# HG changeset patch
# User lparsons
# Date 1437083023 14400
# Node ID 6b33e31bda1090c1008ce24ad1e76c722d66d7f0
# Parent  2e6190c29c540e2a1a79026597e2303929ce9356
Uploaded tar based on https://github.com/lparsons/galaxy_tools/tree/master/tools/rseqc 1a3c419bc0ded7c40cb2bc3e7c87bfb01ddfeba2

diff -r 2e6190c29c54 -r 6b33e31bda10 RPKM_count.xml
--- a/RPKM_count.xml	Tue Apr 21 10:27:06 2015 -0400
+++ b/RPKM_count.xml	Thu Jul 16 17:43:43 2015 -0400
@@ -1,12 +1,22 @@
-<tool id="rseqc_RPKM_count" name="RPKM Count" version="2.4">
+<tool id="rseqc_RPKM_count" name="RPKM Count" version="2.4galaxy1">
     <description>calculates raw count and RPKM values for transcript at exon, intron, and mRNA level</description>
+
+    <macros>
+        <import>rseqc_macros.xml</import>
+    </macros>
+
     <requirements>
-        <requirement type="package" version="1.7.1">numpy</requirement>
-        <requirement type="package" version="2.4">rseqc</requirement>
+        <expand macro="requirement_package_numpy" />
+        <expand macro="requirement_package_rseqc" />
     </requirements>
-    <command>
-        ln -s "${input}" "local_input.bam" &amp;&amp;
-        ln -s "${input.metadata.bam_index}" "local_input.bam.bai" &amp;&amp;
+
+    <expand macro="stdio" />
+
+    <version_command><![CDATA[RPKM_count.py --version]]></version_command>
+
+    <command><![CDATA[
+        ln -s "${input}" "local_input.bam" &&
+        ln -s "${input.metadata.bam_index}" "local_input.bam.bai" &&
         RPKM_count.py -i "local_input.bam" -o output -r $refgene
 
         #if str($strand_type.strand_specific) == "pair"
@@ -27,22 +37,18 @@
             #end if
         #end if
 
-        #if $skiphits
-            -u
-        #end if
-
-        #if $onlyexonic
-            -e
+        #if $multihits.skipmultihits
+            --skip-multi-hits
+            --mapq=$multihits.mapq
         #end if
 
+        $onlyexonic
+        ]]>
     </command>
-    <stdio>
-        <exit_code range="1:" level="fatal" description="An error occured during execution, see stderr and stdout for more information" />
-        <regex match="[Ee]rror" source="both" description="An error occured during execution, see stderr and stdout for more information" />
-    </stdio>
+
     <inputs>
-        <param name="input" type="data" format="bam" label="input bam/sam file" />
-        <param name="refgene" type="data" format="bed" label="Reference gene model" />
+        <param name="input" type="data" label="Input .bam File" format="bam" help="(--input-file)"/>
+        <param name="refgene" type="data" format="bed" label="reference gene model" help="(--refgene)"/>
         <conditional name="strand_type">
             <param name="strand_specific" type="select" label="Strand-specific?" value="None">
                 <option value="none">None</option>
@@ -50,26 +56,44 @@
                 <option value="single">Single-End RNA-seq</option>
             </param>
             <when value="pair">
-                <param name="pair_type" type="select" display="radio" label="Pair-End Read Type (format: mapped --> parent)" value="sd">
+                <param name="pair_type" type="select" display="radio" label="Pair-End Read Type (format: mapped --> parent)" value="sd" help="(--strand)">
                     <option value="sd"> read1 (positive --> positive; negative --> negative), read2 (positive --> negative; negative --> positive)</option>
                     <option value="ds">read1 (positive --> negative; negative --> positive), read2 (positive --> positive; negative --> negative)</option>
                 </param>
             </when>
             <when value="single">
-                <param name="single_type" type="select" display="radio" label="Single-End Read Type (format: mapped --> parent)" value="s">
+                <param name="single_type" type="select" display="radio" label="Single-End Read Type (format: mapped --> parent)" value="s" help="(--strand)">
                     <option value="s">positive --> positive; negative --> negative</option>
                     <option value="d">positive --> negative; negative --> positive</option>
                 </param>
             </when>
             <when value="none"></when>
         </conditional>
-        <param name="skiphits" type="boolean" value="false" label="Skip Multiple Hit Reads" />
-        <param name="onlyexonic" type="boolean" value="false" label="Only use exonic (UTR exons and CDS exons) reads, otherwise use all reads" />
+
+        <conditional name="multihits">
+            <param name="skipmultihits" type="boolean" label="Skip Multiple Hit Reads/Only Use Uniquely Mapped Reads" value="false" help="(--skip-multi-hits)" />
+            <when value="true">
+                <param name="mapq" value="30" type="integer" label="Minimum mapping quality for an alignment to be called 'uniquly mapped'" help="(--mapq)" />
+            </when>
+            <when value="false" />
+        </conditional>
+
+        <param name="onlyexonic" type="boolean" value="false" truevalue="--only-exonic" falsevalue="" label="Only use exonic (UTR exons and CDS exons) reads, otherwise use all reads" help="(--only-exonic)"/>
     </inputs>
+
     <outputs>
         <data format="xls" name="outputxls" from_work_dir="output_read_count.xls"/>
     </outputs>
-    <help>
+
+    <tests>
+        <test>
+            <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam"/>
+            <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed"/>
+            <output name="outputxls" file="output_read_count.xls"/>
+        </test>
+    </tests>
+
+    <help><![CDATA[
 RPKM_count.py
 +++++++++++++
 
@@ -77,7 +101,7 @@
 values for transcript at exon, intron and mRNA level. For strand specific RNA-seq data,
 program will assign read to its parental gene according to strand rule, if you don't know the
 strand rule, run infer_experiment.py. Please note that chromosome ID, genome cooridinates
-should be concordant between BAM and BED files. 
+should be concordant between BAM and BED files.
 
 Inputs
 ++++++++++++++
@@ -97,7 +121,7 @@
 Skip Multiple Hit Reads
     Use Multiple hit reads or use only uniquely mapped reads.
 
-Only use exonic reads 
+Only use exonic reads
     Renders program only used exonic (UTR exons and CDS exons) reads, otherwise use all reads.
 
 Sample Output
@@ -113,10 +137,10 @@
 chr1    29313959   29314417   NM_001166007_exon_2      0      '+'            1699            4               74.158    0.175
 chr1    29319841   29320054   NM_001166007_exon_3      0      '+'             528             1               49.554    0.094
 =====   ========   ========   =====================    =====  ===========   =============   =============   ========  =========
-    
+
 -----
 
-About RSeQC 
+About RSeQC
 +++++++++++
 
 The RSeQC_ package provides a number of useful modules that can comprehensively evaluate high throughput sequence data especially RNA-seq data. "Basic modules" quickly inspect sequence quality, nucleotide composition bias, PCR bias and GC bias, while "RNA-seq specific modules" investigate sequencing saturation status of both splicing junction detection and expression estimation, mapped reads clipping profile, mapped reads distribution, coverage uniformity over gene body, reproducibility, strand specificity and splice junction annotation.
@@ -126,7 +150,9 @@
 .. image:: http://rseqc.sourceforge.net/_static/logo.png
 
 .. _RSeQC: http://rseqc.sourceforge.net/
-
+]]>
+    </help>
 
-    </help>
+    <expand macro="citations" />
+
 </tool>
diff -r 2e6190c29c54 -r 6b33e31bda10 RPKM_saturation.xml
--- a/RPKM_saturation.xml	Tue Apr 21 10:27:06 2015 -0400
+++ b/RPKM_saturation.xml	Thu Jul 16 17:43:43 2015 -0400
@@ -1,11 +1,22 @@
-<tool id="rseqc_RPKM_saturation" name="RPKM Saturation" version="2.4">
+<tool id="rseqc_RPKM_saturation" name="RPKM Saturation" version="2.4galaxy1">
     <description>calculates raw count and RPKM values for transcript at exon, intron, and mRNA level</description>
+
+    <macros>
+        <import>rseqc_macros.xml</import>
+    </macros>
+
     <requirements>
-        <requirement type="package" version="3.0.3">R</requirement>
-        <requirement type="package" version="1.7.1">numpy</requirement>
-        <requirement type="package" version="2.4">rseqc</requirement>
+        <expand macro="requirement_package_r" />
+        <expand macro="requirement_package_numpy" />
+        <expand macro="requirement_package_rseqc" />
     </requirements>
-    <command> RPKM_saturation.py -i $input -o output -r $refgene
+
+    <expand macro="stdio" />
+
+    <version_command><![CDATA[RPKM_saturation.py --version]]></version_command>
+
+    <command><![CDATA[
+        RPKM_saturation.py -i $input -o output -r $refgene
 
         #if str($strand_type.strand_specific) == "pair"
             -d
@@ -26,15 +37,12 @@
         #end if
 
         -l $percentileFloor -u $percentileCeiling -s $percentileStep -c $rpkmCutoff
-
+        ]]>
     </command>
-    <stdio>
-        <exit_code range="1:" level="fatal" description="An error occured during execution, see stderr and stdout for more information" />
-        <regex match="[Ee]rror" source="both" description="An error occured during execution, see stderr and stdout for more information" />
-    </stdio>
+
     <inputs>
-        <param name="input" type="data" format="bam" label="input bam/sam file" />
-        <param name="refgene" type="data" format="bed" label="Reference gene model" />
+        <param name="input" type="data" label="Input .bam File" format="bam" help="(--input-file)"/>
+        <param name="refgene" type="data" format="bed" label="reference gene model" help="(--refgene)"/>
         <conditional name="strand_type">
             <param name="strand_specific" type="select" label="Strand-specific?" value="None">
                 <option value="none">None</option>
@@ -42,31 +50,46 @@
                 <option value="single">Single-End RNA-seq</option>
             </param>
             <when value="pair">
-                <param name="pair_type" type="select" display="radio" label="Pair-End Read Type (format: mapped --> parent)" value="sd">
+                <param name="pair_type" type="select" display="radio" label="Pair-End Read Type (format: mapped --> parent)" value="sd" help="(--strand)">
                     <option value="sd"> read1 (positive --> positive; negative --> negative), read2 (positive --> negative; negative --> positive)</option>
                     <option value="ds">read1 (positive --> negative; negative --> positive), read2 (positive --> positive; negative --> negative)</option>
                 </param>
             </when>
             <when value="single">
-                <param name="single_type" type="select" display="radio" label="Single-End Read Type (format: mapped --> parent)" value="s">
+                <param name="single_type" type="select" display="radio" label="Single-End Read Type (format: mapped --> parent)" value="s" help="(--strand)">
                     <option value="s">positive --> positive; negative --> negative</option>
                     <option value="d">positive --> negative; negative --> positive</option>
                 </param>
             </when>
             <when value="none"></when>
         </conditional>
-        <param name="percentileFloor" type="integer" value="5" label="Begin sampling from this percentile (default=5)" />
-        <param name="percentileCeiling" type="integer" value="100" label="End sampling at this percentile (default=100)" />
-        <param name="percentileStep" type="integer" value="5" label="Sampling step size (default=5)" />
-        <param name="rpkmCutoff" type="text" value="0.01" label="Ignore transcripts with RPKM smaller than this number (default=0.01)" />
+        <param name="percentileFloor" type="integer" value="5" label="Begin sampling from this percentile (default=5)" help="(--percentile-floor)"/>
+        <param name="percentileCeiling" type="integer" value="100" label="End sampling at this percentile (default=100)" help="(--percentile-ceiling)" />
+        <param name="percentileStep" type="integer" value="5" label="Sampling step size (default=5)" help="(--percentile-step)" />
+        <param name="rpkmCutoff" type="text" value="0.01" label="Ignore transcripts with RPKM smaller than this number (default=0.01)" help="(--rpkm-cutoff)" />
+        <param name="mapq" value="30" type="integer" label="Minimum mapping quality for an alignment to be called 'uniquly mapped'" help="(--mapq)" />
     </inputs>
+
     <outputs>
         <data format="xls" name="outputxls" from_work_dir="output.eRPKM.xls" label="${tool.name} on ${on_string} (RPKM XLS)"/>
         <data format="xls" name="outputrawxls" from_work_dir="output.rawCount.xls" label="${tool.name} on ${on_string} (Raw Count XLS)"/>
         <data format="txt" name="outputr" from_work_dir="output.saturation.r" label="${tool.name} on ${on_string} (R Script)"/>
         <data format="pdf" name="outputpdf" from_work_dir="output.saturation.pdf" label="${tool.name} on ${on_string} (PDF)"/>
     </outputs>
-    <help>
+
+    <!-- Unable to succefully run this script with test data
+    <tests>
+        <test>
+            <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam"/>
+            <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed"/>
+            <output name="outputxls" file="output.eRPKM.xls"/>
+            <output name="outputrawxls" file="output.rawCount.xls"/>
+            <output name="outputr" file="output.saturation.r"/>
+        </test>
+    </tests>
+    -->
+
+    <help><![CDATA[
 RPKM_saturation.py
 ++++++++++++++++++
 
@@ -77,7 +100,7 @@
 the current sequencing depth was saturated or not (or if the RPKM values were stable or not)
 in terms of genes' expression estimation. If sequencing depth was saturated, the estimated
 RPKM value will be stationary or reproducible. By default, this module will calculate 20
-RPKM values (using 5%, 10%, ... , 95%,100% of total reads) for each transcripts. 
+RPKM values (using 5%, 10%, ... , 95%,100% of total reads) for each transcripts.
 
 In the output figure, Y axis is "Percent Relative Error" or "Percent Error" which is used
 to measures how the RPKM estimated from subset of reads (i.e. RPKMobs) deviates from real
@@ -107,7 +130,7 @@
 Skip Multiple Hit Reads
     Use Multiple hit reads or use only uniquely mapped reads.
 
-Only use exonic reads 
+Only use exonic reads
     Renders program only used exonic (UTR exons and CDS exons) reads, otherwise use all reads.
 
 Output
@@ -121,7 +144,7 @@
 .. image:: http://rseqc.sourceforge.net/_images/saturation.png
    :height: 600 px
    :width: 600 px
-   :scale: 80 %     
+   :scale: 80 %
 
 - All transcripts were sorted in ascending order according to expression level (RPKM). Then they are divided into 4 groups:
     1. Q1 (0-25%): Transcripts with expression level ranked below 25 percentile.
@@ -140,11 +163,11 @@
 .. image:: http://rseqc.sourceforge.net/_images/saturation_eg.png
    :height: 600 px
    :width: 600 px
-   :scale: 80 % 
+   :scale: 80 %
 
 -----
 
-About RSeQC 
+About RSeQC
 +++++++++++
 
 The RSeQC_ package provides a number of useful modules that can comprehensively evaluate high throughput sequence data especially RNA-seq data. "Basic modules" quickly inspect sequence quality, nucleotide composition bias, PCR bias and GC bias, while "RNA-seq specific modules" investigate sequencing saturation status of both splicing junction detection and expression estimation, mapped reads clipping profile, mapped reads distribution, coverage uniformity over gene body, reproducibility, strand specificity and splice junction annotation.
@@ -154,7 +177,9 @@
 .. image:: http://rseqc.sourceforge.net/_static/logo.png
 
 .. _RSeQC: http://rseqc.sourceforge.net/
-
+]]>
+    </help>
 
-    </help>
+    <expand macro="citations" />
+
 </tool>
diff -r 2e6190c29c54 -r 6b33e31bda10 bam2wig.xml
--- a/bam2wig.xml	Tue Apr 21 10:27:06 2015 -0400
+++ b/bam2wig.xml	Thu Jul 16 17:43:43 2015 -0400
@@ -1,19 +1,26 @@
-<tool id="rseqc_bam2wig" name="BAM to Wiggle" version="2.4">
-    <description> 
-        converts all types of RNA-seq data from .bam to .wig 
+<tool id="rseqc_bam2wig" name="BAM to Wiggle" version="2.4galaxy1">
+    <description>
+        converts all types of RNA-seq data from .bam to .wig
     </description>
+
+    <macros>
+        <import>rseqc_macros.xml</import>
+    </macros>
+
     <requirements>
-        <requirement type="package" version="3.0.3">R</requirement>
-        <requirement type="package" version="1.7.1">numpy</requirement>
-        <requirement type="package" version="2.4">rseqc</requirement>
+        <expand macro="requirement_package_r" />
+        <expand macro="requirement_package_numpy" />
+        <expand macro="requirement_package_rseqc" />
     </requirements>
-    <command>
-        tmp_input_name=\$(mktemp -u);
-        bai='.bai';
+
+    <expand macro="stdio" />
+
+    <version_command><![CDATA[bam2wig.py --version]]></version_command>
 
-        ln -s "${input}" \$tmp_input_name &amp;&amp;
-        ln -s "${input.metadata.bam_index}" \$tmp_input_name\$bai &amp;&amp;
-        bam2wig.py -i \$tmp_input_name -s $chromsize -o outfile
+    <command><![CDATA[
+        ln -sfn '${input}' 'input.bam' &&
+        ln -sfn '${input.metadata.bam_index}' 'input.bam.bai' &&
+        bam2wig.py -i input.bam -s $chromsize -o outfile
 
         #if str($strand_type.strand_specific) == "pair"
             -d
@@ -36,26 +43,34 @@
         #if $wigsum.wigsum_type
             -t $wigsum.totalwig
         #end if
-
-        #if $skipmultihits
-            -u
+        #if $multihits.skipmultihits
+            --skip-multi-hits
+            --mapq=$multihits.mapq
         #end if
-        ;
-        rm "\$tmp_input_name\$bai";
-        rm \$tmp_input_name
+        2>&1
+        ]]>
     </command>
     <inputs>
-        <param name="input" type="data" label="Input .bam File" format="bam" />
-        <param name="chromsize" type="data" label="Chromosome size file (tab or space separated)" format="txt,tabular" />
-        <param name="skipmultihits" type="boolean" label="Skip Multiple Hit Reads/Only Use Uniquely Mapped Reads" value="false" />
+        <param name="input" type="data" label="Input .bam File" format="bam" help="(--input-file)"/>
+        <param name="chromsize" type="data" label="Chromosome size file (tab or space separated)" format="txt,tabular" help="(--chromSize)"/>
+
+        <conditional name="multihits">
+            <param name="skipmultihits" type="boolean" label="Skip Multiple Hit Reads/Only Use Uniquely Mapped Reads" value="false" help="(--skip-multi-hits)" />
+            <when value="true">
+                <param name="mapq" value="30" type="integer" label="Minimum mapping quality for an alignment to be called 'uniquly mapped'" help="(--mapq)" />
+            </when>
+            <when value="false" />
+        </conditional>
+
         <conditional name="wigsum">
             <param name="wigsum_type" type="boolean" label="Specify wigsum?" value="false">
             </param>
             <when value="true">
-                <param name="totalwig" value="0" type="integer" label="specified wigsum" />
+                <param name="totalwig" value="0" type="integer" label="specified wigsum" help="(--wigsum)"/>
             </when>
             <when value="false"/>
         </conditional>
+
         <conditional name="strand_type">
             <param name="strand_specific" type="select" label="Strand-specific?" value="none">
                 <option value="none">none</option>
@@ -63,13 +78,13 @@
                 <option value="single">Single-End RNA-seq</option>
             </param>
             <when value="pair">
-                <param name="pair_type" type="select" display="radio" label="Pair-End Read Type (format: mapped --> parent)" value="sd">
+                <param name="pair_type" type="select" display="radio" label="Pair-End Read Type (format: mapped --> parent)" value="sd" help="(--strand)">
                     <option value="sd"> read1 (positive --> positive; negative --> negative), read2 (positive --> negative; negative --> positive)</option>
                     <option value="ds">read1 (positive --> negative; negative --> positive), read2 (positive --> positive; negative --> negative)</option>
                 </param>
             </when>
             <when value="single">
-                <param name="single_type" type="select" display="radio" label="Single-End Read Type (format: mapped --> parent)" value="s">
+                <param name="single_type" type="select" display="radio" label="Single-End Read Type (format: mapped --> parent)" value="s" help="(--strand)">
                     <option value="s">positive --> positive; negative --> negative</option>
                     <option value="d">positive --> negative; negative --> positive</option>
                 </param>
@@ -77,7 +92,8 @@
             <when value="none"></when>
         </conditional>
     </inputs>
-    <outputs> 
+
+    <outputs>
         <data format="wig" name="output" from_work_dir="outfile.wig">
             <filter>strand_type['strand_specific'] == 'none'</filter>
         </data>
@@ -88,11 +104,31 @@
             <filter>strand_type['strand_specific'] != 'none'</filter>
         </data>
     </outputs>
-    <stdio>
-        <exit_code range="1:" level="fatal" description="An error occured during execution, see stderr and stdout for more information" />
-        <regex match="[Ee]rror" source="both" description="An error occured during execution, see stderr and stdout for more information" />
-    </stdio>
-    <help>
+
+    <tests>
+        <test>
+            <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam"/>
+            <param name="chromsize" value="hg19.chrom.sizes"/>
+            <output name="output" file="testwig.wig"/>
+        </test>
+        <test>
+            <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam"/>
+            <param name="chromsize" value="hg19.chrom.sizes"/>
+            <param name="skipmultihits" value="True"/>
+            <param name="mapq" value="20"/>
+            <output name="output" file="testwig.wig"/>
+        </test>
+        <test>
+            <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam"/>
+            <param name="chromsize" value="hg19.chrom.sizes"/>
+            <param name="strand_specific" value="pair"/>
+            <param name="pair_type" value="sd"/>
+            <output name="outputfwd" file="testwig.Forward.wig"/>
+            <output name="outputrv" file="testwig.Reverse.wig"/>
+        </test>
+    </tests>
+
+    <help><![CDATA[
 bam2wig.py
 ++++++++++
 
@@ -131,10 +167,9 @@
 
 -----
 
-About RSeQC 
+About RSeQC
 +++++++++++
 
-
 The RSeQC_ package provides a number of useful modules that can comprehensively evaluate high throughput sequence data especially RNA-seq data. "Basic modules" quickly inspect sequence quality, nucleotide composition bias, PCR bias and GC bias, while "RNA-seq specific modules" investigate sequencing saturation status of both splicing junction detection and expression estimation, mapped reads clipping profile, mapped reads distribution, coverage uniformity over gene body, reproducibility, strand specificity and splice junction annotation.
 
 The RSeQC package is licensed under the GNU GPL v3 license.
@@ -142,12 +177,16 @@
 .. image:: http://rseqc.sourceforge.net/_static/logo.png
 
 .. _RSeQC: http://rseqc.sourceforge.net/
+
 .. _UCSC: http://genome.ucsc.edu/index.html
 .. _IGB: http://bioviz.org/igb/
 .. _IGV: http://www.broadinstitute.org/igv/home
 .. _BAM: http://genome.ucsc.edu/goldenPath/help/bam.html
 .. _wiggle: http://genome.ucsc.edu/goldenPath/help/wiggle.html
 .. _bigwig: http://genome.ucsc.edu/FAQ/FAQformat.html#format6.1
-
+]]>
     </help>
+
+    <expand macro="citations" />
+
 </tool>
diff -r 2e6190c29c54 -r 6b33e31bda10 bam_stat.xml
--- a/bam_stat.xml	Tue Apr 21 10:27:06 2015 -0400
+++ b/bam_stat.xml	Thu Jul 16 17:43:43 2015 -0400
@@ -1,31 +1,49 @@
-<tool id="rseqc_bam_stat" name="BAM/SAM Mapping Stats" version="2.4">
+<tool id="rseqc_bam_stat" name="BAM/SAM Mapping Stats" version="2.4galaxy1">
     <description>
         reads mapping statistics for a provided BAM or SAM file.
     </description>
+
+    <macros>
+        <import>rseqc_macros.xml</import>
+    </macros>
+
     <requirements>
-        <requirement type="package" version="1.7.1">numpy</requirement>
-        <requirement type="package" version="2.4">rseqc</requirement>
-    </requirements>s
-    <command>
-        bam_stat.py -i $input -q $mapqual 2> $output
+        <expand macro="requirement_package_numpy" />
+        <expand macro="requirement_package_rseqc" />
+    </requirements>
+
+    <expand macro="stdio" />
+
+    <version_command><![CDATA[bam_stat.py --version]]></version_command>
+
+    <command><![CDATA[
+        bam_stat.py -i $input -q $mapq 2> $output
+        ]]>
     </command>
-    <stdio>
-        <exit_code range="1:" level="fatal" description="An error occured during execution, see stderr and stdout for more information" />
-        <regex match="[Ee]rror" source="both" description="An error occured during execution, see stderr and stdout for more information" />
-    </stdio>
+
     <inputs>
-        <param name="input" type="data" label="Input .bam/.sam File" format="bam,sam" />
-        <param label="Minimum mapping quality (default=30" type="integer" value="30" name="mapqual" />
+        <param name="input" type="data" label="Input .bam File" format="bam" help="(--input-file)"/>
+        <param name="mapq" value="30" type="integer" label="Minimum mapping quality for an alignment to be called 'uniquly mapped'" help="(--mapq)" />
     </inputs>
+
     <outputs>
         <data format="txt" name="output" />
     </outputs>
-    <help>
+
+    <tests>
+        <test>
+            <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam"/>
+            <output name="output" file="bamstats.txt"/>
+        </test>
+    </tests>
+
+    <help><![CDATA[
 bam_stat.py
 +++++++++++
 
 This program is used to calculate reads mapping statistics from provided BAM
-file.  This script determines "uniquely mapped reads" from `mapping quality`_,
+file.  This script determines "uniquely mapped reads" from `mapping quality
+<http://genome.sph.umich.edu/wiki/Mapping_Quality_Scores>`_,
 which quality the probability that a read is misplaced (Do NOT confused with
 sequence quality, sequence quality measures the probability that a base-calling
 was wrong) .
@@ -37,7 +55,7 @@
 	Alignment file in BAM/SAM format.
 
 Minimum mapping quality
-	Minimum mapping quality for an alignment to be called “uniquely mapped” (default=30)
+	Minimum mapping quality for an alignment to be called "uniquely mapped" (default=30)
 
 Output
 ++++++++++++++
@@ -49,9 +67,10 @@
 
 -----
 
-About RSeQC 
+About RSeQC
 +++++++++++
 
+
 The RSeQC_ package provides a number of useful modules that can comprehensively evaluate high throughput sequence data especially RNA-seq data. "Basic modules" quickly inspect sequence quality, nucleotide composition bias, PCR bias and GC bias, while "RNA-seq specific modules" investigate sequencing saturation status of both splicing junction detection and expression estimation, mapped reads clipping profile, mapped reads distribution, coverage uniformity over gene body, reproducibility, strand specificity and splice junction annotation.
 
 The RSeQC package is licensed under the GNU GPL v3 license.
@@ -59,7 +78,9 @@
 .. image:: http://rseqc.sourceforge.net/_static/logo.png
 
 .. _RSeQC: http://rseqc.sourceforge.net/
-.. _`mapping quality`: http://genome.sph.umich.edu/wiki/Mapping_Quality_Scores
 
+]]>
     </help>
+
+    <expand macro="citations" />
 </tool>
diff -r 2e6190c29c54 -r 6b33e31bda10 clipping_profile.xml
--- a/clipping_profile.xml	Tue Apr 21 10:27:06 2015 -0400
+++ b/clipping_profile.xml	Thu Jul 16 17:43:43 2015 -0400
@@ -1,27 +1,47 @@
-<tool id="rseqc_clipping_profile" name="Clipping Profile" version="2.4">
+<tool id="rseqc_clipping_profile" name="Clipping Profile" version="2.4galaxy1">
     <description>
      estimates clipping profile of RNA-seq reads from BAM or SAM file
     </description>
+
+    <macros>
+        <import>rseqc_macros.xml</import>
+    </macros>
+
     <requirements>
-        <requirement type="package" version="3.0.3">R</requirement>
-        <requirement type="package" version="1.7.1">numpy</requirement>
-        <requirement type="package" version="2.4">rseqc</requirement>
+        <expand macro="requirement_package_r" />
+        <expand macro="requirement_package_numpy" />
+        <expand macro="requirement_package_rseqc" />
     </requirements>
-    <command>
+
+    <expand macro="stdio" />
+
+    <version_command><![CDATA[clipping_profile.py --version]]></version_command>
+
+    <command><![CDATA[
         clipping_profile.py -i $input -o output
+        ]]>
     </command>
-    <stdio>
-        <exit_code range="1:" level="fatal" description="An error occured during execution, see stderr and stdout for more information" />
-        <regex match="[Ee]rror" source="both" description="An error occured during execution, see stderr and stdout for more information" />
-    </stdio>
+
     <inputs>
-        <param name="input" type="data" label="Input .bam/.sam File" format="bam,sam" />
+        <param name="input" type="data" label="Input .bam File" format="bam" help="(--input-file)"/>
     </inputs>
+
     <outputs>
+        <data format="pdf" name="outputpdf" from_work_dir="output.clipping_profile.pdf" />
         <data format="xls" name="outputxls" from_work_dir="output.clipping_profile.xls" />
         <data format="txt" name="outputr" from_work_dir="output.clipping_profile.r" />
     </outputs>
-    <help>
+
+    <tests>
+        <test>
+            <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam"/>
+            <output name="outputpdf" file="output.clipping_profile.pdf"/>
+            <output name="outputxls" file="output.clipping_profile.xls"/>
+            <output name="outputr" file="output.clipping_profile.r"/>
+        </test>
+    </tests>
+
+    <help><![CDATA[
 clipping_profile.py
 +++++++++++++++++++
 
@@ -46,7 +66,7 @@
 
 -----
 
-About RSeQC 
+About RSeQC
 +++++++++++
 
 The RSeQC_ package provides a number of useful modules that can comprehensively evaluate high throughput sequence data especially RNA-seq data. "Basic modules" quickly inspect sequence quality, nucleotide composition bias, PCR bias and GC bias, while "RNA-seq specific modules" investigate sequencing saturation status of both splicing junction detection and expression estimation, mapped reads clipping profile, mapped reads distribution, coverage uniformity over gene body, reproducibility, strand specificity and splice junction annotation.
@@ -56,6 +76,9 @@
 .. image:: http://rseqc.sourceforge.net/_static/logo.png
 
 .. _RSeQC: http://rseqc.sourceforge.net/
-
+]]>
     </help>
+
+    <expand macro="citations" />
+
 </tool>
diff -r 2e6190c29c54 -r 6b33e31bda10 geneBody_coverage.xml
--- a/geneBody_coverage.xml	Tue Apr 21 10:27:06 2015 -0400
+++ b/geneBody_coverage.xml	Thu Jul 16 17:43:43 2015 -0400
@@ -1,40 +1,49 @@
-<tool id="rseqc_geneBody_coverage" name="Gene Body Converage (BAM)" version="2.4">
+<tool id="rseqc_geneBody_coverage" name="Gene Body Converage (BAM)" version="2.4galaxy1">
     <description>
         Read coverage over gene body.
     </description>
+
+    <macros>
+        <import>rseqc_macros.xml</import>
+    </macros>
+
     <requirements>
-        <requirement type="package" version="3.0.3">R</requirement>
-        <requirement type="package" version="1.7.1">numpy</requirement>
-        <requirement type="package" version="2.4">rseqc</requirement>
+        <expand macro="requirement_package_r" />
+        <expand macro="requirement_package_numpy" />
+        <expand macro="requirement_package_rseqc" />
     </requirements>
-    <command>
+
+    <expand macro="stdio" />
+
+    <version_command><![CDATA[geneBody_coverage.py --version]]></version_command>
+
+    <command><![CDATA[
         #set $safename = ''.join(c in '_0123456789abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ' and c or '_' for c in $input.display_name)
         #set $fname = "d1_" + str($safename) + ".bam"
-        ln -s '${input}' '${fname}' &amp;&amp;
-        ln -s '${input.metadata.bam_index}' '${fname}.bai' &amp;&amp;
-        echo '${fname}' > input_list.txt &amp;&amp;
+        ln -s '${input}' '${fname}' &&
+        ln -s '${input.metadata.bam_index}' '${fname}.bai' &&
+        echo '${fname}' > input_list.txt &&
         #for $i, $additional_input in enumerate($additionalinputs):
             #set $index = $i+2
             #set $safename = ''.join(c in '_0123456789abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ' and c or '_' for c in $additional_input.file.display_name)
             #set $fname = 'd' + str($index) + '_' + str($safename) + ".bam"
-            ln -s '$additional_input.file' '${fname}' &amp;&amp;
-            ln -s '$additional_input.file.metadata.bam_index' '${fname}.bai' &amp;&amp;
-            echo '${fname}' >> input_list.txt &amp;&amp;
+            ln -s '$additional_input.file' '${fname}' &&
+            ln -s '$additional_input.file.metadata.bam_index' '${fname}.bai' &&
+            echo '${fname}' >> input_list.txt &&
         #end for
         geneBody_coverage.py -i input_list.txt -r $refgene --minimum_length $minimum_length -o output
+        ]]>
     </command>
-    <stdio>
-        <exit_code range="1:" level="fatal" description="An error occured during execution, see stderr and stdout for more information" />
-        <regex match="[Ee]rror" source="both" description="An error occured during execution, see stderr and stdout for more information" />
-    </stdio>
+
     <inputs>
-        <param name="input" type="data" label="Additional input .bam files" format="bam" />
-        <repeat name="additionalinputs" title="Input .bam file">
-            <param name="file" type="data" label="Input .bam file" format="bam" />
+        <param name="input" type="data" label="Input .bam File" format="bam" help="(--input-file)"/>
+        <repeat name="additionalinputs" title="Additional input .bam files">
+            <param name="file" type="data" label="Additional input .bam file" format="bam" />
         </repeat>
-        <param name="refgene" type="data" label="Reference Genome" format="bed" />
-        <param name="minimum_length" type="integer" value="100" label="Minimum mRNA length" help="Minimum mRNA length (bp). mRNA that are shorter than this value will be skipped (default is 100)." />
+        <param name="refgene" type="data" format="bed" label="reference gene model" help="(--refgene)"/>
+        <param name="minimum_length" type="integer" value="100" label="Minimum mRNA length in bp (default: 100)" help="mRNA that are shorter than this value will be skipped (--minimum_length)." />
     </inputs>
+
     <outputs>
         <data name="outputcurvespdf" format="pdf" from_work_dir="output.geneBodyCoverage.curves.pdf" label="${tool.name} on ${on_string} (Curves PDF)" />
         <data name="outputheatmappdf" format="pdf" from_work_dir="output.geneBodyCoverage.heatMap.pdf" label="${tool.name} on ${on_string} (HeatMap PDF)">
@@ -43,7 +52,29 @@
         <data name="outputr" format="txt" from_work_dir="output.geneBodyCoverage.r" label="${tool.name} on ${on_string} (R Script)" />
         <data name="outputtxt" format="txt" from_work_dir="output.geneBodyCoverage.txt" label="${tool.name} on ${on_string} (Text)" />
     </outputs>
-    <help>
+
+    <tests>
+        <test>
+            <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam"/>
+            <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed"/>
+            <output name="outputcurvespdf" file="output.geneBodyCoverage.curves.pdf"/>
+            <output name="outputr" file="output.geneBodyCoverage.r"/>
+            <output name="outputtxt" file="output.geneBodyCoverage.txt"/>
+        </test>
+        <test>
+            <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam"/>
+            <param name="file_0" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam"/>
+            <param name="file_1" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam"/>
+            <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed"/>
+            <output name="outputcurvespdf" file="output2.geneBodyCoverage.curves.pdf"/>
+            <output name="outputcurvespdf" file="output2.geneBodyCoverage.heatMap.pdf"/>
+            <output name="outputr" file="output2.geneBodycoverage.r"/>
+            <output name="outputtxt" file="output2.geneBodyCoverage.txt"/>
+        </test>
+
+    </tests>
+
+    <help><![CDATA[
 geneBody_coverage.py
 ++++++++++++++++++++
 
@@ -52,7 +83,12 @@
 If 3 or more BAM files were provided. This program generates a lineGraph and a heatmap. If fewer than 3 BAM files were provided, only lineGraph is generated. See below for examples.
 
 When heatmap is generated, samples are ranked by the "skewness" of the coverage: Sample with best (worst) coverage will be displayed at the top (bottom) of the heatmap.
-Coverage skewness was measured by `Pearson’s skewness coefficients &lt;http://en.wikipedia.org/wiki/Skewness#Pearson.27s_skewness_coefficients>`_
+Coverage skewness was measured by `Pearson’s skewness coefficients <http://en.wikipedia.org/wiki/Skewness#Pearson.27s_skewness_coefficients>`_
+
+    .. image:: http://rseqc.sourceforge.net/_images/geneBody_workflow.png
+        :width: 800 px
+        :scale: 80 %
+
 
 Inputs
 ++++++++++++++
@@ -100,8 +136,9 @@
 .. image:: http://rseqc.sourceforge.net/_static/logo.png
 
 .. _RSeQC: http://rseqc.sourceforge.net/
-
-
+]]>
+    </help>
 
-	</help>
+    <expand macro="citations" />
+
 </tool>
diff -r 2e6190c29c54 -r 6b33e31bda10 geneBody_coverage2.xml
--- a/geneBody_coverage2.xml	Tue Apr 21 10:27:06 2015 -0400
+++ b/geneBody_coverage2.xml	Thu Jul 16 17:43:43 2015 -0400
@@ -1,29 +1,51 @@
-<tool id="rseqc_geneBody_coverage2" name="Gene Body Converage (Bigwig)" version="2.4">
+<tool id="rseqc_geneBody_coverage2" name="Gene Body Converage (Bigwig)" version="2.4galaxy1">
     <description>
         Read coverage over gene body
     </description>
+
+    <macros>
+        <import>rseqc_macros.xml</import>
+    </macros>
+
     <requirements>
-        <requirement type="package" version="3.0.3">R</requirement>
-        <requirement type="package" version="1.7.1">numpy</requirement>
-        <requirement type="package" version="2.4">rseqc</requirement>
+        <expand macro="requirement_package_r" />
+        <expand macro="requirement_package_numpy" />
+        <expand macro="requirement_package_rseqc" />
     </requirements>
-    <command>
+
+    <expand macro="stdio" />
+
+    <version_command><![CDATA[geneBody_coverage2.py --version]]></version_command>
+
+    <command><![CDATA[
         geneBody_coverage2.py -i $input -r $refgene -o output
+        ]]>
     </command>
-    <stdio>
-        <exit_code range="1:" level="fatal" description="An error occured during execution, see stderr and stdout for more information" />
-        <regex match="[Ee]rror" source="both" description="An error occured during execution, see stderr and stdout for more information" />
-    </stdio>
+
     <inputs>
         <param name="input" type="data" label="Input bigwig file" format="bigwig" />
         <param name="refgene" type="data" label="Reference Genome" format="bed" />
     </inputs>
+
     <outputs>
         <data name="outputpdf" format="pdf" from_work_dir="output.geneBodyCoverage.pdf" label="${tool.name} on ${on_string} (PDF)" />
         <data name="outputr" format="txt" from_work_dir="output.geneBodyCoverage_plot.r" label="${tool.name} on ${on_string} (R Script)" />
         <data name="outputtxt" format="txt" from_work_dir="output.geneBodyCoverage.txt" label="${tool.name} on ${on_string} (Text)" />
     </outputs>
-    <help>
+
+    <!-- Unable to succefully run this script, it seems deprecated and should probably be dropped
+    <tests>
+        <test>
+            <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bigwig"/>
+            <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed"/>
+            <output name="outputcurvespdf" file="output.geneBodyCoverage.curves.pdf"/>
+            <output name="outputr" file="output.geneBodyCoverage.r"/>
+            <output name="outputtxt" file="output.geneBodyCoverage.txt"/>
+        </test>
+    </tests>
+    -->
+
+    <help><![CDATA[
 geneBody_coverage2.py
 +++++++++++++++++++++
 
@@ -50,11 +72,11 @@
     .. image:: http://dldcc-web.brc.bcm.edu/lilab/liguow/RSeQC/figure/geneBody_coverage.png
         :height: 600 px
         :width: 600 px
-        :scale: 80 %    
+        :scale: 80 %
 
 -----
 
-About RSeQC 
+About RSeQC
 +++++++++++
 
 The RSeQC_ package provides a number of useful modules that can comprehensively evaluate high throughput sequence data especially RNA-seq data. "Basic modules" quickly inspect sequence quality, nucleotide composition bias, PCR bias and GC bias, while "RNA-seq specific modules" investigate sequencing saturation status of both splicing junction detection and expression estimation, mapped reads clipping profile, mapped reads distribution, coverage uniformity over gene body, reproducibility, strand specificity and splice junction annotation.
@@ -65,7 +87,9 @@
 
 .. _RSeQC: http://rseqc.sourceforge.net/
 
-
+]]>
+    </help>
 
-    </help>
+    <expand macro="citations" />
+
 </tool>
diff -r 2e6190c29c54 -r 6b33e31bda10 infer_experiment.xml
--- a/infer_experiment.xml	Tue Apr 21 10:27:06 2015 -0400
+++ b/infer_experiment.xml	Thu Jul 16 17:43:43 2015 -0400
@@ -1,41 +1,53 @@
-<tool id="rseqc_infer_experiment" name="Infer Experiment" version="2.4">
+<tool id="rseqc_infer_experiment" name="Infer Experiment" version="2.4galaxy1">
     <description>speculates how RNA-seq were configured</description>
+
+    <macros>
+        <import>rseqc_macros.xml</import>
+    </macros>
+
     <requirements>
-        <requirement type="package" version="1.7.1">numpy</requirement>
-        <requirement type="package" version="2.4">rseqc</requirement>
+        <expand macro="requirement_package_numpy" />
+        <expand macro="requirement_package_rseqc" />
     </requirements>
-    <command>
-        infer_experiment.py -i $input -r $refgene 
-            #if $sample_size.boolean
-                -s $sample_size.size
-            #end if
+
+    <expand macro="stdio" />
+
+    <version_command><![CDATA[infer_experiment.py --version]]></version_command>
 
+    <command><![CDATA[
+        infer_experiment.py -i $input -r $refgene
+            --sample-size $sample_size
+            --mapq $mapq
             > $output
+            ]]>
     </command>
-    <stdio>
-        <exit_code range="1:" level="fatal" description="An error occured during execution, see stderr and stdout for more information" />
-        <regex match="[Ee]rror" source="both" description="An error occured during execution, see stderr and stdout for more information" />
-    </stdio>
+
     <inputs>
-        <param name="input" type="data" format="bam,sam" label="Input BAM/SAM file" />
-        <param name="refgene" type="data" format="bed" label="Reference gene model in bed format" />
-        <conditional name="sample_size">
-            <param name="boolean" type="boolean" label="Modify usable sampled reads" value="false" />
-            <when value="true">
-                <param name="size" type="integer" label="Number of usable sampled reads (default = 200000)" value="200000" />
-            </when>
-        </conditional>
+        <param name="input" type="data" format="bam,sam" label="Input BAM/SAM file" help="(--input-file)"/>
+        <param name="refgene" type="data" format="bed" label="Reference gene model in bed format" help="(--refgene)" />
+        <param name="sample_size" type="integer" label="Number of reads sampled from SAM/BAM file (default = 200000)" value="200000" help="(--sample-size)"/>
+        <param name="mapq" type="integer" label="Minimum mapping quality (default=30)" help="Minimum phred scale mapping quality to consider a read 'uniquely mapped' (--mapq)" value="30" />
     </inputs>
+
     <outputs>
         <data format="txt" name="output" />
     </outputs>
-    <help>
+
+    <tests>
+        <test>
+            <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam"/>
+            <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed"/>
+            <output name="output" file="output.infer_experiment.txt"/>
+        </test>
+    </tests>
+
+    <help><![CDATA[
 infer_experiment.py
 +++++++++++++++++++
 
 This program is used to speculate how RNA-seq sequencing were configured, especially how
 reads were stranded for strand-specific RNA-seq data, through comparing reads' mapping
-information to the underneath gene model. 
+information to the underneath gene model.
 
 
 Inputs
@@ -101,13 +113,13 @@
 **Example2** ::
 
     ============================================================
-    This is PairEnd Data 
+    This is PairEnd Data
 
     Fraction of reads explained by "1++,1--,2+-,2-+": 0.9644 ::
-    Fraction of reads explained by "1+-,1-+,2++,2--": 0.0356    
+    Fraction of reads explained by "1+-,1-+,2++,2--": 0.0356
     Fraction of reads explained by other combinations: 0.0000
     ============================================================
-    
+
 *Conclusion*: We can infer that this is a strand-specific RNA-seq data. strandness of read1 is consistent with that of gene model, while strandness of read2 is opposite to the strand of reference gene model.
 
 **Example3** ::
@@ -125,7 +137,7 @@
 
 -----
 
-About RSeQC 
+About RSeQC
 +++++++++++
 
 The RSeQC_ package provides a number of useful modules that can comprehensively evaluate high throughput sequence data especially RNA-seq data. "Basic modules" quickly inspect sequence quality, nucleotide composition bias, PCR bias and GC bias, while "RNA-seq specific modules" investigate sequencing saturation status of both splicing junction detection and expression estimation, mapped reads clipping profile, mapped reads distribution, coverage uniformity over gene body, reproducibility, strand specificity and splice junction annotation.
@@ -136,6 +148,9 @@
 
 .. _RSeQC: http://rseqc.sourceforge.net/
 
-
+]]>
     </help>
+
+    <expand macro="citations" />
+
 </tool>
diff -r 2e6190c29c54 -r 6b33e31bda10 inner_distance.xml
--- a/inner_distance.xml	Tue Apr 21 10:27:06 2015 -0400
+++ b/inner_distance.xml	Thu Jul 16 17:43:43 2015 -0400
@@ -1,58 +1,59 @@
-<tool id="rseqc_inner_distance" name="Inner Distance" version="2.4">
+<tool id="rseqc_inner_distance" name="Inner Distance" version="2.4galaxy1">
     <description>calculate the inner distance (or insert size) between two paired RNA reads</description>
+
+    <macros>
+        <import>rseqc_macros.xml</import>
+    </macros>
+
     <requirements>
-        <requirement type="package" version="3.0.3">R</requirement>
-        <requirement type="package" version="1.7.1">numpy</requirement>
-        <requirement type="package" version="2.4">rseqc</requirement>
+        <expand macro="requirement_package_r" />
+        <expand macro="requirement_package_numpy" />
+        <expand macro="requirement_package_rseqc" />
     </requirements>
-    <command>
-        inner_distance.py -i $input -o output -r $refgene
 
-            #if $bounds.hasLowerBound
-                -l $bounds.lowerBound
-            #end if
+    <expand macro="stdio" />
+
+    <version_command><![CDATA[inner_distance.py --version]]></version_command>
 
-            #if $bounds2.hasUpperBound
-                -u $bounds2.upperBound
-            #end if
-
-            #if $steps.step
-                -s $steps.stepSize
-            #end if
+    <command><![CDATA[
+        inner_distance.py -i $input -o output -r $refgene
+            --sample-size $sample_size
+            --lower-bound $lowerBound
+            --upper-bound $upperBound
+            --step $step
+            --mapq $mapq
+        ]]>
     </command>
-    <stdio>
-        <exit_code range="1:" level="fatal" description="An error occured during execution, see stderr and stdout for more information" />
-        <regex match="[Ee]rror" source="both" description="An error occured during execution, see stderr and stdout for more information" />
-    </stdio>
+
     <inputs>
-        <param name="input" type="data" format="bam,sam" label="input bam/sam file" />
-        <param name="refgene" type="data" format="bed" label="reference gene model" />
-        <conditional name="bounds">
-            <param name="hasLowerBound" type="boolean" label="Specify lower bound" value="false"/>
-            <when value="true">
-                <param name="lowerBound" type="integer" value="-250" label="Estimated Lower Bound (bp, default=-250)" />
-            </when>
-        </conditional>
-        <conditional name="bounds2">
-            <param name="hasUpperBound" type="boolean" label="Specify upper bound" value="false" />
-            <when value="true">
-                <param name="upperBound" type="integer" value="250" label="Estimated Upper Bound (bp, default=250)" />
-            </when>
-        </conditional>
-        <conditional name="steps">
-            <param name="step" type="boolean" label="Specify step size" value="false" />
-            <when value="true">
-                <param name="stepSize" type="integer" value="5" label="Step size (bp, default=5)" />
-            </when>
-        </conditional>
+        <param name="input" type="data" format="bam,sam" label="input bam/sam file" help="(--input-file)" />
+        <param name="refgene" type="data" format="bed" label="reference gene model" help="(--refgene)" />
+        <param name="sample_size" type="integer" label="Number of read-pairs used to estimate inner distance (default = 1000000)" value="1000000" help="(--sample-size)"/>
+        <param name="lowerBound" type="integer" value="-250" label="Lower bound (bp, default=-250)" help="Used for plotting histogram (--lower-bound)"/>
+        <param name="upperBound" type="integer" value="250" label="Upper bound (bp, default=250)" help="Used for plotting histogram (--upper-bound)"/>
+        <param name="step" type="integer" value="5" label="Step size of histogram (bp, default=5)" help="(--step)"/>
+        <param name="mapq" type="integer" label="Minimum mapping quality (default=30)" help="Minimum phred scale mapping quality to consider a read 'uniquely mapped' (--mapq)" value="30" />
     </inputs>
+
     <outputs>
         <data format="txt" name="outputtxt" from_work_dir="output.inner_distance.txt" label="${tool.name} on ${on_string} (Text)"/>
         <data format="txt" name="outputfreqtxt" from_work_dir="output.inner_distance_freq.txt" label="${tool.name} on ${on_string} (Freq Text)" />
         <data format="pdf" name="outputpdf" from_work_dir="output.inner_distance_plot.pdf" label="${tool.name} on ${on_string} (PDF)" />
         <data format="txt" name="outputr" from_work_dir="output.inner_distance_plot.r" label="${tool.name} on ${on_string} (R Script)" />
     </outputs>
-    <help>
+
+    <tests>
+        <test>
+            <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam"/>
+            <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed"/>
+            <output name="outputtxt" file="output.inner_distance.txt"/>
+            <output name="outputfreqtxt" file="output.inner_distance_freq.txt"/>
+            <output name="outputpdf" file="output.inner_distance_plot.pdf"/>
+            <output name="outputr" file="output.inner_distance_plot.r"/>
+        </test>
+    </tests>
+
+    <help><![CDATA[
 inner_distance.py
 +++++++++++++++++
 
@@ -63,10 +64,10 @@
 * if two paired reads map to the same exon: inner distance = D_size
 * if two paired reads map to different exons:inner distance = D_size - intron_size
 * if two paired reads map non-exonic region (such as intron and intergenic region): inner distance = D_size
-* The inner_distance might be a negative value if two fragments were overlapped. 
+* The inner_distance might be a negative value if two fragments were overlapped.
 
 NOTE: Not all read pairs were used to estimate the inner distance distribution. Those low
-quality, PCR duplication, multiple mapped reads were skipped. 
+quality, PCR duplication, multiple mapped reads were skipped.
 
 Inputs
 ++++++++++++++
@@ -102,12 +103,12 @@
 .. image:: http://rseqc.sourceforge.net/_images/inner_distance.png
    :height: 600 px
    :width: 600 px
-   :scale: 80 %                        
+   :scale: 80 %
 
 
 -----
 
-About RSeQC 
+About RSeQC
 +++++++++++
 
 The RSeQC_ package provides a number of useful modules that can comprehensively evaluate high throughput sequence data especially RNA-seq data. "Basic modules" quickly inspect sequence quality, nucleotide composition bias, PCR bias and GC bias, while "RNA-seq specific modules" investigate sequencing saturation status of both splicing junction detection and expression estimation, mapped reads clipping profile, mapped reads distribution, coverage uniformity over gene body, reproducibility, strand specificity and splice junction annotation.
@@ -118,6 +119,9 @@
 
 .. _RSeQC: http://rseqc.sourceforge.net/
 
-
+]]>
     </help>
+
+    <expand macro="citations" />
+
 </tool>
diff -r 2e6190c29c54 -r 6b33e31bda10 junction_annotation.xml
--- a/junction_annotation.xml	Tue Apr 21 10:27:06 2015 -0400
+++ b/junction_annotation.xml	Thu Jul 16 17:43:43 2015 -0400
@@ -1,38 +1,56 @@
-<tool id="rseqc_junction_annotation" name="Junction Annotation" version="2.4">
+<tool id="rseqc_junction_annotation" name="Junction Annotation" version="2.4galaxy1">
     <description>compares detected splice junctions to reference gene model</description>
+
+    <macros>
+        <import>rseqc_macros.xml</import>
+    </macros>
+
     <requirements>
-        <requirement type="package" version="3.0.3">R</requirement>
-        <requirement type="package" version="1.7.1">numpy</requirement>
-        <requirement type="package" version="2.4">rseqc</requirement>
+        <expand macro="requirement_package_r" />
+        <expand macro="requirement_package_numpy" />
+        <expand macro="requirement_package_rseqc" />
     </requirements>
-    <command>
-        junction_annotation.py 
-            -i $input -o output -r $refgene
-            #if $intron.hasIntron
-                -m $intron.min_Intron
-            #end if
+
+    <expand macro="stdio" />
+
+    <version_command><![CDATA[junction_annotation.py --version]]></version_command>
+
+    <command><![CDATA[
+        junction_annotation.py
+            --input-file $input
+            --refgene $refgene
+            --out-prefix output
+            --min-intron $min_intron
+            --mapq $mapq
+        ]]>
     </command>
-    <stdio>
-        <exit_code range="1:" level="fatal" description="An error occured during execution, see stderr and stdout for more information" />
-        <regex match="[Ee]rror" source="both" description="An error occured during execution, see stderr and stdout for more information" />
-    </stdio>
+
     <inputs>
-        <param name="input" type="data" format="bam,sam" label="input bam/sam file" />
-        <param name="refgene" type="data" format="bed" label="reference gene model" />
-        <conditional name="intron">
-            <param name="hasIntron" type="boolean" label="Specify minimum intron length" value="false"/>
-            <when value="true">
-                <param name="min_Intron" type="integer" value="50" label="Minimum intron length (bp, default=50)" />
-            </when>
-        </conditional>
+        <param name="input" type="data" format="bam,sam" label="input bam/sam file" help="(--input-file)"/>
+        <param name="refgene" type="data" format="bed" label="reference gene model" help="(--refgene)"/>
+        <param name="min_intron" type="integer" value="50" label="Minimum intron length (bp, default=50)" help="(--min-intron)" />
+        <param name="mapq" type="integer" label="Minimum mapping quality (default=30)" help="Minimum phred scale mapping quality to consider a read 'uniquely mapped' (--mapq)" value="30" />
     </inputs>
+
     <outputs>
         <data format="xls" name="outputxls" from_work_dir="output.junction.xls" label="${tool.name} on ${on_string} (XLS)"/>
         <data format="txt" name="outputr" from_work_dir="output.junction_plot.r" label="${tool.name} on ${on_string} (R Script)" />
         <data format="pdf" name="outputpdf" from_work_dir="output.splice_events.pdf" label="${tool.name} on ${on_string} (Splice Events PDF)"/>
         <data format="pdf" name="outputjpdf" from_work_dir="output.splice_junction.pdf" label="${tool.name} on ${on_string} (Splice Junction PDF)" />
     </outputs>
-    <help>
+
+    <tests>
+        <test>
+            <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam"/>
+            <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed"/>
+            <output name="outputxls" file="output.junction.xls"/>
+            <output name="outputr" file="output.junction_plot.r"/>
+            <output name="outputpdf" file="output.splice_events.pdf"/>
+            <output name="outputjpdf" file="output.splice_junction.pdf"/>
+        </test>
+    </tests>
+
+    <help><![CDATA[
 junction_annotation.py
 ++++++++++++++++++++++
 
@@ -40,15 +58,15 @@
 format, this program will compare detected splice junctions to reference gene model. splicing
 annotation is performed in two levels: splice event level and splice junction level.
 
-* splice event: An RNA read, especially long read, can be spliced 2 or more times, each time is called a splicing event; In this sense, 100 spliced reads can produce >= 100 splicing events. 
-* splice junction: multiple splicing events spanning the same intron can be consolidated into one splicing junction. 
+* splice event: An RNA read, especially long read, can be spliced 2 or more times, each time is called a splicing event; In this sense, 100 spliced reads can produce >= 100 splicing events.
+* splice junction: multiple splicing events spanning the same intron can be consolidated into one splicing junction.
 
 All detected junctions can be grouped to 3 exclusive categories:
 
-1. Annotated: The junction is part of the gene model. Both splice sites, 5' splice site 
-   (5'SS) and 3'splice site (3'SS) can be annotated by reference gene model. 
-2. complete_novel: Complete new junction. Neither of the two splice sites cannot be annotated by gene model 
-3. partial_novel: One of the splice site (5'SS or 3'SS) is new, while the other splice site is annotated (known) 
+1. Annotated: The junction is part of the gene model. Both splice sites, 5' splice site
+   (5'SS) and 3'splice site (3'SS) can be annotated by reference gene model.
+2. complete_novel: Complete new junction. Neither of the two splice sites cannot be annotated by gene model
+3. partial_novel: One of the splice site (5'SS or 3'SS) is new, while the other splice site is annotated (known)
 
 Inputs
 ++++++++++++++
@@ -79,11 +97,11 @@
 .. image:: http://rseqc.sourceforge.net/_images/junction.png
    :height: 400 px
    :width: 850 px
-   :scale: 80 %      
+   :scale: 80 %
 
 -----
 
-About RSeQC 
+About RSeQC
 +++++++++++
 
 The RSeQC_ package provides a number of useful modules that can comprehensively evaluate high throughput sequence data especially RNA-seq data. "Basic modules" quickly inspect sequence quality, nucleotide composition bias, PCR bias and GC bias, while "RNA-seq specific modules" investigate sequencing saturation status of both splicing junction detection and expression estimation, mapped reads clipping profile, mapped reads distribution, coverage uniformity over gene body, reproducibility, strand specificity and splice junction annotation.
@@ -93,9 +111,9 @@
 .. image:: http://rseqc.sourceforge.net/_static/logo.png
 
 .. _RSeQC: http://rseqc.sourceforge.net/
-
-
+]]>
+    </help>
 
+    <expand macro="citations" />
 
-    </help>
 </tool>
diff -r 2e6190c29c54 -r 6b33e31bda10 junction_saturation.xml
--- a/junction_saturation.xml	Tue Apr 21 10:27:06 2015 -0400
+++ b/junction_saturation.xml	Thu Jul 16 17:43:43 2015 -0400
@@ -1,40 +1,72 @@
-<tool id="rseqc_junction_saturation" name="Junction Saturation" version="2.4">
+<tool id="rseqc_junction_saturation" name="Junction Saturation" version="2.4galaxy1">
     <description>detects splice junctions from each subset and compares them to reference gene model</description>
+
+    <macros>
+        <import>rseqc_macros.xml</import>
+    </macros>
+
     <requirements>
-        <requirement type="package" version="3.0.3">R</requirement>
-        <requirement type="package" version="1.7.1">numpy</requirement>
-        <requirement type="package" version="2.4">rseqc</requirement>
+        <expand macro="requirement_package_r" />
+        <expand macro="requirement_package_numpy" />
+        <expand macro="requirement_package_rseqc" />
     </requirements>
-    <command> junction_saturation.py -i $input -o output -r $refgene -m $intronSize -v $minSplice
+
+    <expand macro="stdio" />
+
+    <version_command><![CDATA[junction_saturation.py --version]]></version_command>
 
+    <command><![CDATA[
+        junction_saturation.py
+            --input-file $input
+            --refgene $refgene
+            --out-prefix output
+            --min-intron $min_intron
+            --min-coverage $min_coverage
+            --mapq $mapq
         #if $percentiles.specifyPercentiles
-            -l $percentiles.lowBound -u $percentiles.upBound -s $percentiles.percentileStep
+            --percentile-floor $percentiles.lowBound
+            --percentile-ceiling $percentiles.upBound
+            --percentile-step $percentiles.percentileStep
         #end if
-
+        ]]>
     </command>
-    <stdio>
-        <exit_code range="1:" level="fatal" description="An error occured during execution, see stderr and stdout for more information" />
-        <regex match="[Ee]rror" source="both" description="An error occured during execution, see stderr and stdout for more information" />
-    </stdio>
+
     <inputs>
-        <param name="input" type="data" format="bam,sam" label="input bam/sam file" />
-        <param name="refgene" type="data" format="bed" label="reference gene model" />
-        <param name="intronSize" type="integer" label="Minimum intron size (bp, default=50)" value="50"/>
-        <param name="minSplice" type="integer" label="Minimum coverage (default=1)" value="1" />
+        <param name="input" type="data" format="bam,sam" label="input bam/sam file" help="(--input-file)"/>
+        <param name="refgene" type="data" format="bed" label="reference gene model" help="(--refgene)"/>
+        <param name="min_intron" type="integer" value="50" label="Minimum intron length (bp, default=50)" help="(--min-intron)" />
+        <param name="min_coverage" type="integer" label="Minimum number of supporting reads to call a junction (default=1)" value="1" help="(--min-coverage)" />
+        <param name="mapq" type="integer" label="Minimum mapping quality (default=30)" help="Minimum phred scale mapping quality to consider a read 'uniquely mapped' (--mapq)" value="30" />
         <conditional name="percentiles">
             <param name="specifyPercentiles" type="boolean" label="Specify sampling bounds and frequency" value="false"/>
             <when value="true">
-                <param name="lowBound" type="integer" value="5" label="Lower Bound Sampling Frequency (bp, default=5)" />
-                <param name="upBound" type="integer" value="100" label="Upper Bound Sampling Frequency (bp, default=100)" />
-                <param name="percentileStep" type="integer" value="5" label="Sampling increment (default=5)" />
+                <param name="lowBound" type="integer" value="5" label="Lower Bound Sampling Frequency (bp, default=5)" help="(--percentile-floor)">
+                    <validator type="in_range" min="0" max="100" />
+                </param>
+                <param name="upBound" type="integer" value="100" label="Upper Bound Sampling Frequency (bp, default=100)" help="(--percentile-ceiling)">
+                    <validator type="in_range" min="0" max="100" />
+                </param>
+                <param name="percentileStep" type="integer" value="5" label="Sampling increment (default=5)" help="(--percentile-step)">
+                    <validator type="in_range" min="0" max="100" />
+                </param>
             </when>
         </conditional>
     </inputs>
+
     <outputs>
         <data format="txt" name="outputr" from_work_dir="output.junctionSaturation_plot.r" label="${tool.name} on ${on_string} (R Script)"/>
         <data format="pdf" name="outputpdf" from_work_dir="output.junctionSaturation_plot.pdf" label="${tool.name} on ${on_string} (PDF)"/>
     </outputs>
-    <help>
+
+    <tests>
+        <test>
+            <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam"/>
+            <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed"/>
+            <output name="outputr" file="output.junctionSaturation_plot.r"/>
+        </test>
+    </tests>
+
+    <help><![CDATA[
 junction_saturation.py
 ++++++++++++++++++++++
 
@@ -46,7 +78,7 @@
 alternative splicing analysis is problematic because low abundance splice junctions are
 missing. This module checks for saturation by resampling 5%, 10%, 15%, ..., 95% of total
 alignments from BAM or SAM file, and then detects splice junctions from each subset and
-compares them to reference gene model. 
+compares them to reference gene model.
 
 Inputs
 ++++++++++++++
@@ -75,14 +107,14 @@
 .. image:: http://rseqc.sourceforge.net/_images/junction_saturation.png
    :height: 600 px
    :width: 600 px
-   :scale: 80 %    
+   :scale: 80 %
 
 In this example, current sequencing depth is almost saturated for "known junction" (red line) detection because the number of "known junction" reaches a plateau. In other words, nearly all "known junctions" (expressed in this particular tissue) have already been detected, and continue sequencing will not detect additional "known junction" and will only increase junction coverage (i.e. junction covered by more reads). While current sequencing depth is not saturated for novel junctions (green).
 
 
 -----
 
-About RSeQC 
+About RSeQC
 +++++++++++
 
 The RSeQC_ package provides a number of useful modules that can comprehensively evaluate high throughput sequence data especially RNA-seq data. "Basic modules" quickly inspect sequence quality, nucleotide composition bias, PCR bias and GC bias, while "RNA-seq specific modules" investigate sequencing saturation status of both splicing junction detection and expression estimation, mapped reads clipping profile, mapped reads distribution, coverage uniformity over gene body, reproducibility, strand specificity and splice junction annotation.
@@ -92,8 +124,9 @@
 .. image:: http://rseqc.sourceforge.net/_static/logo.png
 
 .. _RSeQC: http://rseqc.sourceforge.net/
-
-
+]]>
+    </help>
 
-    </help>
+    <expand macro="citations" />
+
 </tool>
diff -r 2e6190c29c54 -r 6b33e31bda10 read_GC.xml
--- a/read_GC.xml	Tue Apr 21 10:27:06 2015 -0400
+++ b/read_GC.xml	Thu Jul 16 17:43:43 2015 -0400
@@ -1,26 +1,48 @@
-<tool id="rseqc_read_GC" name="Read GC" version="2.4">
+<tool id="rseqc_read_GC" name="Read GC" version="2.4galaxy1">
     <description>determines GC% and read count</description>
+
+    <macros>
+        <import>rseqc_macros.xml</import>
+    </macros>
+
     <requirements>
-        <requirement type="package" version="3.0.3">R</requirement>
-        <requirement type="package" version="1.7.1">numpy</requirement>
-        <requirement type="package" version="2.4">rseqc</requirement>
+        <expand macro="requirement_package_r" />
+        <expand macro="requirement_package_numpy" />
+        <expand macro="requirement_package_rseqc" />
     </requirements>
-    <command>
-        read_GC.py -i $input -o output
+
+    <expand macro="stdio" />
+
+    <version_command><![CDATA[read_GC.py --version]]></version_command>
+
+    <command><![CDATA[
+        read_GC.py
+            --input-file $input
+            --out-prefix output
+            --mapq $mapq
+        ]]>
     </command>
-    <stdio>
-        <exit_code range="1:" level="fatal" description="An error occured during execution, see stderr and stdout for more information" />
-        <regex match="[Ee]rror" source="both" description="An error occured during execution, see stderr and stdout for more information" />
-    </stdio>
+
     <inputs>
-        <param name="input" type="data" format="bam,sam" label="input bam/sam file" />
+        <param name="input" type="data" format="bam,sam" label="input bam/sam file" help="(--input-file)"/>
+        <param name="mapq" type="integer" label="Minimum mapping quality (default=30)" help="Minimum phred scale mapping quality to consider a read 'uniquely mapped' (--mapq)" value="30" />
     </inputs>
+
     <outputs>
         <data format="xls" name="outputxls" from_work_dir="output.GC.xls" label="${tool.name} on ${on_string} (XLS)"/>
         <data format="txt" name="outputr" from_work_dir="output.GC_plot.r" label="${tool.name} on ${on_string} (R Script)" />
         <data format="pdf" name="outputpdf" from_work_dir="output.GC_plot.pdf" label="${tool.name} on ${on_string} (PDF)" />
     </outputs>
-    <help>
+
+    <tests>
+        <test>
+            <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam"/>
+            <output name="outputxls" file="output.GC.xls"/>
+            <output name="outputr" file="output.GC_plot.r"/>
+        </test>
+    </tests>
+
+    <help><![CDATA[
 read_GC.py
 ++++++++++
 
@@ -36,16 +58,16 @@
 
 1. output.GC.xls: Two column, plain text file, first column is GC%, second column is read count
 2. output.GC_plot.r: R script to generate pdf file.
-3. output.GC_plot.pdf: graphical output generated from R script. 
+3. output.GC_plot.pdf: graphical output generated from R script.
 
-.. image:: http://rseqc.sourceforge.net/_images/read_gc.png 
+.. image:: http://rseqc.sourceforge.net/_images/read_gc.png
    :height: 600 px
    :width: 600 px
-   :scale: 80 %    
+   :scale: 80 %
 
 -----
 
-About RSeQC 
+About RSeQC
 +++++++++++
 
 The RSeQC_ package provides a number of useful modules that can comprehensively evaluate high throughput sequence data especially RNA-seq data. "Basic modules" quickly inspect sequence quality, nucleotide composition bias, PCR bias and GC bias, while "RNA-seq specific modules" investigate sequencing saturation status of both splicing junction detection and expression estimation, mapped reads clipping profile, mapped reads distribution, coverage uniformity over gene body, reproducibility, strand specificity and splice junction annotation.
@@ -55,7 +77,9 @@
 .. image:: http://rseqc.sourceforge.net/_static/logo.png
 
 .. _RSeQC: http://rseqc.sourceforge.net/
-
+]]>
+    </help>
 
-    </help>
+    <expand macro="citations" />
+
 </tool>
diff -r 2e6190c29c54 -r 6b33e31bda10 read_NVC.xml
--- a/read_NVC.xml	Tue Apr 21 10:27:06 2015 -0400
+++ b/read_NVC.xml	Thu Jul 16 17:43:43 2015 -0400
@@ -1,27 +1,49 @@
-<tool id="rseqc_read_NVC" name="Read NVC" version="2.4">
+<tool id="rseqc_read_NVC" name="Read NVC" version="2.4galaxy1">
     <description>to check the nucleotide composition bias</description>
+
+    <macros>
+        <import>rseqc_macros.xml</import>
+    </macros>
+
     <requirements>
-        <requirement type="package" version="3.0.3">R</requirement>
-        <requirement type="package" version="1.7.1">numpy</requirement>
-        <requirement type="package" version="2.4">rseqc</requirement>
+        <expand macro="requirement_package_r" />
+        <expand macro="requirement_package_numpy" />
+        <expand macro="requirement_package_rseqc" />
     </requirements>
+
+    <expand macro="stdio" />
+
+    <version_command><![CDATA[read_NVC.py --version]]></version_command>
+
     <command>
-        read_NVC.py -i $input -o output $nx
+        read_NVC.py
+            --input-file $input
+            --out-prefix output
+            $nx
+            --mapq $mapq
     </command>
-    <stdio>
-        <exit_code range="1:" level="fatal" description="An error occured during execution, see stderr and stdout for more information" />
-        <regex match="[Ee]rror" source="both" description="An error occured during execution, see stderr and stdout for more information" />
-    </stdio>
+
     <inputs>
-        <param name="input" type="data" format="bam,sam" label="input bam/sam file" />
-        <param name="nx" type="boolean" value="false" truevalue="-x" falsevalue="" label="Include N,X in NVC plot"/>
+        <param name="input" type="data" format="bam,sam" label="input bam/sam file" help="(--input-file)"/>
+        <param name="nx" type="boolean" value="false" truevalue="--nx" falsevalue="" label="Include N,X in NVC plot" help="(--nx)"/>
+        <param name="mapq" type="integer" label="Minimum mapping quality (default=30)" help="Minimum phred scale mapping quality to consider a read 'uniquely mapped' (--mapq)" value="30" />
     </inputs>
+
     <outputs>
         <data format="xls" name="outputxls" from_work_dir="output.NVC.xls" label="${tool.name} on ${on_string} (XLS)" />
         <data format="txt" name="outputr" from_work_dir="output.NVC_plot.r" label="${tool.name} on ${on_string} (R Script)" />
         <data format="pdf" name="outputpdf" from_work_dir="output.NVC_plot.pdf" label="${tool.name} on ${on_string} (PDF)" />
     </outputs>
-    <help>
+
+    <tests>
+        <test>
+            <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam"/>
+            <output name="outputxls" file="output.NVC.xls"/>
+            <output name="outputr" file="output.NVC_plot.r"/>
+        </test>
+    </tests>
+
+    <help><![CDATA[
 read_NVC.py
 +++++++++++
 
@@ -30,7 +52,7 @@
 examined by NVC (Nucleotide versus cycle) plot. NVC plot is generated by overlaying all
 reads together, then calculating nucleotide composition for each position of read
 (or each sequencing cycle). In ideal condition (genome is random and RNA-seq reads is
-randomly sampled from genome), we expect A%=C%=G%=T%=25% at each position of reads. 
+randomly sampled from genome), we expect A%=C%=G%=T%=25% at each position of reads.
 
 NOTE: this program expect a fixed read length
 
@@ -57,11 +79,11 @@
 .. image:: http://rseqc.sourceforge.net/_images/NVC_plot.png
    :height: 600 px
    :width: 600 px
-   :scale: 80 %    
+   :scale: 80 %
 
 -----
 
-About RSeQC 
+About RSeQC
 +++++++++++
 
 The RSeQC_ package provides a number of useful modules that can comprehensively evaluate high throughput sequence data especially RNA-seq data. "Basic modules" quickly inspect sequence quality, nucleotide composition bias, PCR bias and GC bias, while "RNA-seq specific modules" investigate sequencing saturation status of both splicing junction detection and expression estimation, mapped reads clipping profile, mapped reads distribution, coverage uniformity over gene body, reproducibility, strand specificity and splice junction annotation.
@@ -71,7 +93,9 @@
 .. image:: http://rseqc.sourceforge.net/_static/logo.png
 
 .. _RSeQC: http://rseqc.sourceforge.net/
-
+]]>
+    </help>
 
-    </help>
+    <expand macro="citations" />
+
 </tool>
diff -r 2e6190c29c54 -r 6b33e31bda10 read_distribution.xml
--- a/read_distribution.xml	Tue Apr 21 10:27:06 2015 -0400
+++ b/read_distribution.xml	Thu Jul 16 17:43:43 2015 -0400
@@ -1,24 +1,42 @@
-<tool id="rseqc_read_distribution" name="Read Distribution" version="2.4">
+<tool id="rseqc_read_distribution" name="Read Distribution" version="2.4galaxy1">
     <description>calculates how mapped reads were distributed over genome feature</description>
+
+    <macros>
+        <import>rseqc_macros.xml</import>
+    </macros>
+
     <requirements>
-        <requirement type="package" version="1.7.1">numpy</requirement>
-        <requirement type="package" version="2.4">rseqc</requirement>
+        <expand macro="requirement_package_numpy" />
+        <expand macro="requirement_package_rseqc" />
     </requirements>
-    <command>
+
+    <expand macro="stdio" />
+
+    <version_command><![CDATA[read_distribution.py --version]]></version_command>
+
+    <command><![CDATA[
         read_distribution.py -i $input -r $refgene > $output
+        ]]>
     </command>
-    <stdio>
-        <exit_code range="1:" level="fatal" description="An error occured during execution, see stderr and stdout for more information" />
-        <regex match="[Ee]rror" source="both" description="An error occured during execution, see stderr and stdout for more information" />
-    </stdio>
+
     <inputs>
-        <param name="input" type="data" format="bam,sam" label="input bam/sam file" />
-        <param name="refgene" type="data" format="bed" label="reference gene model" />
+        <param name="input" type="data" format="bam,sam" label="input bam/sam file" help="(--input-file)"/>
+        <param name="refgene" type="data" format="bed" label="reference gene model" help="(--refgene)"/>
     </inputs>
+
     <outputs>
         <data format="txt" name="output" />
     </outputs>
-    <help>
+
+    <tests>
+        <test>
+            <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam"/>
+            <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed"/>
+            <output name="output" file="output.read_distribution.txt"/>
+        </test>
+    </tests>
+
+    <help><![CDATA[
 read_distribution.py
 ++++++++++++++++++++
 
@@ -39,7 +57,7 @@
 
 * hit to intergenic regions that beyond region starting from TSS upstream 10Kb to TES downstream 10Kb.
 * hit to regions covered by both 5'UTR and 3' UTR. This is possible when two head-to-tail transcripts are overlapped in UTR regions.
-* hit to regions covered by both TSS upstream 10Kb and TES downstream 10Kb. 
+* hit to regions covered by both TSS upstream 10Kb and TES downstream 10Kb.
 
 
 Inputs
@@ -57,23 +75,23 @@
 Output:
 
 ===============     ============        ===========         ===========
-Group               Total_bases         Tag_count           Tags/Kb    
+Group               Total_bases         Tag_count           Tags/Kb
 ===============     ============        ===========         ===========
-CDS_Exons           33302033            20002271            600.63     
-5'UTR_Exons         21717577            4408991             203.01     
-3'UTR_Exons         15347845            3643326             237.38     
-Introns             1132597354          6325392             5.58       
-TSS_up_1kb          17957047            215331              11.99      
-TSS_up_5kb          81621382            392296              4.81       
-TSS_up_10kb         149730983           769231              5.14       
-TES_down_1kb        18298543            266161              14.55      
-TES_down_5kb        78900674            729997              9.25       
-TES_down_10kb       140361190           896882              6.39       
+CDS_Exons           33302033            20002271            600.63
+5'UTR_Exons         21717577            4408991             203.01
+3'UTR_Exons         15347845            3643326             237.38
+Introns             1132597354          6325392             5.58
+TSS_up_1kb          17957047            215331              11.99
+TSS_up_5kb          81621382            392296              4.81
+TSS_up_10kb         149730983           769231              5.14
+TES_down_1kb        18298543            266161              14.55
+TES_down_5kb        78900674            729997              9.25
+TES_down_10kb       140361190           896882              6.39
 ===============     ============        ===========         ===========
 
 -----
 
-About RSeQC 
+About RSeQC
 +++++++++++
 
 The RSeQC_ package provides a number of useful modules that can comprehensively evaluate high throughput sequence data especially RNA-seq data. "Basic modules" quickly inspect sequence quality, nucleotide composition bias, PCR bias and GC bias, while "RNA-seq specific modules" investigate sequencing saturation status of both splicing junction detection and expression estimation, mapped reads clipping profile, mapped reads distribution, coverage uniformity over gene body, reproducibility, strand specificity and splice junction annotation.
@@ -83,8 +101,9 @@
 .. image:: http://rseqc.sourceforge.net/_static/logo.png
 
 .. _RSeQC: http://rseqc.sourceforge.net/
-
-
+]]>
+    </help>
 
-    </help>
+    <expand macro="citations" />
+
 </tool>
diff -r 2e6190c29c54 -r 6b33e31bda10 read_duplication.xml
--- a/read_duplication.xml	Tue Apr 21 10:27:06 2015 -0400
+++ b/read_duplication.xml	Thu Jul 16 17:43:43 2015 -0400
@@ -1,35 +1,54 @@
-<tool id="rseqc_read_duplication" name="Read Duplication" version="2.4">
+<tool id="rseqc_read_duplication" name="Read Duplication" version="2.4galaxy1">
     <description>determines reads duplication rate with sequence-based and mapping-based strategies</description>
+
+    <macros>
+        <import>rseqc_macros.xml</import>
+    </macros>
+
     <requirements>
-        <requirement type="package" version="3.0.3">R</requirement>
-        <requirement type="package" version="1.7.1">numpy</requirement>
-        <requirement type="package" version="2.4">rseqc</requirement>
+        <expand macro="requirement_package_r" />
+        <expand macro="requirement_package_numpy" />
+        <expand macro="requirement_package_rseqc" />
     </requirements>
-    <command>
+
+    <expand macro="stdio" />
+
+    <version_command><![CDATA[read_duplication.py --version]]></version_command>
+
+    <command><![CDATA[
         read_duplication.py -i $input -o output -u $upLimit
+        ]]>
     </command>
-    <stdio>
-        <exit_code range="1:" level="fatal" description="An error occured during execution, see stderr and stdout for more information" />
-        <regex match="[Ee]rror" source="both" description="An error occured during execution, see stderr and stdout for more information" />
-    </stdio>
+
     <inputs>
-        <param name="input" type="data" format="bam,sam" label="input bam/sam file" />
-        <param name="upLimit" type="integer" label="Upper Limit of Plotted Duplicated Times (default=500)" value="500" />
+        <param name="input" type="data" format="bam,sam" label="input bam/sam file" help="(--input-file)"/>
+        <param name="upLimit" type="integer" label="Upper Limit of Plotted Duplicated Times (default=500)" value="500" help="(--up-limit)"/>
     </inputs>
+
     <outputs>
-        <data format="xls" name="outputxls" from_work_dir="output.dup.pos.DupRate.xls" label="${tool.name} on ${on_string} (Position XLS)"/>
-        <data format="xls" name="outputseqxls" from_work_dir="output.dup.seq.DupRate.xls" label="${tool.name} on ${on_string} (Sequence XLS)"/>
+        <data format="xls" name="outputxls" from_work_dir="output.pos.DupRate.xls" label="${tool.name} on ${on_string} (Position XLS)"/>
+        <data format="xls" name="outputseqxls" from_work_dir="output.seq.DupRate.xls" label="${tool.name} on ${on_string} (Sequence XLS)"/>
         <data format="txt" name="outputr" from_work_dir="output.DupRate_plot.r" label="${tool.name} on ${on_string} (R Script)" />
         <data format="pdf" name="outputpdf" from_work_dir="output.DupRate_plot.pdf" label="${tool.name} on ${on_string} (PDF)" />
     </outputs>
-    <help>
+
+    <tests>
+        <test>
+            <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam"/>
+            <output name="outputxls" file="output.pos.DupRate.xls"/>
+            <output name="outputseqxls" file="output.seq.DupRate.xls"/>
+            <output name="outputr" file="output.DupRate_plot.r"/>
+        </test>
+    </tests>
+
+    <help><![CDATA[
 read_duplication.py
 +++++++++++++++++++
 
-Two strategies were used to determine reads duplication rate: 
+Two strategies were used to determine reads duplication rate:
 
-* Sequence based: reads with exactly the same sequence content are regarded as duplicated reads. 
-* Mapping based: reads mapped to the same genomic location are regarded as duplicated reads. For splice reads, reads mapped to the same starting position and splice the same way are regarded as duplicated reads. 
+* Sequence based: reads with exactly the same sequence content are regarded as duplicated reads.
+* Mapping based: reads mapped to the same genomic location are regarded as duplicated reads. For splice reads, reads mapped to the same starting position and splice the same way are regarded as duplicated reads.
 
 Inputs
 ++++++++++++++
@@ -51,11 +70,11 @@
 .. image:: http://rseqc.sourceforge.net/_images/duplicate.png
    :height: 600 px
    :width: 600 px
-   :scale: 80 %    
+   :scale: 80 %
 
 -----
 
-About RSeQC 
+About RSeQC
 +++++++++++
 
 The RSeQC_ package provides a number of useful modules that can comprehensively evaluate high throughput sequence data especially RNA-seq data. "Basic modules" quickly inspect sequence quality, nucleotide composition bias, PCR bias and GC bias, while "RNA-seq specific modules" investigate sequencing saturation status of both splicing junction detection and expression estimation, mapped reads clipping profile, mapped reads distribution, coverage uniformity over gene body, reproducibility, strand specificity and splice junction annotation.
@@ -65,7 +84,9 @@
 .. image:: http://rseqc.sourceforge.net/_static/logo.png
 
 .. _RSeQC: http://rseqc.sourceforge.net/
-
+]]>
+    </help>
 
-    </help>
+    <expand macro="citations" />
+
 </tool>
diff -r 2e6190c29c54 -r 6b33e31bda10 read_quality.xml
--- a/read_quality.xml	Tue Apr 21 10:27:06 2015 -0400
+++ b/read_quality.xml	Thu Jul 16 17:43:43 2015 -0400
@@ -1,27 +1,53 @@
-<tool id="rseqc_read_quality" name="Read Quality" version="2.4">
+<tool id="rseqc_read_quality" name="Read Quality" version="2.4galaxy1">
     <description>determines Phred quality score</description>
+
+    <macros>
+        <import>rseqc_macros.xml</import>
+    </macros>
+
     <requirements>
-        <requirement type="package" version="3.0.3">R</requirement>
-        <requirement type="package" version="1.7.1">numpy</requirement>
-        <requirement type="package" version="2.4">rseqc</requirement>
+        <expand macro="requirement_package_r" />
+        <expand macro="requirement_package_numpy" />
+        <expand macro="requirement_package_rseqc" />
     </requirements>
-    <command>
-        read_quality.py -i $input -o output -r $reduce
+
+    <expand macro="stdio" />
+
+    <version_command><![CDATA[read_quality.py --version]]></version_command>
+
+    <command><![CDATA[
+        read_quality.py
+            --input-file $input
+            --out-prefix output
+            -r $reduce
+            --mapq $mapq
+        ]]>
     </command>
-    <stdio>
-        <exit_code range="1:" level="fatal" description="An error occured during execution, see stderr and stdout for more information" />
-        <regex match="[Ee]rror" source="both" description="An error occured during execution, see stderr and stdout for more information" />
-    </stdio>
+
     <inputs>
-        <param name="input" type="data" format="bam,sam" label="input bam/sam file" />
-        <param name="reduce" type="integer" label="Ignore Phred scores less than this amount (only applies to 'boxplot', default=1000)" value="1000" />
+        <param name="input" type="data" format="bam,sam" label="input bam/sam file" help="(--input-file)"/>
+        <param name="reduce" type="integer" label="Ignore Phred scores less than this amount (only applies to 'boxplot', default=1000)" value="1000" help="(--reduce)"/>
+        <param name="mapq" type="integer" label="Minimum mapping quality (default=30)" help="Minimum phred scale mapping quality to consider a read 'uniquely mapped' (--mapq)" value="30" />
     </inputs>
+
     <outputs>
         <data format="txt" name="outputr" from_work_dir="output.qual.r" label="${tool.name} on ${on_string} (R Script)" />
-        <data format="pdf" name="outputpdf" from_work_dir="output.qual.heatmap.pdf" label="${tool.name} on ${on_string} (Heatmap PDF)" />
-        <data format="pdf" name="outputpdf" from_work_dir="output.qual.boxplot.pdf" label="${tool.name} on ${on_string} (Boxplot PDF)" />
+        <data format="pdf" name="outputheatpdf" from_work_dir="output.qual.heatmap.pdf" label="${tool.name} on ${on_string} (Heatmap PDF)" />
+        <data format="pdf" name="outputboxpdf" from_work_dir="output.qual.boxplot.pdf" label="${tool.name} on ${on_string} (Boxplot PDF)" />
     </outputs>
-    <help>
+
+    <!-- Unable to succefully run this script with test data
+    <tests>
+        <test>
+            <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bigwig"/>
+            <output name="outputr" file="output.qual.r"/>
+            <output name="outputheatpdf" file="output.qual.heatmap.pdf"/>
+            <output name="outputboxpdf" file="output.qual.boxplot.pdf"/>
+        </test>
+    </tests>
+    -->
+
+    <help><![CDATA[
 read_quality.py
 +++++++++++++++
 
@@ -30,7 +56,7 @@
 returns an integer representing the Unicode code point of the character when the argument
 is a unicode object, for example, ord('a') returns 97. Phred quality score is widely used
 to measure "reliability" of base-calling, for example, phred quality score of 20 means
-there is 1/100 chance that the base-calling is wrong, phred quality score of 30 means there 
+there is 1/100 chance that the base-calling is wrong, phred quality score of 30 means there
 is 1/1000 chance that the base-calling is wrong. In general: Phred quality score = -10xlog(10)P,
 here P is probability that base-calling is wrong.
 
@@ -51,18 +77,18 @@
     .. image:: http://rseqc.sourceforge.net/_images/36mer.qual.plot.png
         :height: 600 px
         :width: 600 px
-        :scale: 80 %    
+        :scale: 80 %
 3. output.qual.heatmap.pdf
     .. image:: http://rseqc.sourceforge.net/_images/36mer.qual.heatmap.png
         :height: 600 px
         :width: 600 px
-        :scale: 80 %    
+        :scale: 80 %
 
 Heatmap: use different color to represent nucleotide density ("blue"=low density,"orange"=median density,"red"=high density")
 
 -----
 
-About RSeQC 
+About RSeQC
 +++++++++++
 
 The RSeQC_ package provides a number of useful modules that can comprehensively evaluate high throughput sequence data especially RNA-seq data. "Basic modules" quickly inspect sequence quality, nucleotide composition bias, PCR bias and GC bias, while "RNA-seq specific modules" investigate sequencing saturation status of both splicing junction detection and expression estimation, mapped reads clipping profile, mapped reads distribution, coverage uniformity over gene body, reproducibility, strand specificity and splice junction annotation.
@@ -72,7 +98,9 @@
 .. image:: http://rseqc.sourceforge.net/_static/logo.png
 
 .. _RSeQC: http://rseqc.sourceforge.net/
-
+]]>
+    </help>
 
-    </help>
+    <expand macro="citations" />
+
 </tool>
diff -r 2e6190c29c54 -r 6b33e31bda10 rseqc_macros.xml
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/rseqc_macros.xml	Thu Jul 16 17:43:43 2015 -0400
@@ -0,0 +1,42 @@
+<macros>
+
+    <xml name="requirement_package_r"><requirement type="package" version="3.0.3">R</requirement></xml>
+    <xml name="requirement_package_numpy"><requirement type="package" version="1.7.1">numpy</requirement></xml>
+    <xml name="requirement_package_rseqc"><requirement type="package" version="2.4">rseqc</requirement></xml>
+
+    <xml name="stdio">
+        <stdio>
+            <exit_code range="1:" level="fatal" description="An error occured during execution, see stderr and stdout for more information" />
+            <regex match="[Ee]rror" source="both" description="An error occured during execution, see stderr and stdout for more information" />
+        </stdio>
+    </xml>
+
+    <xml name="citations">
+        <citations>
+            <citation type="bibtex">
+    @article{wang_rseqc:_2012,
+        title = {{RSeQC}: quality control of {RNA}-seq experiments},
+        volume = {28},
+        issn = {1367-4803, 1460-2059},
+        shorttitle = {{RSeQC}},
+        url = {http://bioinformatics.oxfordjournals.org/content/28/16/2184},
+        doi = {10.1093/bioinformatics/bts356},
+        abstract = {Motivation: RNA-seq has been extensively used for transcriptome study. Quality control (QC) is critical to ensure that RNA-seq data are of high quality and suitable for subsequent analyses. However, QC is a time-consuming and complex task, due to the massive size and versatile nature of RNA-seq data. Therefore, a convenient and comprehensive QC tool to assess RNA-seq quality is sorely needed.
+    Results: We developed the RSeQC package to comprehensively evaluate different aspects of RNA-seq experiments, such as sequence quality, GC bias, polymerase chain reaction bias, nucleotide composition bias, sequencing depth, strand specificity, coverage uniformity and read distribution over the genome structure. RSeQC takes both SAM and BAM files as input, which can be produced by most RNA-seq mapping tools as well as BED files, which are widely used for gene models. Most modules in RSeQC take advantage of R scripts for visualization, and they are notably efficient in dealing with large BAM/SAM files containing hundreds of millions of alignments.
+    Availability and implementation: RSeQC is written in Python and C. Source code and a comprehensive user's manual are freely available at: http://code.google.com/p/rseqc/.
+    Contact: WL1\{at\}bcm.edu
+    Supplementary Information: Supplementary data are available at Bioinformatics online.},
+        language = {en},
+        number = {16},
+        urldate = {2015-06-30},
+        journal = {Bioinformatics},
+        author = {Wang, Liguo and Wang, Shengqin and Li, Wei},
+        month = aug,
+        year = {2012},
+        pmid = {22743226},
+        pages = {2184--2185},
+    }
+            </citation>
+        </citations>
+    </xml>
+</macros>
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/bamstats.txt
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/bamstats.txt	Thu Jul 16 17:43:43 2015 -0400
@@ -0,0 +1,23 @@
+Load BAM file ...  Done
+
+#==================================================
+#All numbers are READ count
+#==================================================
+
+Total records:                          40
+
+QC failed:                              0
+Optical/PCR duplicate:                  0
+Non primary hits                        0
+Unmapped reads:                         0
+mapq < mapq_cut (non-unique):           0
+
+mapq >= mapq_cut (unique):              40
+Read-1:                                 20
+Read-2:                                 20
+Reads map to '+':                       20
+Reads map to '-':                       20
+Non-splice reads:                       36
+Splice reads:                           4
+Reads mapped in proper pairs:           39
+Proper-paired reads map to different chrom:0
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/hg19.chrom.sizes
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/hg19.chrom.sizes	Thu Jul 16 17:43:43 2015 -0400
@@ -0,0 +1,93 @@
+chr1	249250621
+chr2	243199373
+chr3	198022430
+chr4	191154276
+chr5	180915260
+chr6	171115067
+chr7	159138663
+chrX	155270560
+chr8	146364022
+chr9	141213431
+chr10	135534747
+chr11	135006516
+chr12	133851895
+chr13	115169878
+chr14	107349540
+chr15	102531392
+chr16	90354753
+chr17	81195210
+chr18	78077248
+chr20	63025520
+chrY	59373566
+chr19	59128983
+chr22	51304566
+chr21	48129895
+chr6_ssto_hap7	4928567
+chr6_mcf_hap5	4833398
+chr6_cox_hap2	4795371
+chr6_mann_hap4	4683263
+chr6_apd_hap1	4622290
+chr6_qbl_hap6	4611984
+chr6_dbb_hap3	4610396
+chr17_ctg5_hap1	1680828
+chr4_ctg9_hap1	590426
+chr1_gl000192_random	547496
+chrUn_gl000225	211173
+chr4_gl000194_random	191469
+chr4_gl000193_random	189789
+chr9_gl000200_random	187035
+chrUn_gl000222	186861
+chrUn_gl000212	186858
+chr7_gl000195_random	182896
+chrUn_gl000223	180455
+chrUn_gl000224	179693
+chrUn_gl000219	179198
+chr17_gl000205_random	174588
+chrUn_gl000215	172545
+chrUn_gl000216	172294
+chrUn_gl000217	172149
+chr9_gl000199_random	169874
+chrUn_gl000211	166566
+chrUn_gl000213	164239
+chrUn_gl000220	161802
+chrUn_gl000218	161147
+chr19_gl000209_random	159169
+chrUn_gl000221	155397
+chrUn_gl000214	137718
+chrUn_gl000228	129120
+chrUn_gl000227	128374
+chr1_gl000191_random	106433
+chr19_gl000208_random	92689
+chr9_gl000198_random	90085
+chr17_gl000204_random	81310
+chrUn_gl000233	45941
+chrUn_gl000237	45867
+chrUn_gl000230	43691
+chrUn_gl000242	43523
+chrUn_gl000243	43341
+chrUn_gl000241	42152
+chrUn_gl000236	41934
+chrUn_gl000240	41933
+chr17_gl000206_random	41001
+chrUn_gl000232	40652
+chrUn_gl000234	40531
+chr11_gl000202_random	40103
+chrUn_gl000238	39939
+chrUn_gl000244	39929
+chrUn_gl000248	39786
+chr8_gl000196_random	38914
+chrUn_gl000249	38502
+chrUn_gl000246	38154
+chr17_gl000203_random	37498
+chr8_gl000197_random	37175
+chrUn_gl000245	36651
+chrUn_gl000247	36422
+chr9_gl000201_random	36148
+chrUn_gl000235	34474
+chrUn_gl000239	33824
+chr21_gl000210_random	27682
+chrUn_gl000231	27386
+chrUn_gl000229	19913
+chrM	16571
+chrUn_gl000226	15008
+chr18_gl000207_random	4262
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/hg19_RefSeq_chr1_1-100000.bed
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/hg19_RefSeq_chr1_1-100000.bed	Thu Jul 16 17:43:43 2015 -0400
@@ -0,0 +1,7 @@
+chr1	11873	14409	NR_046018	0	+	14409	14409	0	3	354,109,1189,	0,739,1347,
+chr1	14361	29370	NR_024540	0	-	29370	29370	0	11	468,69,152,159,198,136,137,147,99,154,50,	0,608,1434,2245,2496,2871,3244,3553,3906,10376,14959,
+chr1	17368	17436	NR_106918	0	-	17436	17436	0	1	68,	0,
+chr1	17368	17436	NR_107062	0	-	17436	17436	0	1	68,	0,
+chr1	34610	36081	NR_026818	0	-	36081	36081	0	3	564,205,361,	0,666,1110,
+chr1	34610	36081	NR_026820	0	-	36081	36081	0	3	564,205,361,	0,666,1110,
+chr1	69090	70008	NM_001005484	0	+	69090	70008	0	1	918,	0,
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/output.DupRate_plot.r
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.DupRate_plot.r	Thu Jul 16 17:43:43 2015 -0400
@@ -0,0 +1,14 @@
+pdf('output.DupRate_plot.pdf')
+par(mar=c(5,4,4,5),las=0)
+seq_occ=c(1)
+seq_uniqRead=c(40)
+pos_occ=c(1)
+pos_uniqRead=c(40)
+plot(pos_occ,log10(pos_uniqRead),ylab='Number of Reads (log10)',xlab='Frequency',pch=4,cex=0.8,col='blue',xlim=c(1,500),yaxt='n')
+points(seq_occ,log10(seq_uniqRead),pch=20,cex=0.8,col='red')
+ym=floor(max(log10(pos_uniqRead)))
+legend(300,ym,legend=c('Sequence-base','Mapping-base'),col=c('blue','red'),pch=c(4,20))
+axis(side=2,at=0:ym,labels=0:ym)
+axis(side=4,at=c(log10(pos_uniqRead[1]),log10(pos_uniqRead[2]),log10(pos_uniqRead[3]),log10(pos_uniqRead[4])), labels=c(round(pos_uniqRead[1]*100/sum(pos_uniqRead)),round(pos_uniqRead[2]*100/sum(pos_uniqRead)),round(pos_uniqRead[3]*100/sum(pos_uniqRead)),round(pos_uniqRead[4]*100/sum(pos_uniqRead))))
+mtext(4, text = "Reads %", line = 2)
+dev.off()
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/output.GC.xls
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.GC.xls	Thu Jul 16 17:43:43 2015 -0400
@@ -0,0 +1,19 @@
+GC%	read_count
+60.78	3
+41.18	3
+47.06	5
+56.86	7
+29.41	1
+27.45	2
+37.25	2
+78.43	1
+58.82	1
+50.98	3
+49.02	2
+62.75	1
+68.63	1
+54.90	1
+52.94	3
+35.29	1
+43.14	2
+39.22	1
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/output.GC_plot.r
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.GC_plot.r	Thu Jul 16 17:43:43 2015 -0400
@@ -0,0 +1,4 @@
+pdf("output.GC_plot.pdf")
+gc=rep(c(60.78,41.18,47.06,56.86,29.41,27.45,37.25,78.43,58.82,50.98,49.02,62.75,68.63,54.90,52.94,35.29,43.14,39.22),times=c(3,3,5,7,1,2,2,1,1,3,2,1,1,1,3,1,2,1))
+hist(gc,probability=T,breaks=100,xlab="GC content (%)",ylab="Density of Reads",border="blue",main="")
+dev.off()
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/output.NVC.xls
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.NVC.xls	Thu Jul 16 17:43:43 2015 -0400
@@ -0,0 +1,52 @@
+Position	A	C	G	T	N	X
+0	5	7	18	10	0	0	
+1	6	7	15	8	4	0	
+2	5	9	18	5	3	0	
+3	11	9	14	4	2	0	
+4	5	9	12	14	0	0	
+5	4	11	19	6	0	0	
+6	11	7	12	10	0	0	
+7	9	8	12	9	2	0	
+8	12	9	11	8	0	0	
+9	8	9	8	10	5	0	
+10	9	8	9	14	0	0	
+11	9	6	11	14	0	0	
+12	14	8	12	6	0	0	
+13	10	6	9	15	0	0	
+14	9	9	7	15	0	0	
+15	10	10	9	9	2	0	
+16	8	4	6	14	8	0	
+17	9	9	10	9	3	0	
+18	7	5	11	12	5	0	
+19	12	8	4	10	6	0	
+20	10	6	9	15	0	0	
+21	9	9	15	7	0	0	
+22	14	6	11	9	0	0	
+23	13	11	11	5	0	0	
+24	12	8	7	10	3	0	
+25	9	13	4	8	6	0	
+26	11	16	7	6	0	0	
+27	11	8	13	8	0	0	
+28	13	6	9	12	0	0	
+29	9	9	12	10	0	0	
+30	8	6	15	11	0	0	
+31	7	9	11	13	0	0	
+32	7	8	14	11	0	0	
+33	11	11	10	8	0	0	
+34	6	12	13	9	0	0	
+35	8	17	11	4	0	0	
+36	9	8	7	16	0	0	
+37	11	9	12	8	0	0	
+38	8	9	10	13	0	0	
+39	8	12	11	9	0	0	
+40	12	9	10	9	0	0	
+41	9	13	11	7	0	0	
+42	10	12	9	9	0	0	
+43	7	13	11	9	0	0	
+44	10	12	6	12	0	0	
+45	10	10	9	11	0	0	
+46	7	10	10	13	0	0	
+47	9	9	12	10	0	0	
+48	10	6	14	10	0	0	
+49	8	10	13	9	0	0	
+50	7	8	9	16	0	0	
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/output.NVC_plot.r
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.NVC_plot.r	Thu Jul 16 17:43:43 2015 -0400
@@ -0,0 +1,17 @@
+position=c(0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50)
+A_count=c(5,6,5,11,5,4,11,9,12,8,9,9,14,10,9,10,8,9,7,12,10,9,14,13,12,9,11,11,13,9,8,7,7,11,6,8,9,11,8,8,12,9,10,7,10,10,7,9,10,8,7)
+C_count=c(7,7,9,9,9,11,7,8,9,9,8,6,8,6,9,10,4,9,5,8,6,9,6,11,8,13,16,8,6,9,6,9,8,11,12,17,8,9,9,12,9,13,12,13,12,10,10,9,6,10,8)
+G_count=c(18,15,18,14,12,19,12,12,11,8,9,11,12,9,7,9,6,10,11,4,9,15,11,11,7,4,7,13,9,12,15,11,14,10,13,11,7,12,10,11,10,11,9,11,6,9,10,12,14,13,9)
+T_count=c(10,8,5,4,14,6,10,9,8,10,14,14,6,15,15,9,14,9,12,10,15,7,9,5,10,8,6,8,12,10,11,13,11,8,9,4,16,8,13,9,9,7,9,9,12,11,13,10,10,9,16)
+N_count=c(0,4,3,2,0,0,0,2,0,5,0,0,0,0,0,2,8,3,5,6,0,0,0,0,3,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0)
+X_count=c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0)
+total= A_count + C_count + G_count + T_count
+ym=max(A_count/total,C_count/total,G_count/total,T_count/total) + 0.05
+yn=min(A_count/total,C_count/total,G_count/total,T_count/total)
+pdf("output.NVC_plot.pdf")
+plot(position,A_count/total,type="o",pch=20,ylim=c(yn,ym),col="dark green",xlab="Position of Read",ylab="Nucleotide Frequency")
+lines(position,T_count/total,type="o",pch=20,col="red")
+lines(position,G_count/total,type="o",pch=20,col="blue")
+lines(position,C_count/total,type="o",pch=20,col="cyan")
+legend(41,ym,legend=c("A","T","G","C"),col=c("dark green","red","blue","cyan"),lwd=2,pch=20,text.col=c("dark green","red","blue","cyan"))
+dev.off()
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/output.clipping_profile.pdf
Binary file test-data/output.clipping_profile.pdf has changed
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/output.clipping_profile.r
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.clipping_profile.r	Thu Jul 16 17:43:43 2015 -0400
@@ -0,0 +1,5 @@
+pdf("output.clipping_profile.pdf")
+read_pos=c(0,1,2,3,4,5,6,7,8,9,44,45,46,47,48,49,50)
+count=c(16,12,11,8,6,5,1,1,1,1,1,2,2,2,3,4,4)
+plot(read_pos,1-(count/40),col="blue",main="clipping profile",xlab="Position of reads",ylab="Mappability",type="b")
+dev.off()
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/output.clipping_profile.xls
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.clipping_profile.xls	Thu Jul 16 17:43:43 2015 -0400
@@ -0,0 +1,18 @@
+Position	Read_Total	Read_clipped
+0	40	16
+1	40	12
+2	40	11
+3	40	8
+4	40	6
+5	40	5
+6	40	1
+7	40	1
+8	40	1
+9	40	1
+44	40	1
+45	40	2
+46	40	2
+47	40	2
+48	40	3
+49	40	4
+50	40	4
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/output.eRPKM.xls
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.eRPKM.xls	Thu Jul 16 17:43:43 2015 -0400
@@ -0,0 +1,8 @@
+#chr	start	end	name	score	strand	5%	10%	15%	20%	25%	30%	35%	40%	45%	50%	55%	60%	65%	70%	75%	80%	85%	90%	95%	100%
+chr1	17368	17436	NR_106918	0	-	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
+chr1	17368	17436	NR_107062	0	-	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
+chr1	34610	36081	NR_026818	0	-	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
+chr1	69090	70008	NM_001005484	0	+	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
+chr1	14361	29370	NR_024540	0	-	256950.511332	128475.255666	85650.1704438	128475.255666	102780.204533	85650.1704438	73414.431809	64237.6278329	57100.1136292	51390.1022663	46718.2747875	64237.6278329	59296.2718457	55060.8238568	51390.1022663	48178.2208747	45344.207882	57100.1136292	54094.8444908	51390.1022663
+chr1	34610	36081	NR_026820	0	-	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
+chr1	11873	14409	NR_046018	0	+	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	30572.0644704	27514.8580233	25013.5072939	22929.0483528	42330.5508051	39306.9400333	36686.4773644	34393.5725292	32370.4212039	45858.0967056	43444.5126684	41272.287035
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/output.geneBodyCoverage.curves.pdf
Binary file test-data/output.geneBodyCoverage.curves.pdf has changed
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/output.geneBodyCoverage.r
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.geneBodyCoverage.r	Thu Jul 16 17:43:43 2015 -0400
@@ -0,0 +1,8 @@
+d1_pairend_strandspecific_51mer_hg19_chr1_1_100000_bam <- c(0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0)
+
+
+pdf("output.geneBodyCoverage.curves.pdf")
+x=1:100
+icolor = colorRampPalette(c("#7fc97f","#beaed4","#fdc086","#ffff99","#386cb0","#f0027f"))(1)
+plot(x,d1_pairend_strandspecific_51mer_hg19_chr1_1_100000_bam,type='l',xlab="Gene body percentile (5'->3')", ylab="Coverage",lwd=0.8,col=icolor[1])
+dev.off()
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/output.geneBodyCoverage.txt
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.geneBodyCoverage.txt	Thu Jul 16 17:43:43 2015 -0400
@@ -0,0 +1,2 @@
+Percentile	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20	21	22	23	24	25	26	27	28	29	30	31	32	33	34	35	36	37	38	39	40	41	42	43	44	45	46	47	48	49	50	51	52	53	54	55	56	57	58	59	60	61	62	63	64	65	66	67	68	69	70	71	72	73	74	75	76	77	78	79	80	81	82	83	84	85	86	87	88	89	90	91	92	93	94	95	96	97	98	99	100
+d1_pairend_strandspecific_51mer_hg19_chr1_1_100000_bam	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	1.0	1.0	0.0	1.0	1.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	1.0	1.0	0.0	0.0	1.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/output.infer_experiment.txt
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.infer_experiment.txt	Thu Jul 16 17:43:43 2015 -0400
@@ -0,0 +1,6 @@
+
+
+This is PairEnd Data
+Fraction of reads explained by "1++,1--,2+-,2-+": 1.0000
+Fraction of reads explained by "1+-,1-+,2++,2--": 0.0000
+Fraction of reads explained by other combinations: 0.0000
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/output.inner_distance.txt
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.inner_distance.txt	Thu Jul 16 17:43:43 2015 -0400
@@ -0,0 +1,20 @@
+seq.11990047	235	sameTranscript=No,dist=genomic
+seq.14614493	31	sameTranscript=Yes,sameExon=Yes,dist=mRNA
+seq.24018133	2	sameTranscript=Yes,nonExonic=Yes,dist=genomic
+seq.10608403	158	sameTranscript=Yes,sameExon=No,dist=mRNA
+seq.10820209	146	sameTranscript=Yes,nonExonic=Yes,dist=genomic
+seq.1537155	33	sameTranscript=Yes,nonExonic=Yes,dist=genomic
+seq.25274725	17	sameTranscript=Yes,nonExonic=Yes,dist=genomic
+seq.26326595	211	sameTranscript=Yes,nonExonic=Yes,dist=genomic
+seq.28833653	55	sameTranscript=Yes,nonExonic=Yes,dist=genomic
+seq.25049090	61	sameTranscript=Yes,nonExonic=Yes,dist=genomic
+seq.23476912	69	sameTranscript=Yes,nonExonic=Yes,dist=genomic
+seq.28059536	225	sameTranscript=Yes,nonExonic=Yes,dist=genomic
+seq.13270875	200	sameTranscript=Yes,nonExonic=Yes,dist=genomic
+seq.2214586	132	sameTranscript=Yes,nonExonic=Yes,dist=genomic
+seq.31061198	-31	readPairOverlap
+seq.13539256	208	sameTranscript=No,dist=genomic
+seq.13835843	-7	sameTranscript=No,dist=genomic
+seq.5556605	88	sameTranscript=No,dist=genomic
+seq.20367385	17	sameTranscript=No,dist=genomic
+seq.17373919	146394	sameTranscript=No,dist=genomic
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/output.inner_distance_freq.txt
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.inner_distance_freq.txt	Thu Jul 16 17:43:43 2015 -0400
@@ -0,0 +1,100 @@
+-250	-245	0
+-245	-240	0
+-240	-235	0
+-235	-230	0
+-230	-225	0
+-225	-220	0
+-220	-215	0
+-215	-210	0
+-210	-205	0
+-205	-200	0
+-200	-195	0
+-195	-190	0
+-190	-185	0
+-185	-180	0
+-180	-175	0
+-175	-170	0
+-170	-165	0
+-165	-160	0
+-160	-155	0
+-155	-150	0
+-150	-145	0
+-145	-140	0
+-140	-135	0
+-135	-130	0
+-130	-125	0
+-125	-120	0
+-120	-115	0
+-115	-110	0
+-110	-105	0
+-105	-100	0
+-100	-95	0
+-95	-90	0
+-90	-85	0
+-85	-80	0
+-80	-75	0
+-75	-70	0
+-70	-65	0
+-65	-60	0
+-60	-55	0
+-55	-50	0
+-50	-45	0
+-45	-40	0
+-40	-35	0
+-35	-30	1
+-30	-25	0
+-25	-20	0
+-20	-15	0
+-15	-10	0
+-10	-5	1
+-5	0	0
+0	5	1
+5	10	0
+10	15	0
+15	20	2
+20	25	0
+25	30	0
+30	35	2
+35	40	0
+40	45	0
+45	50	0
+50	55	1
+55	60	0
+60	65	1
+65	70	1
+70	75	0
+75	80	0
+80	85	0
+85	90	1
+90	95	0
+95	100	0
+100	105	0
+105	110	0
+110	115	0
+115	120	0
+120	125	0
+125	130	0
+130	135	1
+135	140	0
+140	145	0
+145	150	1
+150	155	0
+155	160	1
+160	165	0
+165	170	0
+170	175	0
+175	180	0
+180	185	0
+185	190	0
+190	195	0
+195	200	1
+200	205	0
+205	210	1
+210	215	1
+215	220	0
+220	225	1
+225	230	0
+230	235	1
+235	240	0
+240	245	0
+245	250	0
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/output.inner_distance_plot.pdf
Binary file test-data/output.inner_distance_plot.pdf has changed
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/output.inner_distance_plot.r
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.inner_distance_plot.r	Thu Jul 16 17:43:43 2015 -0400
@@ -0,0 +1,11 @@
+pdf('output.inner_distance_plot.pdf')
+fragsize=rep(c(-248,-243,-238,-233,-228,-223,-218,-213,-208,-203,-198,-193,-188,-183,-178,-173,-168,-163,-158,-153,-148,-143,-138,-133,-128,-123,-118,-113,-108,-103,-98,-93,-88,-83,-78,-73,-68,-63,-58,-53,-48,-43,-38,-33,-28,-23,-18,-13,-8,-3,2,7,12,17,22,27,32,37,42,47,52,57,62,67,72,77,82,87,92,97,102,107,112,117,122,127,132,137,142,147,152,157,162,167,172,177,182,187,192,197,202,207,212,217,222,227,232,237,242,247),times=c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,1,0,0,2,0,0,2,0,0,0,1,0,1,1,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,1,0,1,0,0,0,0,0,0,0,1,0,1,1,0,1,0,1,0,0,0))
+frag_sd = sd(fragsize)
+frag_mean = mean(fragsize)
+frag_median = median(fragsize)
+write(c("Mean insert size",frag_mean), stdout())
+write(c("Median insert size",frag_median), stdout())
+write(c("Standard deviation",frag_sd), stdout())
+hist(fragsize,probability=T,breaks=100,xlab="mRNA insert size (bp)",main=paste(c("Mean=",frag_mean,";","SD=",frag_sd),collapse=""),border="blue")
+lines(density(fragsize,bw=10),col='red')
+dev.off()
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/output.junction.xls
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.junction.xls	Thu Jul 16 17:43:43 2015 -0400
@@ -0,0 +1,4 @@
+chrom	intron_st(0-based)	intron_end(1-based)	read_count	annotation
+chr1	17055	17232	1	annotated
+chr1	21768	22000	1	complete_novel
+chr1	12697	13220	1	partial_novel
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/output.junctionSaturation_plot.r
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.junctionSaturation_plot.r	Thu Jul 16 17:43:43 2015 -0400
@@ -0,0 +1,12 @@
+pdf('output.junctionSaturation_plot.pdf')
+x=c(5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80,85,90,95,100)
+y=c(0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1)
+z=c(0,0,0,0,0,0,1,1,1,1,1,1,1,2,2,2,2,2,2,3)
+w=c(0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,2)
+m=max(0,0,0)
+n=min(0,0,0)
+plot(x,z/1000,xlab='percent of total reads',ylab='Number of splicing junctions (x1000)',type='o',col='blue',ylim=c(n,m))
+points(x,y/1000,type='o',col='red')
+points(x,w/1000,type='o',col='green')
+legend(5,0, legend=c("All junctions","known junctions", "novel junctions"),col=c("blue","red","green"),lwd=1,pch=1)
+dev.off()
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/output.junction_plot.r
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.junction_plot.r	Thu Jul 16 17:43:43 2015 -0400
@@ -0,0 +1,8 @@
+pdf("output.splice_events.pdf")
+events=c(25.0,25.0,25.0)
+pie(events,col=c(2,3,4),init.angle=30,angle=c(60,120,150),density=c(70,70,70),main="splicing events",labels=c("partial_novel 25%","complete_novel 25%","known 25%"))
+dev.off()
+pdf("output.splice_junction.pdf")
+junction=c(33.3333333333,33.3333333333,33.3333333333)
+pie(junction,col=c(2,3,4),init.angle=30,angle=c(60,120,150),density=c(70,70,70),main="splicing junctions",labels=c("partial_novel 33%","complete_novel 33%","known 33%"))
+dev.off()
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/output.pos.DupRate.xls
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.pos.DupRate.xls	Thu Jul 16 17:43:43 2015 -0400
@@ -0,0 +1,2 @@
+Occurrence	UniqReadNumber
+1	40
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/output.qual.r
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.qual.r	Thu Jul 16 17:43:43 2015 -0400
@@ -0,0 +1,62 @@
+pdf('output.qual.boxplot.pdf')
+p0<-rep(c(33,43,45,51,54,58,59,60,61,62,63,64,66,67,69,70,71),times=c(1,2,1,3,1,1,1,1,1,3,1,1,1,2,5,5,10)/1000)
+p1<-rep(c(43,45,51,56,57,58,60,61,62,63,64,65,66,67,68,69,70,71),times=c(1,1,1,1,1,1,1,2,1,1,2,1,3,3,1,8,5,6)/1000)
+p2<-rep(c(43,49,51,53,54,56,58,59,60,61,64,65,66,67,69,70,71),times=c(1,1,1,1,2,1,1,1,2,1,1,2,2,2,7,6,8)/1000)
+p3<-rep(c(33,39,53,54,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(1,1,1,1,1,1,1,1,1,1,2,1,1,1,4,4,1,5,5,6)/1000)
+p4<-rep(c(33,55,58,59,60,61,62,64,65,66,67,68,69,70,71),times=c(1,1,1,1,5,1,1,4,1,2,5,2,3,3,9)/1000)
+p5<-rep(c(33,53,58,60,61,62,64,65,67,68,69,70,71),times=c(1,1,1,2,1,4,3,2,2,3,5,4,11)/1000)
+p6<-rep(c(33,40,54,56,58,60,64,66,67,68,69,70,71),times=c(3,2,1,1,1,1,2,2,4,4,4,2,13)/1000)
+p7<-rep(c(41,42,43,49,50,51,57,58,62,64,65,66,67,68,69,70,71),times=c(1,1,1,1,2,1,1,1,2,1,1,2,7,1,2,3,12)/1000)
+p8<-rep(c(33,39,53,56,58,59,60,62,63,66,67,68,69,70,71),times=c(1,1,1,1,1,1,2,1,2,4,3,2,3,5,12)/1000)
+p9<-rep(c(33,40,50,52,53,57,58,60,64,65,66,67,68,69,70,71),times=c(1,1,1,1,1,1,3,1,4,1,1,3,2,5,4,10)/1000)
+p10<-rep(c(33,40,53,54,55,58,60,63,64,66,67,68,69,70,71),times=c(2,1,1,2,1,1,2,1,4,1,1,1,7,6,9)/1000)
+p11<-rep(c(45,50,51,52,53,56,57,58,60,62,63,64,65,66,67,68,69,70,71),times=c(1,2,1,1,1,1,1,1,3,2,1,1,1,3,1,1,3,5,10)/1000)
+p12<-rep(c(33,41,52,53,54,58,59,60,64,65,66,67,69,70,71),times=c(3,1,1,2,1,1,1,3,1,2,3,2,5,6,8)/1000)
+p13<-rep(c(33,40,51,53,55,56,58,59,60,63,64,65,66,67,68,69,70,71),times=c(4,1,1,1,1,1,1,1,1,1,3,1,2,2,2,3,5,9)/1000)
+p14<-rep(c(33,39,54,56,57,59,60,61,62,63,65,66,67,68,69,70,71),times=c(4,1,3,1,1,1,1,2,1,1,1,2,2,1,7,2,9)/1000)
+p15<-rep(c(33,39,40,42,45,50,52,53,57,58,59,60,61,64,66,68,69,70,71),times=c(2,2,1,1,1,1,1,1,1,3,1,1,1,3,1,1,4,5,9)/1000)
+p16<-rep(c(33,47,51,52,53,58,59,60,61,64,67,69,70,71),times=c(4,1,1,1,2,3,1,1,2,3,3,7,2,9)/1000)
+p17<-rep(c(33,48,50,51,53,54,55,56,58,60,61,63,64,65,66,67,69,70,71),times=c(1,1,1,1,2,1,1,1,2,2,3,2,2,1,2,1,7,2,7)/1000)
+p18<-rep(c(33,43,48,51,53,58,59,60,61,63,64,66,67,68,69,70,71),times=c(2,1,1,1,2,2,1,2,2,3,1,1,3,1,7,2,8)/1000)
+p19<-rep(c(33,44,47,50,51,52,54,58,59,61,62,64,65,67,69,70,71),times=c(2,1,1,2,1,1,2,1,1,1,1,3,1,1,8,4,9)/1000)
+p20<-rep(c(33,46,47,51,54,56,58,59,61,62,63,64,66,67,69,70,71),times=c(1,1,1,1,2,1,1,2,1,2,1,5,5,3,5,2,6)/1000)
+p21<-rep(c(33,43,54,55,57,58,62,64,65,66,67,68,69,70,71),times=c(1,1,1,1,1,5,2,3,1,3,2,4,5,4,6)/1000)
+p22<-rep(c(33,47,51,53,54,57,58,60,62,63,64,65,66,68,69,70,71),times=c(1,1,1,1,1,1,1,1,2,1,5,1,4,3,5,5,6)/1000)
+p23<-rep(c(33,42,53,54,55,57,58,62,63,64,65,66,67,68,69,70,71),times=c(1,1,1,1,1,1,2,1,1,5,2,2,3,2,9,3,4)/1000)
+p24<-rep(c(33,42,52,54,57,60,61,63,64,65,66,67,69,70,71),times=c(1,1,1,1,1,2,1,1,5,1,6,4,5,4,6)/1000)
+p25<-rep(c(33,53,54,57,61,62,63,64,66,67,68,69,70,71),times=c(1,1,1,2,1,1,1,2,4,5,2,9,5,5)/1000)
+p26<-rep(c(46,53,54,57,58,60,61,62,64,66,67,68,69,70,71),times=c(1,1,1,1,1,1,1,2,5,8,4,1,5,3,5)/1000)
+p27<-rep(c(42,43,48,54,56,57,60,61,62,66,67,68,69,70,71),times=c(1,1,1,2,1,1,4,1,2,1,4,1,5,6,9)/1000)
+p28<-rep(c(51,55,56,57,60,62,64,65,66,67,68,69,70,71),times=c(1,1,1,1,1,2,4,2,2,2,4,10,1,8)/1000)
+p29<-rep(c(49,52,56,57,58,60,63,64,65,66,67,69,70,71),times=c(2,1,1,1,2,1,1,3,1,3,6,8,2,8)/1000)
+p30<-rep(c(45,47,50,57,61,62,64,66,67,68,69,70,71),times=c(1,1,1,1,1,1,2,6,3,2,8,5,8)/1000)
+p31<-rep(c(48,52,53,54,57,58,59,60,61,62,64,65,66,67,68,69,70,71),times=c(1,1,1,1,1,1,1,1,2,1,4,1,2,3,3,7,3,6)/1000)
+p32<-rep(c(43,47,48,54,56,62,64,66,67,68,69,70,71),times=c(1,1,1,1,2,1,2,1,5,3,10,5,7)/1000)
+p33<-rep(c(52,55,58,60,61,63,64,68,69,70,71),times=c(1,1,2,1,1,1,5,4,11,5,8)/1000)
+p34<-rep(c(42,43,50,56,59,60,63,64,67,68,69,70,71),times=c(1,1,1,1,1,1,1,3,1,4,9,5,11)/1000)
+p35<-rep(c(42,53,57,58,60,64,66,68,69,70,71),times=c(1,1,1,2,1,3,2,2,12,7,8)/1000)
+p36<-rep(c(48,53,56,61,63,64,66,67,69,70,71),times=c(2,1,1,2,1,1,2,6,7,3,14)/1000)
+p37<-rep(c(53,56,60,63,64,66,68,69,70,71),times=c(2,2,1,1,3,2,6,7,8,8)/1000)
+p38<-rep(c(41,48,53,57,59,61,62,63,64,66,67,68,69,70,71),times=c(1,1,1,1,1,1,1,1,3,3,4,1,4,6,11)/1000)
+p39<-rep(c(38,42,51,53,56,58,61,63,64,65,66,67,68,69,70,71),times=c(1,1,1,1,1,1,1,1,2,1,4,2,2,7,3,11)/1000)
+p40<-rep(c(53,58,61,62,63,64,66,67,68,69,70,71),times=c(1,1,3,1,2,2,1,2,2,9,4,12)/1000)
+p41<-rep(c(48,53,54,57,58,59,60,61,63,64,66,67,68,69,70,71),times=c(1,1,1,1,1,1,2,1,1,1,3,3,1,5,7,9)/1000)
+p42<-rep(c(38,49,54,58,59,64,65,66,67,68,69,70,71),times=c(1,1,3,1,1,3,1,2,1,1,7,7,9)/1000)
+p43<-rep(c(50,51,62,63,64,65,66,67,69,70,71),times=c(2,1,1,1,3,1,2,4,3,8,12)/1000)
+p44<-rep(c(48,54,63,64,65,66,67,68,69,70,71),times=c(1,2,4,1,1,2,2,1,7,8,8)/1000)
+p45<-rep(c(50,57,58,59,60,62,64,67,69,70,71),times=c(1,1,1,1,1,1,1,1,10,8,7)/1000)
+p46<-rep(c(43,48,54,59,60,64,65,66,67,68,69,70,71),times=c(2,1,1,2,1,2,1,1,4,2,1,6,8)/1000)
+p47<-rep(c(49,53,56,61,64,66,67,69,70,71),times=c(1,1,1,1,2,2,2,3,10,7)/1000)
+p48<-rep(c(61,64,66,67,68,69,70,71),times=c(2,1,2,2,2,6,5,7)/1000)
+p49<-rep(c(33,56,60,64,66,68,69,70,71),times=c(1,1,2,1,1,2,2,5,10)/1000)
+p50<-rep(c(33,66,67,68,69,70,71),times=c(1,1,1,2,4,5,7)/1000)
+boxplot(p0,p1,p2,p3,p4,p5,p6,p7,p8,p9,p10,p11,p12,p13,p14,p15,p16,p17,p18,p19,p20,p21,p22,p23,p24,p25,p26,p27,p28,p29,p30,p31,p32,p33,p34,p35,p36,p37,p38,p39,p40,p41,p42,p43,p44,p45,p46,p47,p48,p49,p50,xlab="Position of Read(5'->3')",ylab="Phred Quality Score",outline=F)
+dev.off()
+
+
+pdf('output.qual.heatmap.pdf')
+qual=c(1,0,0,0,0,0,0,0,0,0,2,0,1,0,0,0,0,0,3,0,0,1,0,0,0,1,1,1,1,3,1,1,0,1,2,0,5,5,10,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,1,1,1,0,1,2,1,1,2,1,3,3,1,8,5,6,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,1,0,1,2,0,1,0,1,1,2,1,0,0,1,2,2,2,0,7,6,8,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,1,1,1,1,1,1,2,1,1,1,4,4,1,5,5,6,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,1,5,1,1,0,4,1,2,5,2,3,3,9,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,2,1,4,0,3,2,0,2,3,5,4,11,3,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,1,0,1,0,0,0,2,0,2,4,4,4,2,13,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,1,2,1,0,0,0,0,0,1,1,0,0,0,2,0,1,1,2,7,1,2,3,12,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,1,1,2,0,1,2,0,0,4,3,2,3,5,12,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,1,1,0,0,0,1,3,0,1,0,0,0,4,1,1,3,2,5,4,10,2,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,2,1,0,0,1,0,2,0,0,1,4,0,1,1,1,7,6,9,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,2,1,1,1,0,0,1,1,1,0,3,0,2,1,1,1,3,1,1,3,5,10,3,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,2,1,0,0,0,1,1,3,0,0,0,1,2,3,2,0,5,6,8,4,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,1,0,1,1,0,1,1,1,0,0,1,3,1,2,2,2,3,5,9,4,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,1,1,0,1,1,2,1,1,0,1,2,2,1,7,2,9,2,0,0,0,0,0,2,1,0,1,0,0,1,0,0,0,0,1,0,1,1,0,0,0,1,3,1,1,1,0,0,3,0,1,0,1,4,5,9,4,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,1,2,0,0,0,0,3,1,1,2,0,0,3,0,0,3,0,7,2,9,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,1,0,2,1,1,1,0,2,0,2,3,0,2,2,1,2,1,0,7,2,7,2,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,1,0,2,0,0,0,0,2,1,2,2,0,3,1,0,1,3,1,7,2,8,2,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,2,1,1,0,2,0,0,0,1,1,0,1,1,0,3,1,0,1,0,8,4,9,1,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,1,0,0,2,0,1,0,1,2,0,1,2,1,5,0,5,3,0,5,2,6,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,1,0,1,5,0,0,0,2,0,3,1,3,2,4,5,4,6,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,1,1,0,0,1,1,0,1,0,2,1,5,1,4,0,3,5,5,6,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,1,1,0,1,2,0,0,0,1,1,5,2,2,3,2,9,3,4,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,1,0,0,1,0,0,2,1,0,1,5,1,6,4,0,5,4,6,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,2,0,0,0,1,1,1,2,0,4,5,2,9,5,5,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,1,0,0,1,1,0,1,1,2,0,5,0,8,4,1,5,3,5,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,1,0,0,0,0,0,2,0,1,1,0,0,4,1,2,0,0,0,1,4,1,5,6,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,1,1,0,0,1,0,2,0,4,2,2,2,4,10,1,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,1,0,0,0,1,1,2,0,1,0,0,1,3,1,3,6,0,8,2,8,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,1,0,0,0,0,0,0,1,0,0,0,1,1,0,2,0,6,3,2,8,5,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,1,1,0,0,1,1,1,1,2,1,0,4,1,2,3,3,7,3,6,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,1,0,0,0,0,0,1,0,2,0,0,0,0,0,1,0,2,0,1,5,3,10,5,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,2,0,1,1,0,1,5,0,0,0,4,11,5,8,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,1,1,0,0,1,3,0,0,1,4,9,5,11,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,2,0,1,0,0,0,3,0,2,0,2,12,7,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,1,0,0,1,0,0,0,0,2,0,1,1,0,2,6,0,7,3,14,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,2,0,0,0,1,0,0,1,3,0,2,0,6,7,8,8,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,1,0,1,0,1,1,1,3,0,3,4,1,4,6,11,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,1,0,1,0,0,1,0,1,0,0,1,0,1,2,1,4,2,2,7,3,11,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,3,1,2,2,0,1,2,2,9,4,12,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,1,0,0,1,1,1,2,1,0,1,1,0,3,3,1,5,7,9,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,3,0,0,0,1,1,0,0,0,0,3,1,2,1,1,7,7,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,1,0,0,0,0,0,0,0,0,0,0,1,1,3,1,2,4,0,3,8,12,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,2,0,0,0,0,0,0,0,0,4,1,1,2,2,1,7,8,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,1,1,1,0,1,0,1,0,0,1,0,10,8,7,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,2,1,0,0,0,2,1,1,4,2,1,6,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,1,0,0,0,0,1,0,0,2,0,2,2,0,3,10,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,1,0,2,2,2,6,5,7,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,2,0,0,0,1,0,1,0,2,2,5,10,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,2,4,5,7)
+mat=matrix(qual,ncol=51,byrow=F)
+Lab.palette <- colorRampPalette(c("blue", "orange", "red3","red2","red1","red"), space = "rgb",interpolate=c('spline'))
+heatmap(mat,Rowv=NA,Colv=NA,xlab="Position of Read",ylab="Phred Quality Score",labRow=seq(from=33,to=71),col = Lab.palette(256),scale="none" )
+dev.off()
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/output.rawCount.xls
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.rawCount.xls	Thu Jul 16 17:43:43 2015 -0400
@@ -0,0 +1,8 @@
+#chr	start	end	name	score	strand	5%	10%	15%	20%	25%	30%	35%	40%	45%	50%	55%	60%	65%	70%	75%	80%	85%	90%	95%	100%
+chr1	17368	17436	NR_106918	0	-	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
+chr1	17368	17436	NR_107062	0	-	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
+chr1	34610	36081	NR_026818	0	-	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
+chr1	69090	70008	NM_001005484	0	+	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
+chr1	14361	29370	NR_024540	0	-	1	1	1	2	2	2	2	2	2	2	2	3	3	3	3	3	3	4	4	4
+chr1	34610	36081	NR_026820	0	-	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
+chr1	11873	14409	NR_046018	0	+	0	0	0	0	0	0	0	0	1	1	1	1	2	2	2	2	2	3	3	3
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/output.read_distribution.txt
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.read_distribution.txt	Thu Jul 16 17:43:43 2015 -0400
@@ -0,0 +1,16 @@
+Total Reads                   40
+Total Tags                    44
+Total Assigned Tags           38
+=====================================================================
+Group               Total_bases         Tag_count           Tags/Kb             
+CDS_Exons           918                 0                   0.00              
+5'UTR_Exons         1652                3                   1.81              
+3'UTR_Exons         2967                4                   1.35              
+Introns             14397               27                  1.88              
+TSS_up_1kb          4000                0                   0.00              
+TSS_up_5kb          20000               4                   0.20              
+TSS_up_10kb         35240               4                   0.11              
+TES_down_1kb        2000                0                   0.00              
+TES_down_5kb        12512               0                   0.00              
+TES_down_10kb       22752               0                   0.00              
+=====================================================================
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/output.saturation.r
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.saturation.r	Thu Jul 16 17:43:43 2015 -0400
@@ -0,0 +1,87 @@
+pdf('output.saturation.pdf')
+par(mfrow=c(2,2))
+name=c(5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80,85,90,95)
+S5=c()
+S10=c()
+S15=c()
+S20=c()
+S25=c()
+S30=c()
+S35=c()
+S40=c()
+S45=c()
+S50=c()
+S55=c()
+S60=c()
+S65=c()
+S70=c()
+S75=c()
+S80=c()
+S85=c()
+S90=c()
+S95=c()
+boxplot(100*S5,100*S10,100*S15,100*S20,100*S25,100*S30,100*S35,100*S40,100*S45,100*S50,100*S55,100*S60,100*S65,100*S70,100*S75,100*S80,100*S85,100*S90,100*S95,names=name,outline=F,ylab='Percent Relative Error',main='Q1',xlab='Resampling percentage')
+name=c(5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80,85,90,95)
+S5=c(1.0)
+S10=c(1.0)
+S15=c(1.0)
+S20=c(1.0)
+S25=c(1.0)
+S30=c(1.0)
+S35=c(1.0)
+S40=c(1.0)
+S45=c(0.259259259259)
+S50=c(0.333333333334)
+S55=c(0.39393939394)
+S60=c(0.444444444444)
+S65=c(0.0256410256403)
+S70=c(0.0476190476199)
+S75=c(0.111111111112)
+S80=c(0.166666666666)
+S85=c(0.21568627451)
+S90=c(0.111111111112)
+S95=c(0.0526315789469)
+boxplot(100*S5,100*S10,100*S15,100*S20,100*S25,100*S30,100*S35,100*S40,100*S45,100*S50,100*S55,100*S60,100*S65,100*S70,100*S75,100*S80,100*S85,100*S90,100*S95,names=name,outline=F,ylab='Percent Relative Error',main='Q2',xlab='Resampling percentage')
+name=c(5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80,85,90,95)
+S5=c()
+S10=c()
+S15=c()
+S20=c()
+S25=c()
+S30=c()
+S35=c()
+S40=c()
+S45=c()
+S50=c()
+S55=c()
+S60=c()
+S65=c()
+S70=c()
+S75=c()
+S80=c()
+S85=c()
+S90=c()
+S95=c()
+boxplot(100*S5,100*S10,100*S15,100*S20,100*S25,100*S30,100*S35,100*S40,100*S45,100*S50,100*S55,100*S60,100*S65,100*S70,100*S75,100*S80,100*S85,100*S90,100*S95,names=name,outline=F,ylab='Percent Relative Error',main='Q3',xlab='Resampling percentage')
+name=c(5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80,85,90,95)
+S5=c(4.00000000001)
+S10=c(1.5)
+S15=c(0.666666666666)
+S20=c(1.5)
+S25=c(1.00000000001)
+S30=c(0.666666666666)
+S35=c(0.428571428571)
+S40=c(0.25)
+S45=c(0.111111111111)
+S50=c(0.0)
+S55=c(0.09090909091)
+S60=c(0.25)
+S65=c(0.153846153846)
+S70=c(0.0714285714295)
+S75=c(0.0)
+S80=c(0.0624999999991)
+S85=c(0.117647058824)
+S90=c(0.111111111111)
+S95=c(0.0526315789465)
+boxplot(100*S5,100*S10,100*S15,100*S20,100*S25,100*S30,100*S35,100*S40,100*S45,100*S50,100*S55,100*S60,100*S65,100*S70,100*S75,100*S80,100*S85,100*S90,100*S95,names=name,outline=F,ylab='Percent Relative Error',main='Q4',xlab='Resampling percentage')
+dev.off()
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/output.seq.DupRate.xls
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.seq.DupRate.xls	Thu Jul 16 17:43:43 2015 -0400
@@ -0,0 +1,2 @@
+Occurrence	UniqReadNumber
+1	40
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/output.splice_events.pdf
Binary file test-data/output.splice_events.pdf has changed
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/output.splice_junction.pdf
Binary file test-data/output.splice_junction.pdf has changed
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/output2.geneBodyCoverage.curves.pdf
Binary file test-data/output2.geneBodyCoverage.curves.pdf has changed
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/output2.geneBodyCoverage.heatMap.pdf
Binary file test-data/output2.geneBodyCoverage.heatMap.pdf has changed
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/output2.geneBodyCoverage.r
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output2.geneBodyCoverage.r	Thu Jul 16 17:43:43 2015 -0400
@@ -0,0 +1,8 @@
+d1_pairend_strandspecific_51mer_hg19_chr1_1_100000_bam <- c(0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0)
+
+
+pdf("output.geneBodyCoverage.curves.pdf")
+x=1:100
+icolor = colorRampPalette(c("#7fc97f","#beaed4","#fdc086","#ffff99","#386cb0","#f0027f"))(1)
+plot(x,d1_pairend_strandspecific_51mer_hg19_chr1_1_100000_bam,type='l',xlab="Gene body percentile (5'->3')", ylab="Coverage",lwd=0.8,col=icolor[1])
+dev.off()
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/output2.geneBodyCoverage.txt
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output2.geneBodyCoverage.txt	Thu Jul 16 17:43:43 2015 -0400
@@ -0,0 +1,2 @@
+Percentile	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20	21	22	23	24	25	26	27	28	29	30	31	32	33	34	35	36	37	38	39	40	41	42	43	44	45	46	47	48	49	50	51	52	53	54	55	56	57	58	59	60	61	62	63	64	65	66	67	68	69	70	71	72	73	74	75	76	77	78	79	80	81	82	83	84	85	86	87	88	89	90	91	92	93	94	95	96	97	98	99	100
+d1_pairend_strandspecific_51mer_hg19_chr1_1_100000_bam	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	1.0	1.0	0.0	1.0	1.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	1.0	1.0	0.0	0.0	1.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/output_read_count.xls
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output_read_count.xls	Thu Jul 16 17:43:43 2015 -0400
@@ -0,0 +1,47 @@
+#chrom	st	end	accession	score	gene_strand	tag_count	RPKM
+chr1	12227	12612	NR_046018_intron_1	0	+	0	0.000
+chr1	12721	13220	NR_046018_intron_2	0	+	0	0.000
+chr1	11873	12227	NR_046018_exon_1	0	+	0	0.000
+chr1	12612	12721	NR_046018_exon_2	0	+	1	208507.089
+chr1	13220	14409	NR_046018_exon_3	0	+	2	38229.222
+chr1	11873	14409	NR_046018_mRNA	0	+	3	41272.287
+chr1	14829	14969	NR_024540_intron_10	0	-	0	0.000
+chr1	15038	15795	NR_024540_intron_9	0	-	0	0.000
+chr1	15947	16606	NR_024540_intron_8	0	-	2	68975.031
+chr1	16765	16857	NR_024540_intron_7	0	-	0	0.000
+chr1	17055	17232	NR_024540_intron_6	0	-	0	0.000
+chr1	17368	17605	NR_024540_intron_5	0	-	1	95895.666
+chr1	17742	17914	NR_024540_intron_4	0	-	0	0.000
+chr1	18061	18267	NR_024540_intron_3	0	-	0	0.000
+chr1	18366	24737	NR_024540_intron_2	0	-	22	78480.615
+chr1	24891	29320	NR_024540_intron_1	0	-	2	10262.936
+chr1	14361	14829	NR_024540_exon_11	0	-	2	97125.097
+chr1	14969	15038	NR_024540_exon_10	0	-	0	0.000
+chr1	15795	15947	NR_024540_exon_9	0	-	0	0.000
+chr1	16606	16765	NR_024540_exon_8	0	-	0	0.000
+chr1	16857	17055	NR_024540_exon_7	0	-	1	114784.206
+chr1	17232	17368	NR_024540_exon_6	0	-	1	167112.299
+chr1	17605	17742	NR_024540_exon_5	0	-	0	0.000
+chr1	17914	18061	NR_024540_exon_4	0	-	0	0.000
+chr1	18267	18366	NR_024540_exon_3	0	-	0	0.000
+chr1	24737	24891	NR_024540_exon_2	0	-	0	0.000
+chr1	29320	29370	NR_024540_exon_1	0	-	0	0.000
+chr1	14361	29370	NR_024540_mRNA	0	-	4	51390.102
+chr1	17368	17436	NR_106918_exon_1	0	-	0	0.000
+chr1	17368	17436	NR_106918_mRNA	0	-	0	0.000
+chr1	17368	17436	NR_107062_exon_1	0	-	0	0.000
+chr1	17368	17436	NR_107062_mRNA	0	-	0	0.000
+chr1	35174	35276	NR_026818_intron_2	0	-	0	0.000
+chr1	35481	35720	NR_026818_intron_1	0	-	0	0.000
+chr1	34610	35174	NR_026818_exon_3	0	-	0	0.000
+chr1	35276	35481	NR_026818_exon_2	0	-	0	0.000
+chr1	35720	36081	NR_026818_exon_1	0	-	0	0.000
+chr1	34610	36081	NR_026818_mRNA	0	-	0	0.000
+chr1	35174	35276	NR_026820_intron_2	0	-	0	0.000
+chr1	35481	35720	NR_026820_intron_1	0	-	0	0.000
+chr1	34610	35174	NR_026820_exon_3	0	-	0	0.000
+chr1	35276	35481	NR_026820_exon_2	0	-	0	0.000
+chr1	35720	36081	NR_026820_exon_1	0	-	0	0.000
+chr1	34610	36081	NR_026820_mRNA	0	-	0	0.000
+chr1	69090	70008	NM_001005484_exon_1	0	+	0	0.000
+chr1	69090	70008	NM_001005484_mRNA	0	+	0	0.000
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/pairend_strandspecific_51mer_hg19_chr1_1-100000.bam
Binary file test-data/pairend_strandspecific_51mer_hg19_chr1_1-100000.bam has changed
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/testwig.Forward.wig
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/testwig.Forward.wig	Thu Jul 16 17:43:43 2015 -0400
@@ -0,0 +1,127 @@
+variableStep chrom=chr13
+variableStep chrom=chr12
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+variableStep chrom=chr15
+variableStep chrom=chr14
+variableStep chrom=chr19
+variableStep chrom=chr18
+variableStep chrom=chr8
+variableStep chrom=chr3
+variableStep chrom=chr1
+12674	1.00
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+variableStep chrom=chrY
+variableStep chrom=chrX
+variableStep chrom=chr9
+variableStep chrom=chrM
+variableStep chrom=chr22
+variableStep chrom=chr20
+variableStep chrom=chr21
+variableStep chrom=chr7
+variableStep chrom=chr6
+variableStep chrom=chr5
+variableStep chrom=chr4
+variableStep chrom=chr2
diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/testwig.Reverse.wig
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/testwig.Reverse.wig	Thu Jul 16 17:43:43 2015 -0400
@@ -0,0 +1,1686 @@
+variableStep chrom=chr13
+variableStep chrom=chr12
+variableStep chrom=chr11
+variableStep chrom=chr10
+variableStep chrom=chr17
+variableStep chrom=chr16
+variableStep chrom=chr15
+variableStep chrom=chr14
+variableStep chrom=chr19
+variableStep chrom=chr18
+variableStep chrom=chr8
+variableStep chrom=chr3
+variableStep chrom=chr1
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diff -r 2e6190c29c54 -r 6b33e31bda10 test-data/testwig.wig
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/testwig.wig	Thu Jul 16 17:43:43 2015 -0400
@@ -0,0 +1,1788 @@
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diff -r 2e6190c29c54 -r 6b33e31bda10 tool_dependencies.xml
--- a/tool_dependencies.xml	Tue Apr 21 10:27:06 2015 -0400
+++ b/tool_dependencies.xml	Thu Jul 16 17:43:43 2015 -0400
@@ -4,7 +4,7 @@
         <repository changeset_revision="f386d7431fe0" name="package_r_3_0_3" owner="iuc" toolshed="https://toolshed.g2.bx.psu.edu" />
     </package>
     <package name="numpy" version="1.7.1">
-        <repository changeset_revision="c7ae57300a77" name="package_numpy_1_7" owner="iuc" toolshed="https://toolshed.g2.bx.psu.edu" />
+        <repository changeset_revision="300877695495" name="package_numpy_1_7" owner="iuc" toolshed="https://toolshed.g2.bx.psu.edu" />
     </package>
     <package name="rseqc" version="2.4">
         <repository changeset_revision="8e7baa602cec" name="package_rseqc_2_4" owner="lparsons" toolshed="https://toolshed.g2.bx.psu.edu" />