\.000000\,24000\.000000$\,xaxt\=\"s\"\,yaxt\=\"s\"\,lwd\=2\) +\>\ dev\.off +null\ device\ +\ \ \ \ \ \ \ \ \ \ 1\ +\>\ +INFO\ \ \@\ .*\ \#\.\.\.\ cong\!\ See\ ceas\.pdf\ for\ the\ graphical\ results\ of\ CEAS\!\ diff -r 000000000000 -r f411ce97a351 test-data/ceas_out3.pdf Binary file test-data/ceas_out3.pdf has changed diff -r 000000000000 -r f411ce97a351 test-data/ceas_out3.xls --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/ceas_out3.xls Tue Jun 30 07:08:05 2015 -0400 @@ -0,0 +1,133 @@ +# RefSeq: RefSeq ID +# chr: chromosome of a RefSeq gene +# txStart: 5' end of a RefSeq gene +# txEnd: 3' end site of a RefSeq gene +# strand: strand of a RefSeq gene +# dist u TSS: Distance to the nearest ChIP region's center upstream of transcription start site (bp) +# dist d TSS: Distance to the nearest ChIP region's center downstream of transcription start site (bp) +# dist u TTS: Distance to the nearest ChIP region's center upstream of transcription end site (bp) +# dist d TTS: Distance to the nearest ChIP region's center downstream of transcription end (bp) +# 3000bp u TSS: Occupancy rate of ChIP region in 3000bp upstream of transcription start site (0.0 - 1.0) +# 3000bp d TSS: Occupancy rate of ChIP region in 3000bp downstream of transcription start site (0.0 - 1.0) +# 1/3 gene: Occupancy rate of ChIP region in 1/3 gene (0.0 - 1.0) +# 2/3 gene: Occupancy rate of ChIP region in 2/3 gene (0.0 - 1.0) +# 3/3 gene: Occupancy rate of ChIP region in 3/3 gene (0.0 - 1.0) +# 3000bp d TTS: Occupancy rate of ChIP region in 3000bp downstream of transcriptino end (0.0 - 1.0) +# exons: Occupancy rate of ChIP regions in exons (0.0-1.0) +# Note that txStart and txEnd indicate 5' and 3' ends of genes whereas TSS and TTS transcription start and end sites in consideration of strand. +#name chr txStart txEnd strand dist u TSS dist d TSS dist u TTS dist d TTS 3000bp u TSS 3000bp d TSS 1/3 gene 2/3 gene 3/3 gene 3000bp d TTS exons +NM_001031576 chr26 19281 27136 + NA 4099848 NA 4091993 0 0 0 0 0 0 0 +NM_204615 chr26 57466 61594 - 4057535 NA 4061663 NA 0 0 0 0 0 0 0 +NM_001005431 chr26 65800 76175 - 4042954 NA 4053329 NA 0 0 0 0 0 0 0 +NM_001145491 chr26 91618 92166 - 4026963 NA 4027511 NA 0 0 0 0 0 0 0 +NM_204398 chr26 93069 97423 + NA 4026060 NA 4021706 0 0 0 0 0 0 0 +NM_001305147 chr26 254661 282571 + NA 3864468 NA 3836558 0 0 0 0 0 0 0 +NM_001305148 chr26 254661 282571 + NA 3864468 NA 3836558 0 0 0 0 0 0 0 +NM_001012868 chr26 350397 355252 - 3763877 NA 3768732 NA 0 0 0 0 0 0 0 +NM_001031030 chr26 479573 493561 + NA 3639556 NA 3625568 0 0 0 0 0 0 0 +NM_001305140 chr26 520705 526012 + NA 3598424 NA 3593117 0 0 0 0 0 0 0 +NM_001031029 chr26 537101 565572 + NA 3582028 NA 3553557 0 0 0 0 0 0 0 +NM_205248 chr26 537250 760479 + NA 3581879 NA 3358650 0 0 0 0 0 0 0 +NM_204727 chr26 662969 683066 - 3436063 NA 3456160 NA 0 0 0 0 0 0 0 +NR_105475 chr26 669012 669122 - 3450007 NA 3450117 NA 0 0 0 0 0 0 0 +NM_205449 chr26 785617 794076 + NA 3333512 NA 3325053 0 0 0 0 0 0 0 +NM_204681 chr26 897458 902049 - 3217080 NA 3221671 NA 0 0 0 0 0 0 0 +NM_001278156 chr26 905313 917094 - 3202035 NA 3213816 NA 0 0 0 0 0 0 0 +NM_204184 chr26 960209 964268 - 3154861 NA 3158920 NA 0 0 0 0 0 0 0 +NM_204316 chr26 974223 991244 + NA 3144906 NA 3127885 0 0 0 0 0 0 0 +NM_001031028 chr26 993815 1003847 - 3115282 NA 3125314 NA 0 0 0 0 0 0 0 +NM_001006392 chr26 1024606 1047756 - 3071373 NA 3094523 NA 0 0 0 0 0 0 0 +NM_001039596 chr26 1073550 1080033 - 3039096 NA 3045579 NA 0 0 0 0 0 0 0 +NM_001031027 chr26 1090460 1096137 + NA 3028669 NA 3022992 0 0 0 0 0 0 0 +NM_001031026 chr26 1096566 1104751 - 3014378 NA 3022563 NA 0 0 0 0 0 0 0 +NM_001030913 chr26 1122296 1132596 + NA 2996833 NA 2986533 0 0 0 0 0 0 0 +NM_001171886 chr26 1220031 1222791 - 2896338 NA 2899098 NA 0 0 0 0 0 0 0 +NM_205054 chr26 1229703 1232833 + NA 2889426 NA 2886296 0 0 0 0 0 0 0 +NM_204462 chr26 1234686 1236536 - 2882593 NA 2884443 NA 0 0 0 0 0 0 0 +NM_204463 chr26 1265724 1267989 - 2851140 NA 2853405 NA 0 0 0 0 0 0 0 +NM_001030378 chr26 1289091 1290386 - 2828743 NA 2830038 NA 0 0 0 0 0 0 0 +NM_001195554 chr26 1382510 1388447 + NA 2736619 NA 2730682 0 0 0 0 0 0 0 +NM_001012548 chr26 1406905 1428443 + NA 2712224 NA 2690686 0 0 0 0 0 0 0 +NR_031486 chr26 1442696 1442779 - 2676350 NA 2676433 NA 0 0 0 0 0 0 0 +NR_031487 chr26 1442896 1442979 - 2676150 NA 2676233 NA 0 0 0 0 0 0 0 +NM_205250 chr26 1472137 1474003 + NA 2646992 NA 2645126 0 0 0 0 0 0 0 +NR_105486 chr26 1566398 1566508 - 2552621 NA 2552731 NA 0 0 0 0 0 0 0 +NM_001160320 chr26 1697226 1773801 + NA 2421903 NA 2345328 0 0 0 0 0 0 0 +NM_001004709 chr26 1697226 1773801 + NA 2421903 NA 2345328 0 0 0 0 0 0 0 +NM_001160324 chr26 1697226 1773801 + NA 2421903 NA 2345328 0 0 0 0 0 0 0 +NM_001004493 chr26 1697226 1773801 + NA 2421903 NA 2345328 0 0 0 0 0 0 0 +NM_001160323 chr26 1697226 1773801 + NA 2421903 NA 2345328 0 0 0 0 0 0 0 +NM_001160322 chr26 1697226 1773801 + NA 2421903 NA 2345328 0 0 0 0 0 0 0 +NM_001160321 chr26 1697226 1773801 + NA 2421903 NA 2345328 0 0 0 0 0 0 0 +NM_001004395 chr26 1776431 1800083 + NA 2342698 NA 2319046 0 0 0 0 0 0 0 +NM_001030914 chr26 1811042 1820368 - 2298761 NA 2308087 NA 0 0 0 0 0 0 0 +NM_204506 chr26 1823407 1843085 - 2276044 NA 2295722 NA 0 0 0 0 0 0 0 +NR_031488 chr26 1925941 1926037 - 2193092 NA 2193188 NA 0 0 0 0 0 0 0 +NM_213581 chr26 2070404 2084478 - 2034651 NA 2048725 NA 0 0 0 0 0 0 0 +NR_035298 chr26 2086590 2086691 - 2032438 NA 2032539 NA 0 0 0 0 0 0 0 +NR_105470 chr26 2094750 2094860 - 2024269 NA 2024379 NA 0 0 0 0 0 0 0 +NM_001030915 chr26 2117140 2128322 - 1990807 NA 2001989 NA 0 0 0 0 0 0 0 +NM_001031498 chr26 2175178 2177159 - 1941970 NA 1943951 NA 0 0 0 0 0 0 0 +NM_001008452 chr26 2305308 2315138 + NA 1813821 NA 1803991 0 0 0 0 0 0 0 +NM_001006322 chr26 2315293 2325130 - 1793999 NA 1803836 NA 0 0 0 0 0 0 0 +NM_001004414 chr26 2373245 2375480 - 1743649 NA 1745884 NA 0 0 0 0 0 0 0 +NM_001044644 chr26 2390696 2401255 - 1717874 NA 1728433 NA 0 0 0 0 0 0 0 +NM_001031499 chr26 2425841 2429413 - 1689716 NA 1693288 NA 0 0 0 0 0 0 0 +NM_001033642 chr26 2445710 2453125 + NA 1673419 NA 1666004 0 0 0 0 0 0 0 +NM_001033643 chr26 2469318 2475028 + NA 1649811 NA 1644101 0 0 0 0 0 0 0 +NM_204664 chr26 2498398 2509349 + NA 1620731 NA 1609780 0 0 0 0 0 0 0 +NR_031489 chr26 2511657 2511746 - 1607383 NA 1607472 NA 0 0 0 0 0 0 0 +NR_031490 chr26 2512568 2512648 - 1606481 NA 1606561 NA 0 0 0 0 0 0 0 +NR_105523 chr26 2669792 2669902 - 1449227 NA 1449337 NA 0 0 0 0 0 0 0 +NR_031491 chr26 2896046 2896142 + NA 1223083 NA 1222987 0 0 0 0 0 0 0 +NM_001190924 chr26 2961382 2962268 + NA 1157747 NA 1156861 0 0 0 0 0 0 0 +NM_001007881 chr26 2999189 3002725 + NA 1119940 NA 1116404 0 0 0 0 0 0 0 +NM_204320 chr26 3006741 3011817 - 1107312 NA 1112388 NA 0 0 0 0 0 0 0 +NM_001030916 chr26 3035271 3039335 - 1079794 NA 1083858 NA 0 0 0 0 0 0 0 +NM_204151 chr26 3047964 3050306 - 1068823 NA 1071165 NA 0 0 0 0 0 0 0 +NM_204326 chr26 3124816 3214381 - 904748 NA 994313 NA 0 0 0 0 0 0 0 +NM_204336 chr26 3320769 3332327 + NA 798360 NA 786802 0 0 0 0 0 0 0 +NM_204622 chr26 3339753 3358863 - 760266 NA 779376 NA 0 0 0 0 0 0 0 +NM_205515 chr26 3359016 3368964 + NA 760113 NA 750165 0 0 0 0 0 0 0 +NM_001012843 chr26 3370712 3377196 + NA 748417 NA 741933 0 0 0 0 0 0 0 +NM_001029849 chr26 3377655 3382628 - 736501 NA 741474 NA 0 0 0 0 0 0 0 +NM_001006323 chr26 3439841 3454783 - 664346 NA 679288 NA 0 0 0 0 0 0 0 +NR_035162 chr26 3455233 3455324 + NA 663896 NA 663805 0 0 0 0 0 0 0 +NM_001012697 chr26 3516478 3545774 + NA 602651 NA 573355 0 0 0 0 0 0 0 +NM_001030917 chr26 3590932 3597509 - 521620 NA 528197 NA 0 0 0 0 0 0 0 +NM_001031500 chr26 3597231 3600802 + NA 521898 NA 518327 0 0 0 0 0 0 0 +NM_001040018 chr26 3629575 3631171 + NA 489554 NA 487958 0 0 0 0 0 0 0 +NM_001257295 chr26 3698350 3701362 - 417767 NA 420779 NA 0 0 0 0 0 0 0 +NM_001257296 chr26 3701377 3715857 - 403272 NA 417752 NA 0 0 0 0 0 0 0 +NM_001012549 chr26 3735643 3742472 - 376657 NA 383486 NA 0 0 0 0 0 0 0 +NM_001030918 chr26 3742618 3760175 - 358954 NA 376511 NA 0 0 0 0 0 0 0 +NM_001006324 chr26 3760758 3765368 - 353761 NA 358371 NA 0 0 0 0 0 0 0 +NM_205063 chr26 3809805 3812700 + NA 309324 NA 306429 0 0 0 0 0 0 0 +NM_001293109 chr26 3859074 3879130 - 239999 NA 260055 NA 0 0 0 0 0 0 0 +NM_001293108 chr26 3859074 3882051 - 237078 NA 260055 NA 0 0 0 0 0 0 0 +NR_102328 chr26 3916006 3918143 - 200986 NA 203123 NA 0 0 0 0 0 0 0 +NM_204728 chr26 3920817 3937442 - 181687 NA 198312 NA 0 0 0 0 0 0 0 +NM_001244905 chr26 4104910 4108376 + NA 14219 NA 10753 0 0 0 0 0 0 0 +NM_001293166 chr26 4138324 4142325 - NA 23196 NA 19195 0 0 0 0 0 0 0 +NM_001030919 chr26 4144091 4175943 + 24962 NA 56814 NA 0 0 0 0 0 0 0 +NM_001257297 chr26 4209891 4216177 + 90762 NA 97048 NA 0 0 0 0 0 0 0 +NM_001257298 chr26 4218028 4238067 + 98899 NA 118938 NA 0 0 0 0 0 0 0 +NM_205490 chr26 4375371 4380959 - NA 261830 NA 256242 0 0 0 0 0 0 0 +NM_001305129 chr26 4391940 4397490 + 272811 NA 278361 NA 0 0 0 0 0 0 0 +NM_001271612 chr26 4433568 4438784 + 314439 NA 319655 NA 0 0 0 0 0 0 0 +NM_001030920 chr26 4498991 4730550 + 379862 NA 611421 NA 0 0 0 0 0 0 0 +NM_001030921 chr26 4541748 4544997 - NA 425868 NA 422619 0 0 0 0 0 0 0 +NM_001006325 chr26 4548211 4559974 + 429082 NA 440845 NA 0 0 0 0 0 0 0 +NM_001037832 chr26 4571684 4576072 - NA 456943 NA 452555 0 0 0 0 0 0 0 +NM_001080870 chr26 4578266 4580646 - NA 461517 NA 459137 0 0 0 0 0 0 0 +NM_001080868 chr26 4578266 4580647 - NA 461518 NA 459137 0 0 0 0 0 0 0 +NM_001030922 chr26 4730394 4744364 - NA 625235 NA 611265 0 0 0 0 0 0 0 +NM_204877 chr26 4751619 4755464 - NA 636335 NA 632490 0 0 0 0 0 0 0 +NM_001302134 chr26 4791084 4792014 + 671955 NA 672885 NA 0 0 0 0 0 0 0 +NM_001006327 chr26 4828534 4833077 - NA 713948 NA 709405 0 0 0 0 0 0 0 +NM_001008453 chr26 4838545 4850970 - NA 731841 NA 719416 0 0 0 0 0 0 0 +NM_001030923 chr26 4876559 4884910 + 757430 NA 765781 NA 0 0 0 0 0 0 0 +NM_204429 chr26 4897094 4901738 - NA 782609 NA 777965 0 0 0 0 0 0 0 +NM_204967 chr26 4946735 4952662 - NA 833533 NA 827606 0 0 0 0 0 0 0 +NM_204473 chr26 4990765 4993729 + 871636 NA 874600 NA 0 0 0 0 0 0 0 +NR_105623 chr26 5087926 5087980 - NA 968851 NA 968797 0 0 0 0 0 0 0 diff -r 000000000000 -r f411ce97a351 test-data/galGal3.len --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/galGal3.len Tue Jun 30 07:08:05 2015 -0400 @@ -0,0 +1,57 @@ +chr1 200994015 +chr2 154873767 +chr3 113657789 +chr4 94230402 +chrZ 74602320 +chrUn_random 63870806 +chr5 62238931 +chr7 38384769 +chr6 37400442 +chr8 30671729 +chr9 25554352 +chr10 22556432 +chr11 21928095 +chr12 20536687 +chr13 18911934 +chr14 15819469 +chr20 13986235 +chr15 12968165 +chr17 11182526 +chr18 10925261 +chr19 9939723 +chr21 6959642 +chr24 6400109 +chr23 6042217 +chr26 5102438 +chr27 4841970 +chr28 4512026 +chr22 3936574 +chr25 2031799 +chrE22C19W28_E50C23 895237 +chrW_random 729481 +chrE64_random 557643 +chr16 432983 +chr8_random 420759 +chrZ_random 346234 +chrW 259642 +chr16_random 246252 +chr1_random 222095 +chrE22C19W28_E50C23_random 191099 +chr4_random 180706 +chr22_random 156216 +chr2_random 142837 +chr28_random 105415 +chr7_random 104000 +chr25_random 80372 +chr20_random 75095 +chr11_random 72667 +chrE64 49846 +chr13_random 35775 +chr6_random 34212 +chr5_random 27907 +chrM 16775 +chr10_random 13679 +chr18_random 11891 +chr12_random 7060 +chr17_random 2911 +chr32 1028 diff -r 000000000000 -r f411ce97a351 test-data/galGal3.refGene Binary file test-data/galGal3.refGene has changed diff -r 000000000000 -r f411ce97a351 tool-data/ceas.loc.sample --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/tool-data/ceas.loc.sample Tue Jun 30 07:08:05 2015 -0400 @@ -0,0 +1,17 @@ +#This is a sample file distributed with Galaxy that is used by the +#ceas tool. The ceas.loc file has this format (white space +#characters are TAB characters): +# +# +# +#For example: +# +#hg18_illumina_pe hg18 Human (hg18) /home/galaxy/genomes/ceaslib/GeneTable/hg18 +#mm9_generic mm9 Mouse (mm9) /home/galaxy/genomes/ceaslib/GeneTable/mm9 +#...etc... +# +# The GDB files are sqlite databases containing the RefSeq genes for +# the organism in question +# +#This file should be placed in galaxy's tool-data directory when the +#ceas tool is installed. diff -r 000000000000 -r f411ce97a351 tool_data_table_conf.xml.sample --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/tool_data_table_conf.xml.sample Tue Jun 30 07:08:05 2015 -0400 @@ -0,0 +1,6 @@ + + + value, dbkey, name, path + +

+ \ No newline at end of file diff -r 000000000000 -r f411ce97a351 tool_data_table_conf.xml.test --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/tool_data_table_conf.xml.test Tue Jun 30 07:08:05 2015 -0400 @@ -0,0 +1,6 @@ + + + value, dbkey, name, path + +

+ \ No newline at end of file diff -r 000000000000 -r f411ce97a351 tool_dependencies.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/tool_dependencies.xml Tue Jun 30 07:08:05 2015 -0400 @@ -0,0 +1,114 @@ + + + + + + + http://cran.r-project.org/src/base/R-3/R-3.1.2.tar.gz + ./configure --prefix=$INSTALL_DIR + + + $INSTALL_DIR/bin + + + + + + + + + https://pypi.python.org/packages/source/M/MySQL-python/MySQL-python-1.2.5.zip + $INSTALL_DIR/lib/python + + export PYTHONPATH=$PYTHONPATH:$INSTALL_DIR/lib/python && + python setup.py install --install-lib $INSTALL_DIR/lib/python --install-scripts $INSTALL_DIR/bin + + + $INSTALL_DIR/lib/python + $INSTALL_DIR/bin + + + + Installs Python module MySQLdb 1.2.5 + + + + + + +numpy==1.7.1 +bx-python==0.7.1 + + + $INSTALL_DIR + + + + + Installation of bx-python 0.7.1 along with numpy 1.7.1. The installation can be + accessed via BX_PYTHON_PATH. + + + + + + + + hg clone https://bitbucket.org/cistrome/cistrome-applications-harvard cistrome_ceas + + + hg update d8c0751 + + $INSTALL_DIR/lib/python + + cd published-packages/CEAS/ + export PYTHONPATH=$PYTHONPATH:$INSTALL_DIR/lib/python && + python setup.py install --install-lib $INSTALL_DIR/lib/python --install-scripts $INSTALL_DIR/bin + + + $INSTALL_DIR/lib/python + $INSTALL_DIR/bin + + + + Installs version 1.0.2 of CEAS from cistrome (commit id d8c0751, + datestamp 20140929), which includes ceasBW (a version of ceas which can + handle bigWig file input from MACS2. + + Cistrome code is at + https://bitbucket.org/cistrome/cistrome-applications-harvard/overview + + The CEAS code is under the published-packages/CEAS/ subdirectory + + Cistrome data files and documentation can be found at + http://liulab.dfci.harvard.edu/CEAS/index.html + + + + + + + + http://hgdownload.cse.ucsc.edu/admin/exe/linux.x86_64/fetchChromSizes + + + $INSTALL_DIR/fetchChromSizes + + + $INSTALL_DIR + + + + Installs the binary executable for the fetchChromSizes utility + from UCSC tools + + +