# HG changeset patch
# User iuc
# Date 1489501401 14400
# Node ID 09846d5169fa501a548c2f154710a24a5a79550a
# Parent  f242ee1032770958f8cc15f5a57e5d2bf8659f7c
planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/rseqc commit 37fb1988971807c6a072e1afd98eeea02329ee83

diff -r f242ee103277 -r 09846d5169fa FPKM_count.xml
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/FPKM_count.xml	Tue Mar 14 10:23:21 2017 -0400
@@ -0,0 +1,132 @@
+<tool id="rseqc_FPKM_count" name="FPKM Count" version="@WRAPPER_VERSION@">
+    <description>calculates raw read count, FPM, and FPKM for each gene</description>
+
+    <macros>
+        <import>rseqc_macros.xml</import>
+    </macros>
+
+    <expand macro="requirements" />
+
+    <expand macro="stdio" />
+
+    <version_command><![CDATA[FPKM_count.py --version]]></version_command>
+
+    <command><![CDATA[
+        ln -sf '${input}' 'local_input.bam' &&
+        ln -sf '${input.metadata.bam_index}' 'local_input.bam.bai' &&
+        FPKM_count.py -i 'local_input.bam' -o output -r '${refgene}'
+
+        #if str($strand_type.strand_specific) == "pair"
+            -d
+            #if str($strand_type.pair_type) == "sd"
+                '1++,1--,2+-,2-+'
+            #else
+                '1+-,1-+,2++,2--'
+            #end if
+        #end if
+
+        #if str($strand_type.strand_specific) == "single"
+            -d
+            #if str($strand_type.single_type) == "s"
+                '++,--'
+            #else
+                '+-,-+'
+            #end if
+        #end if
+
+        @MULTIHITS@
+
+        $onlyexonic
+        --single-read="${singleread}"
+        ]]>
+    </command>
+
+    <inputs>
+        <expand macro="bam_param" />
+        <expand macro="refgene_param" />
+        <expand macro="strand_type_param" />
+        <expand macro="multihits_param" />
+        <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)"/>
+        <param name="singleread" type="select" label="How should read-pairs that only have one end mapped be counted?" help="(--single-read)">
+            <option value="1" selected="true">Treat it as a whole fragment (1)</option>
+            <option value="0.5">Treat it as a half fragment (0.5)</option>
+            <option value="0">Ignore it (0)</option>
+        </param>
+    </inputs>
+
+    <outputs>
+        <data format="xls" name="outputxls" from_work_dir="output.FPKM.xls"/>
+    </outputs>
+
+    <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.FPKM.xls"/>
+        </test>
+    </tests>
+
+    <help><![CDATA[
+FPKM_count.py
++++++++++++++
+
+Given a BAM file and reference gene model, this program will calculate the raw
+read count, FPM (fragments per million), and FPKM (fragments per million
+mapped reads per kilobase exon) for each gene in a BED file. 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.
+
+Inputs
+++++++++++++++
+
+Input BAM/SAM file
+    Alignment file in BAM/SAM format.
+
+Reference gene model
+    Gene model in BED format.
+
+Strand sequencing type (default=none)
+    See Infer Experiment tool if uncertain.
+
+Options
+++++++++++++++
+
+Skip Multiple Hit Reads
+    Use Multiple hit reads or use only uniquely mapped reads.
+
+Minimum mapping quality
+    Minimum mapping quality (phred scaled) for an alignment to be called
+    "uniquely mapped". default=30
+
+Only use exonic reads
+    Renders program only used exonic (UTR exons and CDS exons) reads,
+    otherwise use all reads.
+
+Single Reads
+    How to count read-pairs that only have one end mapped. 0: ignore it. 0.5:
+    treat it as half fragment. 1: treat it as whole fragment. default=1
+
+Sample Output
+++++++++++++++
+
+======  =========  =========  =========  =========  ===========  ==========  ============  ============
+#chrom  st         end        accession  mRNA_size  gene_strand  Frag_count  FPM           FPKM
+======  =========  =========  =========  =========  ===========  ==========  ============  ============
+chr1    100652477  100715409  NM_001918  10815.0    ‘-‘          5498.0      191.73788949  17.728884835
+chr1    175913961  176176380  NM_022457  2789.0     ‘-‘          923.0       32.188809021  11.541344217
+chr1    150980972  151008189  NM_021222  2977.0     ‘+’          687.0       23.958517657  8.0478729115
+chr1    6281252    6296044    NM_012405  4815.0     ‘-‘          1396.0      48.684265866  10.11095864
+chr1    20959947   20978004   NM_032409  2660.0     ‘+’          509.0       17.750925018  6.6732800821
+chr1    32479294   32509482   NM_006559  2891.0     ‘+’          2151.0      75.014223408  25.947500314
+======  =========  =========  =========  =========  ===========  ==========  ============  ============
+
+@ABOUT@
+
+]]>
+    </help>
+
+    <expand macro="citations" />
+
+</tool>
diff -r f242ee103277 -r 09846d5169fa RNA_fragment_size.xml
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/RNA_fragment_size.xml	Tue Mar 14 10:23:21 2017 -0400
@@ -0,0 +1,76 @@
+<tool id="rseqc_RNA_fragment_size" name="RNA fragment size" version="@WRAPPER_VERSION@">
+    <description>
+     calculates the fragment size for each gene/transcript
+    </description>
+
+    <macros>
+        <import>rseqc_macros.xml</import>
+    </macros>
+
+    <expand macro="requirements" />
+
+    <expand macro="stdio" />
+
+    <version_command><![CDATA[RNA_fragment_size.py --version]]></version_command>
+
+    <command><![CDATA[
+        ln -sf '${input}' 'input.bam' &&
+        ln -sf '$input.metadata.bam_index' 'input.bam.bai' &&
+        RNA_fragment_size.py -i 'input.bam' --refgene='${refgene}' --mapq=${mapq} --frag-num=${fragnum} > '${output}'
+        ]]>
+    </command>
+
+    <inputs>
+        <expand macro="bam_param" />
+        <expand macro="refgene_param" />
+        <expand macro="mapq_param" />
+        <param name="fragnum" type="integer" value="3" label="Minimum number of fragments (default: 3)" help="(--frag-num)" />
+    </inputs>
+
+    <outputs>
+        <data format="tabular" name="output" />
+    </outputs>
+
+    <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.RNA_fragment_size.txt" />
+        </test>
+    </tests>
+
+    <help><![CDATA[
+RNA_fragment_size.py
+++++++++++++++++++++
+
+Calculate fragment size for each gene/transcript. For each transcript, it will
+report : 1) Number of fragment that was used to estimate mean, median, std (see
+below). 2) mean of fragment size 3) median of fragment size 4) stdev of fragment
+size.
+
+Inputs
+++++++
+
+Input BAM/SAM file
+    Alignment file in BAM/SAM format.
+
+Reference gene model
+    Reference gene model in BED format. Must be strandard 12-column BED file.
+    [required]
+
+Minimum mapping quality
+    Minimum mapping quality for an alignment to be considered as "uniquely
+    mapped". default=30
+
+Minimum number of fragments
+    Minimum number of fragments. default=3
+
+@ABOUT@
+
+]]>
+
+    </help>
+
+    <expand macro="citations" />
+
+</tool>
diff -r f242ee103277 -r 09846d5169fa RPKM_count.xml
--- a/RPKM_count.xml	Tue May 03 16:36:57 2016 -0400
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,158 +0,0 @@
-<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>
-        <expand macro="requirement_package_numpy" />
-        <expand macro="requirement_package_rseqc" />
-    </requirements>
-
-    <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"
-            -d
-            #if str($strand_type.pair_type) == "sd"
-                '1++,1--,2+-,2-+'
-            #else
-                '1+-,1-+,2++,2--'
-            #end if
-        #end if
-
-        #if str($strand_type.strand_specific) == "single"
-            -d
-            #if str($strand_type.single_type) == "s"
-                '++,--'
-            #else
-                '+-,-+'
-            #end if
-        #end if
-
-        #if $multihits.skipmultihits
-            --skip-multi-hits
-            --mapq=$multihits.mapq
-        #end if
-
-        $onlyexonic
-        ]]>
-    </command>
-
-    <inputs>
-        <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>
-                <option value="pair">Pair-End RNA-seq</option>
-                <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" 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" 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>
-
-        <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>
-
-    <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
-+++++++++++++
-
-Given a BAM file and reference gene model, this program will calculate the raw count and RPKM
-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.
-
-Inputs
-++++++++++++++
-
-Input BAM/SAM file
-    Alignment file in BAM/SAM format.
-
-Reference gene model
-    Gene model in BED format.
-
-Strand sequencing type (default=none)
-    See Infer Experiment tool if uncertain.
-
-Options
-++++++++++++++
-
-Skip Multiple Hit Reads
-    Use Multiple hit reads or use only uniquely mapped reads.
-
-Only use exonic reads
-    Renders program only used exonic (UTR exons and CDS exons) reads, otherwise use all reads.
-
-Sample Output
-++++++++++++++
-
-=====   ========   ========   =====================    =====  ===========   =============   =============   ========  =========
-chrom   start      end        accession                score  gene strand   tag count (+)   tag count (-)   RPKM (+)  RPKM (-)
-=====   ========   ========   =====================    =====  ===========   =============   =============   ========  =========
-chr1    29213722   29313959   NM_001166007_intron_1    0      '+'             431             4329            0.086     0.863
-chr1    29314417   29319841   NM_001166007_intron_2    0      '+'             31              1               0.114     0.004
-chr1    29320054   29323726   NM_001166007_intron_3    0      '+'             32              0               0.174     0.000
-chr1    29213602   29213722   NM_001166007_exon_1      0      '+'             164             0               27.321    0.000
-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
-+++++++++++
-
-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.
-
-.. image:: http://rseqc.sourceforge.net/_static/logo.png
-
-.. _RSeQC: http://rseqc.sourceforge.net/
-]]>
-    </help>
-
-    <expand macro="citations" />
-
-</tool>
diff -r f242ee103277 -r 09846d5169fa RPKM_saturation.xml
--- a/RPKM_saturation.xml	Tue May 03 16:36:57 2016 -0400
+++ b/RPKM_saturation.xml	Tue Mar 14 10:23:21 2017 -0400
@@ -1,22 +1,18 @@
-<tool id="rseqc_RPKM_saturation" name="RPKM Saturation" version="2.4galaxy1">
+<tool id="rseqc_RPKM_saturation" name="RPKM Saturation" version="@WRAPPER_VERSION@">
     <description>calculates raw count and RPKM values for transcript at exon, intron, and mRNA level</description>
 
     <macros>
         <import>rseqc_macros.xml</import>
     </macros>
 
-    <requirements>
-        <expand macro="requirement_package_r" />
-        <expand macro="requirement_package_numpy" />
-        <expand macro="requirement_package_rseqc" />
-    </requirements>
+    <expand macro="requirements" />
 
     <expand macro="stdio" />
 
     <version_command><![CDATA[RPKM_saturation.py --version]]></version_command>
 
     <command><![CDATA[
-        RPKM_saturation.py -i $input -o output -r $refgene
+        RPKM_saturation.py -i '${input}' -o output -r '${refgene}'
 
         #if str($strand_type.strand_specific) == "pair"
             -d
@@ -36,51 +32,34 @@
             #end if
         #end if
 
-        -l $percentileFloor -u $percentileCeiling -s $percentileStep -c $rpkmCutoff
+        -l ${percentileFloor} -u ${percentileCeiling} -s ${percentileStep} -c ${rpkmCutoff}
         ]]>
     </command>
 
     <inputs>
-        <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>
-                <option value="pair">Pair-End RNA-seq</option>
-                <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" 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" 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>
+        <expand macro="bam_param" />
+        <expand macro="refgene_param" />
+        <expand macro="strand_type_param" />
         <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)" />
+        <expand macro="mapq_param" />
+        <expand macro="rscript_output_param" />
     </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 ${on_string} (PDF)"/>
+        <expand macro="pdf_output_data" filename="output.saturation.pdf" />
+        <data format="xls" name="outputxls" from_work_dir="output.eRPKM.xls" label="${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)"/>
+        <expand macro="rscript_output_data" filename="output.saturation.r" />
     </outputs>
 
     <tests>
         <test>
             <param name="input" value="pairend_strandspecific_51mer_hg19_random.bam"/>
             <param name="refgene" value="hg19.HouseKeepingGenes_30.bed"/>
+            <param name="rscript_output" value="true" />
             <output name="outputxls">
               <assert_contents>
                 <has_n_columns n="26" />
@@ -99,6 +78,7 @@
                 <has_line_matching expression="S5=c\(\d+\.\d+\)" />
               </assert_contents>
             </output>
+            <output name="outputpdf" file="output.saturation.pdf" compare="sim_size" />
         </test>
     </tests>
 
@@ -120,7 +100,7 @@
 expression level (i.e. RPKMreal). However, in practice one cannot know the RPKMreal. As a
 proxy, we use the RPKM estimated from total reads to approximate RPKMreal.
 
-.. image:: http://rseqc.sourceforge.net/_images/RelativeError.png
+.. image:: $PATH_TO_IMAGES/RelativeError.png
    :height: 80 px
    :width: 400 px
    :scale: 100 %
@@ -154,7 +134,7 @@
 3. output.saturation.r: R script to generate plot
 4. output.saturation.pdf:
 
-.. image:: http://rseqc.sourceforge.net/_images/saturation.png
+.. image:: $PATH_TO_IMAGES/saturation.png
    :height: 600 px
    :width: 600 px
    :scale: 80 %
@@ -173,23 +153,13 @@
     scatter.smooth(x,100*abs(rpkm-rpkm[length(rpkm)])/(rpkm[length(rpkm)]),type="p",ylab="Precent Relative Error",xlab="Resampling Percentage")
     dev.off()          #close graphical device
 
-.. image:: http://rseqc.sourceforge.net/_images/saturation_eg.png
+.. image:: $PATH_TO_IMAGES/saturation_eg.png
    :height: 600 px
    :width: 600 px
    :scale: 80 %
 
------
-
-About RSeQC
-+++++++++++
+@ABOUT@
 
-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.
-
-.. image:: http://rseqc.sourceforge.net/_static/logo.png
-
-.. _RSeQC: http://rseqc.sourceforge.net/
 ]]>
     </help>
 
diff -r f242ee103277 -r 09846d5169fa bam2wig.xml
--- a/bam2wig.xml	Tue May 03 16:36:57 2016 -0400
+++ b/bam2wig.xml	Tue Mar 14 10:23:21 2017 -0400
@@ -1,4 +1,4 @@
-<tool id="rseqc_bam2wig" name="BAM to Wiggle" version="2.4galaxy1">
+<tool id="rseqc_bam2wig" name="BAM to Wiggle" version="@WRAPPER_VERSION@">
     <description>
         converts all types of RNA-seq data from .bam to .wig
     </description>
@@ -7,20 +7,16 @@
         <import>rseqc_macros.xml</import>
     </macros>
 
-    <requirements>
-        <expand macro="requirement_package_r" />
-        <expand macro="requirement_package_numpy" />
-        <expand macro="requirement_package_rseqc" />
-    </requirements>
+    <expand macro="requirements" />
 
     <expand macro="stdio" />
 
     <version_command><![CDATA[bam2wig.py --version]]></version_command>
 
     <command><![CDATA[
-        ln -sfn '${input}' 'input.bam' &&
-        ln -sfn '${input.metadata.bam_index}' 'input.bam.bai' &&
-        bam2wig.py -i input.bam -s $chromsize -o outfile
+        ln -sf '${input}' 'input.bam' &&
+        ln -sf '${input.metadata.bam_index}' 'input.bam.bai' &&
+        bam2wig.py -i 'input.bam' -s '${chromsize}' -o outfile
 
         #if str($strand_type.strand_specific) == "pair"
             -d
@@ -40,57 +36,28 @@
             #end if
         #end if
 
-        #if $wigsum.wigsum_type
-            -t $wigsum.totalwig
+        #if str($wigsum_type.wigsum_type_selector) == "normalize":
+            -t ${wigsum.totalwig}
         #end if
-        #if $multihits.skipmultihits
-            --skip-multi-hits
-            --mapq=$multihits.mapq
-        #end if
-        2>&1
+
+        @MULTIHITS@
         ]]>
     </command>
     <inputs>
-        <param name="input" type="data" label="Input .bam File" format="bam" help="(--input-file)"/>
+        <expand macro="bam_param" />
         <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)" />
+        <expand macro="multihits_param" />
+        <conditional name="wigsum_type">
+            <param name="wigsum_type_selector" type="select" label="Normalization">
+                <option value="normalize">Normalize to specified sum</option>
+                <option value="raw" selected="true">Do not normalize</option>
+            </param>
+            <when value="normalize">
+                <param name="totalwig" value="" type="integer" label="specified wigsum" help="(--wigsum)"/>
             </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" help="(--wigsum)"/>
-            </when>
-            <when value="false"/>
+            <when value="raw"/>
         </conditional>
-
-        <conditional name="strand_type">
-            <param name="strand_specific" type="select" label="Strand-specific?" value="none">
-                <option value="none">none</option>
-                <option value="pair">Pair-End RNA-seq</option>
-                <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" 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" 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>
+        <expand macro="strand_type_param" />
     </inputs>
 
     <outputs>
@@ -114,8 +81,8 @@
         <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"/>
+            <param name="multihits_type.multihits_type_selector" value="skipmultihits"/>
+            <param name="multihits_type.mapq" value="20"/>
             <output name="output" file="testwig.wig"/>
         </test>
         <test>
@@ -165,22 +132,11 @@
 If RNA-seq is not strand specific, one wig file will be generated, if RNA-seq
 is strand specific, two wig files corresponding to Forward and Reverse will be generated.
 
------
-
-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.
-
-.. image:: http://rseqc.sourceforge.net/_static/logo.png
-
-.. _RSeQC: http://rseqc.sourceforge.net/
+@ABOUT@
 
 .. _UCSC: http://genome.ucsc.edu/index.html
 .. _IGB: http://bioviz.org/igb/
-.. _IGV: http://www.broadinstitute.org/igv/home
+.. _IGV: http://software.broadinstitute.org/software/igv/
 .. _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
diff -r f242ee103277 -r 09846d5169fa bam_stat.xml
--- a/bam_stat.xml	Tue May 03 16:36:57 2016 -0400
+++ b/bam_stat.xml	Tue Mar 14 10:23:21 2017 -0400
@@ -1,4 +1,4 @@
-<tool id="rseqc_bam_stat" name="BAM/SAM Mapping Stats" version="2.4galaxy1">
+<tool id="rseqc_bam_stat" name="BAM/SAM Mapping Stats" version="@WRAPPER_VERSION@">
     <description>
         reads mapping statistics for a provided BAM or SAM file.
     </description>
@@ -7,23 +7,20 @@
         <import>rseqc_macros.xml</import>
     </macros>
 
-    <requirements>
-        <expand macro="requirement_package_numpy" />
-        <expand macro="requirement_package_rseqc" />
-    </requirements>
+    <expand macro="requirements" />
 
     <expand macro="stdio" />
 
     <version_command><![CDATA[bam_stat.py --version]]></version_command>
 
     <command><![CDATA[
-        bam_stat.py -i $input -q $mapq 2> $output
+        bam_stat.py -i '${input}' -q ${mapq} > '${output}'
         ]]>
     </command>
 
     <inputs>
-        <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)" />
+        <expand macro="bam_param" />
+        <expand macro="mapq_param" />
     </inputs>
 
     <outputs>
@@ -32,8 +29,8 @@
 
     <tests>
         <test>
-            <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam"/>
-            <output name="output" file="bamstats.txt"/>
+            <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam" />
+            <output name="output" file="output.bamstats.txt" />
         </test>
     </tests>
 
@@ -52,10 +49,10 @@
 ++++++++++++++
 
 Input BAM/SAM file
-	Alignment file in BAM/SAM format.
+    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
 ++++++++++++++
@@ -65,19 +62,7 @@
 - Uniquely mapped Reads = {Reads map to '+'} + {Reads map to '-'}
 - Uniquely mapped Reads = {Splice reads} + {Non-splice reads}
 
------
-
-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.
-
-.. image:: http://rseqc.sourceforge.net/_static/logo.png
-
-.. _RSeQC: http://rseqc.sourceforge.net/
+@ABOUT@
 
 ]]>
     </help>
diff -r f242ee103277 -r 09846d5169fa clipping_profile.xml
--- a/clipping_profile.xml	Tue May 03 16:36:57 2016 -0400
+++ b/clipping_profile.xml	Tue Mar 14 10:23:21 2017 -0400
@@ -1,4 +1,4 @@
-<tool id="rseqc_clipping_profile" name="Clipping Profile" version="2.4galaxy1">
+<tool id="rseqc_clipping_profile" name="Clipping Profile" version="@WRAPPER_VERSION@">
     <description>
      estimates clipping profile of RNA-seq reads from BAM or SAM file
     </description>
@@ -7,37 +7,42 @@
         <import>rseqc_macros.xml</import>
     </macros>
 
-    <requirements>
-        <expand macro="requirement_package_r" />
-        <expand macro="requirement_package_numpy" />
-        <expand macro="requirement_package_rseqc" />
-    </requirements>
+    <expand macro="requirements" />
 
     <expand macro="stdio" />
 
     <version_command><![CDATA[clipping_profile.py --version]]></version_command>
 
     <command><![CDATA[
-        clipping_profile.py -i $input -o output
+        clipping_profile.py -i '${input}' -o output -q ${mapq} -s "${layout}"
         ]]>
     </command>
 
     <inputs>
-        <param name="input" type="data" label="Input .bam File" format="bam" help="(--input-file)"/>
+        <expand macro="bam_param" />
+        <expand macro="mapq_param" />
+        <expand macro="layout_param" />
+        <expand macro="rscript_output_param" />
     </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" />
+        <expand macro="pdf_output_data" filename="output.clipping_profile.pdf" />
+        <expand macro="xls_output_data" filename="output.clipping_profile.xls" />
+        <expand macro="rscript_output_data" filename="output.clipping_profile.r" />
     </outputs>
 
     <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"/>
+            <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam" />
+            <output name="outputpdf" file="output.clipping_profile.pdf" compare="sim_size" />
+            <output name="outputxls" file="output.clipping_profile.xls" />
+        </test>
+        <test>
+            <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam" />
+            <param name="rscript_output" value="true" />
+            <output name="outputpdf" file="output.clipping_profile.pdf" compare="sim_size" />
+            <output name="outputxls" file="output.clipping_profile.xls" />
+            <output name="outputr" file="output.clipping_profile.r" />
         </test>
     </tests>
 
@@ -53,29 +58,25 @@
 ++++++++++++++
 
 Input BAM/SAM file
-	Alignment file in BAM/SAM format.
+    Alignment file in BAM/SAM format.
 
+Minimum mapping quality
+    Minimum mapping quality for an alignment to be considered as "uniquely
+    mapped". default=30
+
+Sequencing layout
+    Denotes whether the sequecing was single-end (SE) or paired-end (PE).
 
 Sample Output
 ++++++++++++++
 
-.. image:: http://rseqc.sourceforge.net/_images/clipping_good.png
+.. image:: $PATH_TO_IMAGES/clipping_good.png
    :height: 600 px
    :width: 600 px
    :scale: 80 %
 
------
-
-About RSeQC
-+++++++++++
+@ABOUT@
 
-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.
-
-.. image:: http://rseqc.sourceforge.net/_static/logo.png
-
-.. _RSeQC: http://rseqc.sourceforge.net/
 ]]>
     </help>
 
diff -r f242ee103277 -r 09846d5169fa deletion_profile.xml
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/deletion_profile.xml	Tue Mar 14 10:23:21 2017 -0400
@@ -0,0 +1,87 @@
+<tool id="rseqc_deletion_profile" name="Deletion Profile" version="@WRAPPER_VERSION@">
+    <description>
+     calculates the distributions of deleted nucleotides across reads
+    </description>
+
+    <macros>
+        <import>rseqc_macros.xml</import>
+    </macros>
+
+    <expand macro="requirements" />
+
+    <expand macro="stdio" />
+
+    <version_command><![CDATA[deletion_profile.py --version]]></version_command>
+
+    <command><![CDATA[
+        deletion_profile.py -i '${input}' -o output -l ${readlength} -n ${readnum} -q ${mapq}
+        ]]>
+    </command>
+
+    <inputs>
+        <expand macro="bam_param" />
+        <expand macro="readlength_param" />
+        <expand macro="readnum_param" />
+        <expand macro="mapq_param" />
+        <expand macro="rscript_output_param" />
+    </inputs>
+
+    <outputs>
+        <expand macro="pdf_output_data" filename="output.deletion_profile.pdf" />
+        <expand macro="xls_output_data" filename="output.deletion_profile.txt" />
+        <expand macro="rscript_output_data" filename="output.deletion_profile.r" />
+    </outputs>
+
+    <tests>
+        <test>
+            <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam" />
+            <param name="readlength" value="101" />
+            <param name="rscript_output" value="true" />
+            <output name="outputpdf" file="output.deletion_profile.pdf" compare="sim_size" />
+            <output name="outputxls" file="output.deletion_profile.txt" />
+            <output name="outputr" file="output.deletion_profile.r" />
+        </test>
+    </tests>
+
+    <help><![CDATA[
+deletion_profile.py
++++++++++++++++++++
+
+Calculate the distributions of deleted nucleotides across reads.
+
+Inputs
+++++++
+
+Input BAM/SAM file
+    Alignment file in BAM/SAM format.
+
+Alignment length of read
+    It is usually set to the orignial read length. For example, all these cigar
+    strings ("101M", "68M140N33M", "53M1D48M") suggest the read alignment
+    length is 101. [required]
+
+Number of aligned reads used
+    Number of aligned reads with deletions used to calculate the deletion
+    profile. default=1000000
+
+Minimum mapping quality
+    Minimum mapping quality for an alignment to be considered as "uniquely
+    mapped". default=30
+
+Sample Output
+++++++++++++++
+
+.. image:: $PATH_TO_IMAGES/out.deletion_profile.png
+   :height: 600 px
+   :width: 600 px
+   :scale: 80 %
+
+@ABOUT@
+
+]]>
+
+    </help>
+
+    <expand macro="citations" />
+
+</tool>
diff -r f242ee103277 -r 09846d5169fa geneBody_coverage.xml
--- a/geneBody_coverage.xml	Tue May 03 16:36:57 2016 -0400
+++ b/geneBody_coverage.xml	Tue Mar 14 10:23:21 2017 -0400
@@ -1,4 +1,4 @@
-<tool id="rseqc_geneBody_coverage" name="Gene Body Converage (BAM)" version="2.4galaxy2">
+<tool id="rseqc_geneBody_coverage" name="Gene Body Converage (BAM)" version="@WRAPPER_VERSION@">
   <description>
     Read coverage over gene body.
   </description>
@@ -7,121 +7,117 @@
     <import>rseqc_macros.xml</import>
   </macros>
 
-  <requirements>
-    <expand macro="requirement_package_r" />
-    <expand macro="requirement_package_numpy" />
-    <expand macro="requirement_package_rseqc" />
-  </requirements>
+    <expand macro="requirements" />
 
   <expand macro="stdio" />
 
   <version_command><![CDATA[geneBody_coverage.py --version]]></version_command>
 
   <command><![CDATA[
+    #import re
+    #set $input_list = []
     #for $i, $input in enumerate($inputs):
-    #set $index = $i+1
-    #set $safename = ''.join(c in '_0123456789abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ' and c or '_' for c in $input.display_name)
-    #set $fname = 'd' + str($index) + '_' + str($safename) + ".bam"
-    ln -s '$input' '${fname}' &&
-    ln -s '$input.metadata.bam_index' '${fname}.bai' &&
-    echo '${fname}' >> input_list.txt &&
+        #set $safename = re.sub('[^\w\-_]', '_', $input.element_identifier)
+        #if $safename in $input_list:
+            #set $safename = str($safename) + "." + str($i)
+        #end if
+        $input_list.append($safename)
+        ln -sf '${input}' '${safename}.bam' &&
+        ln -sf '${input.metadata.bam_index}' '${safename}.bam.bai' &&
+        echo '${safename}.bam' >> 'input_list.txt' &&
     #end for
-    geneBody_coverage.py -i input_list.txt -r $refgene --minimum_length $minimum_length -o output
+    geneBody_coverage.py -i 'input_list.txt' -r '${refgene}' --minimum_length ${minimum_length} -o output
     ]]>
   </command>
 
   <inputs>
-    <param name="inputs" type="data" label="Input .bam File(s)" format="bam" help="(--input-file)" multiple="true"/>
-    <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)." />
+    <param name="inputs" type="data" label="Input .bam file(s)" format="bam" help="(--input-file)" multiple="true"/>
+    <expand macro="refgene_param" />
+    <param name="minimum_length" type="integer" value="100" label="Minimum mRNA length (default: 100)" help="Minimum mRNA length in bp, mRNA that are shorter than this value will be skipped (--minimum_length)." />
+    <expand macro="rscript_output_param" />
   </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 ${on_string} (HeatMap PDF)">
+    <data name="outputcurvespdf" format="pdf" from_work_dir="output.geneBodyCoverage.curves.pdf" label="${tool.name} on ${on_string} (Curves pdf)" />
+    <data name="outputheatmappdf" format="pdf" from_work_dir="output.geneBodyCoverage.heatMap.pdf" label="${tool.name} on ${on_string} (HeatMap pdf)">
       <filter>len(inputs) >= 3</filter>
     </data>
-    <data name="outputr" format="txt" from_work_dir="output.geneBodyCoverage.r" label="${tool.name} on ${on_string} (R Script)" />
-    <data name="outputtxt" format="txt" from_work_dir="output.geneBodyCoverage.txt" label="${tool.name} on ${on_string} (Text)" />
+    <expand macro="rscript_output_data" filename="output.geneBodyCoverage.r" />
+    <data name="outputtxt" format="txt" from_work_dir="output.geneBodyCoverage.txt" label="${tool.name} on ${on_string} (text)" />
   </outputs>
 
   <!-- PDF Files contain R version, must avoid checking for diff -->
   <tests>
     <test>
-      <param name="inputs" 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"/>
+      <param name="inputs" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam" />
+      <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed" />
+      <param name="rscript_output" value="true" />
+      <output name="outputcurvespdf" file="output.geneBodyCoverage.curves.pdf" compare="sim_size" />
+      <output name="outputr" file="output.geneBodyCoverage.r" />
+      <output name="outputtxt" file="output.geneBodyCoverage.txt" />
     </test>
     <test>
-      <param name="inputs" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam,pairend_strandspecific_51mer_hg19_chr1_1-100000.bam,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="outputheatmappdf" file="output2.geneBodyCoverage.heatMap.pdf"/> -->
-      <output name="outputr" file="output2.geneBodycoverage.r"/>
-      <output name="outputtxt" file="output2.geneBodyCoverage.txt"/>
+      <param name="inputs" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam,pairend_strandspecific_51mer_hg19_chr1_1-100000.bam,pairend_strandspecific_51mer_hg19_chr1_1-100000.bam" />
+      <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed" />
+      <param name="rscript_output" value="true" />
+      <output name="outputcurvespdf" file="output2.geneBodyCoverage.curves.pdf" compare="sim_size" />
+      <output name="outputheatmappdf" file="output2.geneBodyCoverage.heatMap.pdf" compare="sim_size" />
+      <output name="outputr" file="output2.geneBodyCoverage.r" />
+      <output name="outputtxt" file="output2.geneBodyCoverage.txt" />
     </test>
 
   </tests>
 
   <help><![CDATA[
-    ## geneBody_coverage.py
+## geneBody_coverage.py
 
-    Read coverage over gene body. This module is used to check if read coverage is uniform and if there is any 5\'/3\' bias. This module scales all transcripts to 100 nt and calculates the number of reads covering each nucleotide position. Finally, it generates plots illustrating the coverage profile along the gene body.
+Read coverage over gene body. This module is used to check if read coverage is uniform and if there is any 5\'/3\' bias. This module scales all transcripts to 100 nt and calculates the number of reads covering each nucleotide position. Finally, it generates plots illustrating the coverage profile along the gene body.
 
-    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.
+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 <http://en.wikipedia.org/wiki/Skewness#Pearson.27s_skewness_coefficients>`_
+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 <http://en.wikipedia.org/wiki/Skewness#Pearson.27s_skewness_coefficients>`_
 
-    .. image:: http://rseqc.sourceforge.net/_images/geneBody_workflow.png
-    :width: 800 px
-    :scale: 80 %
+.. image:: $PATH_TO_IMAGES/geneBody_workflow.png
+:width: 800 px
+:scale: 80 %
 
 
-    ## Inputs
+## Inputs
 
-    Input BAM/SAM file
+Input BAM/SAM file
     Alignment file in BAM/SAM format.
 
-    Reference gene model
+Reference gene model
     Gene Model in BED format.
 
-    Minimum mRNA length
+Minimum mRNA length
     Minimum mRNA length (bp). mRNA that are shorter than this value will be skipped (default is 100).
 
     ## Outputs
 
-    Text
+Text
     Table that includes the data used to generate the plots
 
-    R Script
+R Script
     R script file that reads the data and generates the plot
 
-    PDF
+PDF
     The final plot, in PDF format
 
-    Example plots:
-    .. image:: http://rseqc.sourceforge.net/_images/Aug_26.geneBodyCoverage.curves.png
-    :height: 600 px
-    :width: 600 px
-    :scale: 80 %
+Example plots:
+.. image:: $PATH_TO_IMAGES/Aug_26.geneBodyCoverage.curves.png
+:height: 600 px
+:width: 600 px
+:scale: 80 %
 
-    .. image:: http://rseqc.sourceforge.net/_images/Aug_26.geneBodyCoverage.heatMap.png
-    :height: 600 px
-    :width: 600 px
-    :scale: 80 %
-
-    ## About RSeQC
+.. image:: $PATH_TO_IMAGES/Aug_26.geneBodyCoverage.heatMap.png
+:height: 600 px
+:width: 600 px
+:scale: 80 %
 
-    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.
+@ABOUT@
 
-    .. image:: http://rseqc.sourceforge.net/_static/logo.png
-
-    .. _RSeQC: http://rseqc.sourceforge.net/
     ]]>
   </help>
 
diff -r f242ee103277 -r 09846d5169fa geneBody_coverage2.xml
--- a/geneBody_coverage2.xml	Tue May 03 16:36:57 2016 -0400
+++ b/geneBody_coverage2.xml	Tue Mar 14 10:23:21 2017 -0400
@@ -1,4 +1,4 @@
-<tool id="rseqc_geneBody_coverage2" name="Gene Body Converage (Bigwig)" version="2.4galaxy1">
+<tool id="rseqc_geneBody_coverage2" name="Gene Body Converage (Bigwig)" version="@WRAPPER_VERSION@">
     <description>
         Read coverage over gene body
     </description>
@@ -7,43 +7,38 @@
         <import>rseqc_macros.xml</import>
     </macros>
 
-    <requirements>
-        <expand macro="requirement_package_r" />
-        <expand macro="requirement_package_numpy" />
-        <expand macro="requirement_package_rseqc" />
-    </requirements>
+    <expand macro="requirements" />
 
     <expand macro="stdio" />
 
     <version_command><![CDATA[geneBody_coverage2.py --version]]></version_command>
 
     <command><![CDATA[
-        geneBody_coverage2.py -i $input -r $refgene -o output
+        geneBody_coverage2.py -i '${input}' -r '${refgene}' -o output
         ]]>
     </command>
 
     <inputs>
         <param name="input" type="data" label="Input bigwig file" format="bigwig" />
-        <param name="refgene" type="data" label="Reference Genome" format="bed" />
+        <expand macro="refgene_param" />
     </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 ${on_string} (Text)" />
+        <expand macro="pdf_output_data" filename="output.geneBodyCoverage.pdf" />
+        <data name="outputtxt" format="txt" from_work_dir="output.geneBodyCoverage.txt" label="${tool.name} on ${on_string} (text)" />
+        <expand macro="rscript_output_data" filename="output.geneBodyCoverage_plot.r" />
     </outputs>
 
-    <!-- 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"/>
+            <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bigwig" />
+            <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed" />
+            <param name="rscript_output" value="true" />
+            <output name="outputpdf" file="output.geneBodyCoverage2.curves.pdf" compare="sim_size" />
+            <output name="outputr" file="output.geneBodyCoverage2.r" />
+            <output name="outputtxt" file="output.geneBodyCoverage2.txt" />
         </test>
     </tests>
-    -->
 
     <help><![CDATA[
 geneBody_coverage2.py
@@ -69,23 +64,12 @@
 Read coverage over gene body. This module is used to check if reads coverage is uniform and if there is any 5’/3’ bias. This module scales all transcripts to 100 nt and calculates the number of reads covering each nucleotide position. Finally, it generates a plot illustrating the coverage profile along the gene body. NOTE: this module requires lots of memory for large BAM files, because it load the entire BAM file into memory. We add another script "geneBody_coverage2.py" into v2.3.1 which takes bigwig (instead of BAM) as input. It only use 200M RAM, but users need to convert BAM into WIG, and then WIG into BigWig.
 
 Example output:
-    .. image:: http://dldcc-web.brc.bcm.edu/lilab/liguow/RSeQC/figure/geneBody_coverage.png
+    .. image:: $PATH_TO_IMAGES/geneBody_coverage.png
         :height: 600 px
         :width: 600 px
         :scale: 80 %
 
------
-
-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.
-
-.. image:: http://rseqc.sourceforge.net/_static/logo.png
-
-.. _RSeQC: http://rseqc.sourceforge.net/
+@ABOUT@
 
 ]]>
     </help>
diff -r f242ee103277 -r 09846d5169fa infer_experiment.xml
--- a/infer_experiment.xml	Tue May 03 16:36:57 2016 -0400
+++ b/infer_experiment.xml	Tue Mar 14 10:23:21 2017 -0400
@@ -1,32 +1,29 @@
-<tool id="rseqc_infer_experiment" name="Infer Experiment" version="2.4galaxy1">
+<tool id="rseqc_infer_experiment" name="Infer Experiment" version="@WRAPPER_VERSION@">
     <description>speculates how RNA-seq were configured</description>
 
     <macros>
         <import>rseqc_macros.xml</import>
     </macros>
 
-    <requirements>
-        <expand macro="requirement_package_numpy" />
-        <expand macro="requirement_package_rseqc" />
-    </requirements>
+    <expand macro="requirements" />
 
     <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
-            > $output
+        infer_experiment.py -i '${input}' -r '${refgene}'
+            --sample-size ${sample_size}
+            --mapq ${mapq}
+            > '${output}'
             ]]>
     </command>
 
     <inputs>
-        <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" />
+        <expand macro="bam_param" />
+        <expand macro="refgene_param" />
+        <expand macro="sample_size_param" />
+        <expand macro="mapq_param" />
     </inputs>
 
     <outputs>
@@ -134,19 +131,7 @@
 
 *Conclusion*: This is single-end, strand specific RNA-seq data. Strandness of reads are concordant with strandness of reference gene.
 
-
------
-
-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.
-
-.. image:: http://rseqc.sourceforge.net/_static/logo.png
-
-.. _RSeQC: http://rseqc.sourceforge.net/
+@ABOUT@
 
 ]]>
     </help>
diff -r f242ee103277 -r 09846d5169fa inner_distance.xml
--- a/inner_distance.xml	Tue May 03 16:36:57 2016 -0400
+++ b/inner_distance.xml	Tue Mar 14 10:23:21 2017 -0400
@@ -1,55 +1,53 @@
-<tool id="rseqc_inner_distance" name="Inner Distance" version="2.4galaxy1">
+<tool id="rseqc_inner_distance" name="Inner Distance" version="@WRAPPER_VERSION@">
     <description>calculate the inner distance (or insert size) between two paired RNA reads</description>
 
     <macros>
         <import>rseqc_macros.xml</import>
     </macros>
 
-    <requirements>
-        <expand macro="requirement_package_r" />
-        <expand macro="requirement_package_numpy" />
-        <expand macro="requirement_package_rseqc" />
-    </requirements>
+    <expand macro="requirements" />
 
     <expand macro="stdio" />
 
     <version_command><![CDATA[inner_distance.py --version]]></version_command>
 
     <command><![CDATA[
-        inner_distance.py -i $input -o output -r $refgene
-            --sample-size $sample_size
-            --lower-bound $lowerBound
-            --upper-bound $upperBound
-            --step $step
-            --mapq $mapq
+        inner_distance.py -i '${input}' -o output -r '${refgene}'
+            --sample-size ${sample_size}
+            --lower-bound ${lowerBound}
+            --upper-bound ${upperBound}
+            --step ${step}
+            --mapq ${mapq}
         ]]>
     </command>
 
     <inputs>
-        <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)"/>
+        <expand macro="bam_sam_param" />
+        <expand macro="refgene_param" />
+        <expand macro="sample_size_param" />
         <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" />
+        <expand macro="mapq_param" />
+        <expand macro="rscript_output_param" />
     </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 ${on_string} (R Script)" />
+        <expand macro="pdf_output_data" filename="output.inner_distance_plot.pdf" />
+        <data format="txt" name="outputtxt" from_work_dir="output.inner_distance.txt" label="${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} (frequency text)" />
+        <expand macro="rscript_output_data" filename="output.inner_distance_plot.r" />
     </outputs>
 
     <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"/>
+            <param name="rscript_output" value="true" />
+            <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" compare="sim_size"/>
+            <output name="outputr" file="output.inner_distance_plot.r" />
         </test>
     </tests>
 
@@ -100,24 +98,12 @@
 3. output.inner_distance_plot.r: R script to generate histogram
 4. output.inner_distance_plot.pdf: histogram plot
 
-.. image:: http://rseqc.sourceforge.net/_images/inner_distance.png
+.. image:: $PATH_TO_IMAGES/inner_distance.png
    :height: 600 px
    :width: 600 px
    :scale: 80 %
 
-
------
-
-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.
-
-.. image:: http://rseqc.sourceforge.net/_static/logo.png
-
-.. _RSeQC: http://rseqc.sourceforge.net/
+@ABOUT@
 
 ]]>
     </help>
diff -r f242ee103277 -r 09846d5169fa insertion_profile.xml
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/insertion_profile.xml	Tue Mar 14 10:23:21 2017 -0400
@@ -0,0 +1,88 @@
+<tool id="rseqc_insertion_profile" name="Insertion Profile" version="@WRAPPER_VERSION@">
+    <description>
+     calculates the distribution of inserted nucleotides across reads
+    </description>
+
+    <macros>
+        <import>rseqc_macros.xml</import>
+    </macros>
+
+    <expand macro="requirements" />
+
+    <expand macro="stdio" />
+
+    <version_command><![CDATA[insertion_profile.py --version]]></version_command>
+
+    <command><![CDATA[
+        insertion_profile.py -i '${input}' -o output -q ${mapq} -s "${layout}"
+        ]]>
+    </command>
+
+    <inputs>
+        <expand macro="bam_param" />
+        <expand macro="mapq_param" />
+        <expand macro="layout_param" />
+        <expand macro="rscript_output_param" />
+    </inputs>
+
+    <outputs>
+        <expand macro="pdf_output_data" filename="output.insertion_profile.pdf" />
+        <expand macro="xls_output_data" filename="output.insertion_profile.xls" />
+        <expand macro="rscript_output_data" filename="output.insertion_profile.r" />
+    </outputs>
+
+    <tests>
+        <test>
+            <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam" />
+            <param name="rscript_output" value="true" />
+            <output name="outputpdf" file="output.insertion_profile.pdf" compare="sim_size" />
+            <output name="outputxls" file="output.insertion_profile.xls" />
+            <output name="outputr" file="output.insertion_profile.r" />
+        </test>
+    </tests>
+
+    <help><![CDATA[
+insertion_profile.py
+++++++++++++++++++++
+
+Calculate the distributions of inserted nucleotides across reads. Note that to
+use this funciton, CIGAR strings within SAM/BAM file should have ‘I’ operation.
+
+Inputs
+++++++
+
+Input BAM/SAM file
+    Alignment file in BAM/SAM format.
+
+Minimum mapping quality
+    Minimum mapping quality for an alignment to be considered as "uniquely
+    mapped". default=30
+
+Sequencing layout
+    Denotes whether the sequecing was single-end (SE) or paired-end (PE).
+
+Sample Output
+++++++++++++++
+
+Read-1 insertion profile:
+
+.. image:: $PATH_TO_IMAGES/out.insertion_profile.R1.png
+   :height: 600 px
+   :width: 600 px
+   :scale: 80 %
+
+Read-2 insertion profile:
+
+.. image:: $PATH_TO_IMAGES/out.insertion_profile.R2.png
+  :height: 600 px
+  :width: 600 px
+  :scale: 80 %
+
+@ABOUT@
+
+]]>
+    </help>
+
+    <expand macro="citations" />
+
+</tool>
diff -r f242ee103277 -r 09846d5169fa junction_annotation.xml
--- a/junction_annotation.xml	Tue May 03 16:36:57 2016 -0400
+++ b/junction_annotation.xml	Tue Mar 14 10:23:21 2017 -0400
@@ -1,15 +1,11 @@
-<tool id="rseqc_junction_annotation" name="Junction Annotation" version="2.4galaxy1">
+<tool id="rseqc_junction_annotation" name="Junction Annotation" version="@WRAPPER_VERSION@">
     <description>compares detected splice junctions to reference gene model</description>
 
     <macros>
         <import>rseqc_macros.xml</import>
     </macros>
 
-    <requirements>
-        <expand macro="requirement_package_r" />
-        <expand macro="requirement_package_numpy" />
-        <expand macro="requirement_package_rseqc" />
-    </requirements>
+    <expand macro="requirements" />
 
     <expand macro="stdio" />
 
@@ -17,36 +13,38 @@
 
     <command><![CDATA[
         junction_annotation.py
-            --input-file $input
-            --refgene $refgene
+            --input-file '${input}'
+            --refgene '${refgene}'
             --out-prefix output
-            --min-intron $min_intron
-            --mapq $mapq
+            --min-intron ${min_intron}
+            --mapq ${mapq}
         ]]>
     </command>
 
     <inputs>
-        <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" />
+        <expand macro="bam_sam_param" />
+        <expand macro="refgene_param" />
+        <expand macro="min_intron_param" />
+        <expand macro="mapq_param" />
+        <expand macro="rscript_output_param" />
     </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 ${on_string} (Splice Junction PDF)" />
+        <data format="pdf" name="outputpdf" from_work_dir="output.splice_events.pdf" label="${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)" />
+        <expand macro="xls_output_data" filename="output.junction.xls" />
+        <expand macro="rscript_output_data" filename="output.junction_plot.r" />
     </outputs>
 
     <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"/>
+            <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam" />
+            <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed" />
+            <param name="rscript_output" value="true" />
+            <output name="outputxls" file="output.junction.xls" />
+            <output name="outputr" file="output.junction_plot.r" />
+            <output name="outputpdf" file="output.splice_events.pdf" compare="sim_size" />
+            <output name="outputjpdf" file="output.splice_junction.pdf" compare="sim_size" />
         </test>
     </tests>
 
@@ -94,23 +92,13 @@
 3. output.splice_junction.pdf: plot of splice junctions
 4. output.splice_events.pdf: plot of splice events
 
-.. image:: http://rseqc.sourceforge.net/_images/junction.png
+.. image:: $PATH_TO_IMAGES/junction.png
    :height: 400 px
    :width: 850 px
    :scale: 80 %
 
------
-
-About RSeQC
-+++++++++++
+@ABOUT@
 
-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.
-
-.. image:: http://rseqc.sourceforge.net/_static/logo.png
-
-.. _RSeQC: http://rseqc.sourceforge.net/
 ]]>
     </help>
 
diff -r f242ee103277 -r 09846d5169fa junction_saturation.xml
--- a/junction_saturation.xml	Tue May 03 16:36:57 2016 -0400
+++ b/junction_saturation.xml	Tue Mar 14 10:23:21 2017 -0400
@@ -1,15 +1,11 @@
-<tool id="rseqc_junction_saturation" name="Junction Saturation" version="2.4galaxy1">
+<tool id="rseqc_junction_saturation" name="Junction Saturation" version="@WRAPPER_VERSION@">
     <description>detects splice junctions from each subset and compares them to reference gene model</description>
 
     <macros>
         <import>rseqc_macros.xml</import>
     </macros>
 
-    <requirements>
-        <expand macro="requirement_package_r" />
-        <expand macro="requirement_package_numpy" />
-        <expand macro="requirement_package_rseqc" />
-    </requirements>
+    <expand macro="requirements" />
 
     <expand macro="stdio" />
 
@@ -17,29 +13,32 @@
 
     <command><![CDATA[
         junction_saturation.py
-            --input-file $input
-            --refgene $refgene
+            --input-file '${input}'
+            --refgene '${refgene}'
             --out-prefix output
-            --min-intron $min_intron
-            --min-coverage $min_coverage
-            --mapq $mapq
-        #if $percentiles.specifyPercentiles
-            --percentile-floor $percentiles.lowBound
-            --percentile-ceiling $percentiles.upBound
-            --percentile-step $percentiles.percentileStep
+            --min-intron ${min_intron}
+            --min-coverage ${min_coverage}
+            --mapq ${mapq}
+        #if str($percentiles_type.percentiles_type_selector) == "specify":
+            --percentile-floor ${percentiles_type.lowBound}
+            --percentile-ceiling ${percentiles_type.upBound}
+            --percentile-step ${percentiles_type.percentileStep}
         #end if
         ]]>
     </command>
 
     <inputs>
-        <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)" />
+        <expand macro="bam_sam_param" />
+        <expand macro="refgene_param" />
+        <expand macro="min_intron_param" />
         <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">
+        <expand macro="mapq_param" />
+        <conditional name="percentiles_type">
+            <param name="percentiles_type_selector" type="select" label="Sampling bounds and frequency">
+                <option value="default" selected="true">Default sampling bounds and frequency</option>
+                <option value="specify">Specify sampling bounds and frequency</option>
+            </param>
+            <when value="specify">
                 <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>
@@ -50,20 +49,28 @@
                     <validator type="in_range" min="0" max="100" />
                 </param>
             </when>
-            <when value="false"/>
+            <when value="default"/>
         </conditional>
+        <expand macro="rscript_output_param" />
     </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)"/>
+        <expand macro="pdf_output_data" filename="output.junctionSaturation_plot.pdf" />
+        <expand macro="rscript_output_data" filename="output.junctionSaturation_plot.r" />
     </outputs>
 
     <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"/>
+            <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam" />
+            <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed" />
+            <param name="rscript_output" value="true" />
+            <output name="outputr" file="output.junctionSaturation_plot.r" compare="sim_size">
+                <assert_contents>
+                    <has_line line="pdf('output.junctionSaturation_plot.pdf')" />
+                    <has_line line="x=c(5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80,85,90,95,100)" />
+                </assert_contents>
+            </output>
+            <output name="outputpdf" file="output.junctionSaturation_plot.pdf" compare="sim_size" />
         </test>
     </tests>
 
@@ -105,26 +112,15 @@
 1. output.junctionSaturation_plot.r: R script to generate plot
 2. output.junctionSaturation_plot.pdf
 
-.. image:: http://rseqc.sourceforge.net/_images/junction_saturation.png
+.. image:: $PATH_TO_IMAGES/junction_saturation.png
    :height: 600 px
    :width: 600 px
    :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@
 
-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.
-
-.. image:: http://rseqc.sourceforge.net/_static/logo.png
-
-.. _RSeQC: http://rseqc.sourceforge.net/
 ]]>
     </help>
 
diff -r f242ee103277 -r 09846d5169fa mismatch_profile.xml
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/mismatch_profile.xml	Tue Mar 14 10:23:21 2017 -0400
@@ -0,0 +1,89 @@
+<tool id="rseqc_mismatch_profile" name="Mismatch Profile" version="@WRAPPER_VERSION@">
+    <description>
+     calculates the distribution of mismatches across reads
+    </description>
+
+    <macros>
+        <import>rseqc_macros.xml</import>
+    </macros>
+
+    <expand macro="requirements" />
+
+    <expand macro="stdio" />
+
+    <version_command><![CDATA[mismatch_profile.py --version]]></version_command>
+
+    <command><![CDATA[
+        mismatch_profile.py -i '${input}' -o output -l ${readlength} -n ${readnum} -q ${mapq}
+        ]]>
+    </command>
+
+    <inputs>
+        <expand macro="bam_param" />
+        <expand macro="readlength_param" />
+        <expand macro="readnum_param" />
+        <expand macro="mapq_param" />
+        <expand macro="rscript_output_param" />
+    </inputs>
+
+    <outputs>
+        <expand macro="pdf_output_data" filename="output.mismatch_profile.pdf" />
+        <expand macro="xls_output_data" filename="output.mismatch_profile.xls" />
+        <expand macro="rscript_output_data" filename="output.mismatch_profile.r" />
+    </outputs>
+
+    <tests>
+        <test>
+            <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam"/>
+            <param name="readlength" value="101" />
+            <param name="rscript_output" value="true" />
+            <output name="outputpdf" file="output.mismatch_profile.pdf" compare="sim_size" />
+            <output name="outputxls" file="output.mismatch_profile.xls"/>
+            <output name="outputr" file="output.mismatch_profile.r"/>
+        </test>
+    </tests>
+
+    <help><![CDATA[
+mismatch_profile.py
++++++++++++++++++++
+
+Calculate the distribution of mismatches across reads.
+
+Note that the “MD” tag must exist in BAM file.
+
+Inputs
+++++++
+
+Input BAM/SAM file
+    Alignment file in BAM/SAM format.
+
+Alignment length of read
+    It is usually set to the orignial read length. For example, all these cigar
+    strings ("101M", "68M140N33M", "53M1D48M") suggest the read alignment
+    length is 101. [required]
+
+Number of aligned reads used
+    Number of aligned reads with deletions used to calculate the deletion
+    profile. default=1000000
+
+Minimum mapping quality
+    Minimum mapping quality for an alignment to be considered as "uniquely
+    mapped". default=30
+
+Sample Output
+++++++++++++++
+
+.. image:: $PATH_TO_IMAGES/mismatch_profile.png
+   :height: 600 px
+   :width: 600 px
+   :scale: 80 %
+
+@ABOUT@
+
+]]>
+
+    </help>
+
+    <expand macro="citations" />
+
+</tool>
diff -r f242ee103277 -r 09846d5169fa read_GC.xml
--- a/read_GC.xml	Tue May 03 16:36:57 2016 -0400
+++ b/read_GC.xml	Tue Mar 14 10:23:21 2017 -0400
@@ -1,15 +1,11 @@
-<tool id="rseqc_read_GC" name="Read GC" version="2.4galaxy1">
+<tool id="rseqc_read_GC" name="Read GC" version="@WRAPPER_VERSION@">
     <description>determines GC% and read count</description>
 
     <macros>
         <import>rseqc_macros.xml</import>
     </macros>
 
-    <requirements>
-        <expand macro="requirement_package_r" />
-        <expand macro="requirement_package_numpy" />
-        <expand macro="requirement_package_rseqc" />
-    </requirements>
+    <expand macro="requirements" />
 
     <expand macro="stdio" />
 
@@ -17,28 +13,31 @@
 
     <command><![CDATA[
         read_GC.py
-            --input-file $input
+            --input-file '${input}'
             --out-prefix output
-            --mapq $mapq
+            --mapq ${mapq}
         ]]>
     </command>
 
     <inputs>
-        <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" />
+        <expand macro="bam_sam_param" />
+        <expand macro="mapq_param" />
+        <expand macro="rscript_output_param" />
     </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)" />
+        <expand macro="pdf_output_data" filename="output.GC_plot.pdf" />
+        <expand macro="xls_output_data" filename="output.GC.xls" />
+        <expand macro="rscript_output_data" filename="output.GC_plot.r" />
     </outputs>
 
     <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"/>
+            <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam" />
+            <param name="rscript_output" value="true" />
+            <output name="outputxls" file="output.GC.xls" />
+            <output name="outputr" file="output.GC_plot.r" />
+            <output name="outputpdf" file="output.GC_plot.pdf" compare="sim_size" />
         </test>
     </tests>
 
@@ -60,23 +59,13 @@
 2. output.GC_plot.r: R script to generate pdf file.
 3. output.GC_plot.pdf: graphical output generated from R script.
 
-.. image:: http://rseqc.sourceforge.net/_images/read_gc.png
+.. image:: $PATH_TO_IMAGES/read_gc.png
    :height: 600 px
    :width: 600 px
    :scale: 80 %
 
------
-
-About RSeQC
-+++++++++++
+@ABOUT@
 
-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.
-
-.. image:: http://rseqc.sourceforge.net/_static/logo.png
-
-.. _RSeQC: http://rseqc.sourceforge.net/
 ]]>
     </help>
 
diff -r f242ee103277 -r 09846d5169fa read_NVC.xml
--- a/read_NVC.xml	Tue May 03 16:36:57 2016 -0400
+++ b/read_NVC.xml	Tue Mar 14 10:23:21 2017 -0400
@@ -1,45 +1,45 @@
-<tool id="rseqc_read_NVC" name="Read NVC" version="2.4galaxy1">
+<tool id="rseqc_read_NVC" name="Read NVC" version="@WRAPPER_VERSION@">
     <description>to check the nucleotide composition bias</description>
 
     <macros>
         <import>rseqc_macros.xml</import>
     </macros>
 
-    <requirements>
-        <expand macro="requirement_package_r" />
-        <expand macro="requirement_package_numpy" />
-        <expand macro="requirement_package_rseqc" />
-    </requirements>
+    <expand macro="requirements" />
 
     <expand macro="stdio" />
 
     <version_command><![CDATA[read_NVC.py --version]]></version_command>
 
-    <command>
+    <command><![CDATA[
         read_NVC.py
-            --input-file $input
+            --input-file '${input}'
             --out-prefix output
-            $nx
-            --mapq $mapq
+            ${nx}
+            --mapq ${mapq}
+    ]]>
     </command>
 
     <inputs>
-        <param name="input" type="data" format="bam,sam" label="input bam/sam file" help="(--input-file)"/>
+        <expand macro="bam_sam_param" />
         <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" />
+        <expand macro="mapq_param" />
+        <expand macro="rscript_output_param" />
     </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)" />
+        <expand macro="pdf_output_data" filename="output.NVC_plot.pdf" />
+        <expand macro="xls_output_data" filename="output.NVC.xls" />
+        <expand macro="rscript_output_data" filename="output.NVC_plot.r" />
     </outputs>
 
     <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"/>
+            <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam" />
+            <param name="rscript_output" value="true" />
+            <output name="outputxls" file="output.NVC.xls" />
+            <output name="outputr" file="output.NVC_plot.r" />
+            <output name="outputpdf" file="output.NVC_plot.pdf" compare="sim_size" />
         </test>
     </tests>
 
@@ -76,23 +76,13 @@
 3. output.NVC_plot.pdf: NVC plot.
 
 
-.. image:: http://rseqc.sourceforge.net/_images/NVC_plot.png
+.. image:: $PATH_TO_IMAGES/NVC_plot.png
    :height: 600 px
    :width: 600 px
    :scale: 80 %
 
------
-
-About RSeQC
-+++++++++++
+@ABOUT@
 
-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.
-
-.. image:: http://rseqc.sourceforge.net/_static/logo.png
-
-.. _RSeQC: http://rseqc.sourceforge.net/
 ]]>
     </help>
 
diff -r f242ee103277 -r 09846d5169fa read_distribution.xml
--- a/read_distribution.xml	Tue May 03 16:36:57 2016 -0400
+++ b/read_distribution.xml	Tue Mar 14 10:23:21 2017 -0400
@@ -1,27 +1,24 @@
-<tool id="rseqc_read_distribution" name="Read Distribution" version="2.4galaxy1">
+<tool id="rseqc_read_distribution" name="Read Distribution" version="@WRAPPER_VERSION@">
     <description>calculates how mapped reads were distributed over genome feature</description>
 
     <macros>
         <import>rseqc_macros.xml</import>
     </macros>
 
-    <requirements>
-        <expand macro="requirement_package_numpy" />
-        <expand macro="requirement_package_rseqc" />
-    </requirements>
+    <expand macro="requirements" />
 
     <expand macro="stdio" />
 
     <version_command><![CDATA[read_distribution.py --version]]></version_command>
 
     <command><![CDATA[
-        read_distribution.py -i $input -r $refgene > $output
+        read_distribution.py -i '${input}' -r '${refgene}' > '${output}'
         ]]>
     </command>
 
     <inputs>
-        <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)"/>
+        <expand macro="bam_sam_param" />
+        <expand macro="refgene_param" />
     </inputs>
 
     <outputs>
@@ -89,18 +86,8 @@
 TES_down_10kb       140361190           896882              6.39
 ===============     ============        ===========         ===========
 
------
-
-About RSeQC
-+++++++++++
+@ABOUT@
 
-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.
-
-.. image:: http://rseqc.sourceforge.net/_static/logo.png
-
-.. _RSeQC: http://rseqc.sourceforge.net/
 ]]>
     </help>
 
diff -r f242ee103277 -r 09846d5169fa read_duplication.xml
--- a/read_duplication.xml	Tue May 03 16:36:57 2016 -0400
+++ b/read_duplication.xml	Tue Mar 14 10:23:21 2017 -0400
@@ -1,43 +1,43 @@
-<tool id="rseqc_read_duplication" name="Read Duplication" version="2.4galaxy1">
+<tool id="rseqc_read_duplication" name="Read Duplication" version="@WRAPPER_VERSION@">
     <description>determines reads duplication rate with sequence-based and mapping-based strategies</description>
 
     <macros>
         <import>rseqc_macros.xml</import>
     </macros>
 
-    <requirements>
-        <expand macro="requirement_package_r" />
-        <expand macro="requirement_package_numpy" />
-        <expand macro="requirement_package_rseqc" />
-    </requirements>
+    <expand macro="requirements" />
 
     <expand macro="stdio" />
 
     <version_command><![CDATA[read_duplication.py --version]]></version_command>
 
     <command><![CDATA[
-        read_duplication.py -i $input -o output -u $upLimit
+        read_duplication.py -i '${input}' -o output -u ${upLimit} -q ${mapq}
         ]]>
     </command>
 
     <inputs>
-        <param name="input" type="data" format="bam,sam" label="input bam/sam file" help="(--input-file)"/>
+        <expand macro="bam_sam_param" />
         <param name="upLimit" type="integer" label="Upper Limit of Plotted Duplicated Times (default=500)" value="500" help="(--up-limit)"/>
+        <expand macro="mapq_param" />
+        <expand macro="rscript_output_param" />
     </inputs>
 
     <outputs>
-        <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 ${on_string} (PDF)" />
+        <expand macro="pdf_output_data" filename="output.DupRate_plot.pdf" />
+        <data format="xls" name="outputxls" from_work_dir="output.pos.DupRate.xls" label="${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)"/>
+        <expand macro="rscript_output_data" filename="output.DupRate_plot.r" />
     </outputs>
 
     <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"/>
+            <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam" />
+            <param name="rscript_output" value="true" />
+            <output name="outputxls" file="output.pos.DupRate.xls" />
+            <output name="outputseqxls" file="output.seq.DupRate.xls" />
+            <output name="outputr" file="output.DupRate_plot.r" />
+            <output name="outputpdf" file="output.DupRate_plot.pdf" compare="sim_size" />
         </test>
     </tests>
 
@@ -67,23 +67,13 @@
 3. output.DupRate_plot.r: R script to generate pdf file
 4. output.DupRate_plot.pdf: graphical output generated from R script
 
-.. image:: http://rseqc.sourceforge.net/_images/duplicate.png
+.. image:: $PATH_TO_IMAGES/duplicate.png
    :height: 600 px
    :width: 600 px
    :scale: 80 %
 
------
-
-About RSeQC
-+++++++++++
+@ABOUT@
 
-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.
-
-.. image:: http://rseqc.sourceforge.net/_static/logo.png
-
-.. _RSeQC: http://rseqc.sourceforge.net/
 ]]>
     </help>
 
diff -r f242ee103277 -r 09846d5169fa read_hexamer.xml
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/read_hexamer.xml	Tue Mar 14 10:23:21 2017 -0400
@@ -0,0 +1,137 @@
+<tool id="rseqc_read_hexamer" name="Hexamer frequency" version="@WRAPPER_VERSION@">
+    <description>
+        calculates hexamer (6mer) frequency for reads, genomes, and mRNA sequences
+    </description>
+
+    <macros>
+        <import>rseqc_macros.xml</import>
+    </macros>
+
+    <expand macro="requirements" />
+
+    <expand macro="stdio" />
+
+    <version_command><![CDATA[read_hexamer.py --version]]></version_command>
+
+    <command><![CDATA[
+        #import re
+        #set $input_list = []
+        #for $i, $input in enumerate($inputs):
+
+            #set $safename = re.sub('[^\w\-_]', '_', $input.element_identifier)
+            #if $safename in $input_list:
+                #set $safename = str($safename) + "." + str($i)
+            #end if
+            $input_list.append($safename)
+
+            #if $input.is_of_type("fastq.gz", "fastqsanger.gz"):
+                gunzip -c '${input}' > "${safename}" &&
+            #else:
+                ln -sf '${input}' "${safename}" &&
+            #end if
+        #end for
+        read_hexamer.py -i '${ ','.join( [ $name for $name in $input_list ] ) }'
+        #if $refgenome:
+            -r '${refgenome}'
+        #end if
+        #if $refgene:
+            -g '${refgene}'
+        #end if
+        > '${output}'
+        ]]>
+    </command>
+
+    <inputs>
+        <param name="inputs" type="data" label="Read sequences in fasta or fastq format" format="fasta,fastq,fastqsanger,fastq.gz,fastqsanger.gz" help="(--input)" multiple="true" />
+        <param name="refgenome" type="data" label="Reference genome seqeunce (fasta)" format="fasta" optional="true" help="(--refgenome)" />
+        <param name="refgene" type="data" label="Reference mRNA sequence (fasta)" format="fasta" optional="true" help="(--refgene)" />
+    </inputs>
+
+    <outputs>
+        <data name="output" format="tabular" label="${tool.name} on ${on_string}" />
+    </outputs>
+
+    <tests>
+        <test>
+            <param name="inputs" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.R1.fastq"/>
+            <output name="output">
+                <assert_contents>
+                    <has_line line="Hexamer&#009;pairend_strandspecific_51mer_hg19_chr1_1-100000_R1_fastq" />
+                    <has_line line="AAAAAA&#009;0.00217391304348" />
+                </assert_contents>
+            </output>
+        </test>
+        <test>
+            <param name="inputs" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.R1.fastq.gz" ftype="fastqsanger.gz"/>
+            <output name="output">
+                <assert_contents>
+                    <has_line line="Hexamer&#009;pairend_strandspecific_51mer_hg19_chr1_1-100000_R1_fastq_gz" />
+                    <has_line line="AAAAAA&#009;0.00217391304348" />
+                </assert_contents>
+            </output>
+        </test>
+        <test>
+            <param name="inputs" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.R1.fastq,pairend_strandspecific_51mer_hg19_chr1_1-100000.R2.fastq"/>
+            <output name="output">
+                <assert_contents>
+                    <has_line line="Hexamer&#009;pairend_strandspecific_51mer_hg19_chr1_1-100000_R1_fastq&#009;pairend_strandspecific_51mer_hg19_chr1_1-100000_R2_fastq" />
+                    <has_line line="AAAAAA&#009;0.00217391304348&#009;0.00534759358289" />
+                </assert_contents>
+            </output>
+        </test>
+        <test>
+            <param name="inputs" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.R1.fastq,pairend_strandspecific_51mer_hg19_chr1_1-100000.R1.fastq"/>
+            <output name="output">
+                <assert_contents>
+                    <has_line line="Hexamer&#009;pairend_strandspecific_51mer_hg19_chr1_1-100000_R1_fastq&#009;pairend_strandspecific_51mer_hg19_chr1_1-100000_R1_fastq.1" />
+                    <has_line line="AAAAAA&#009;0.00217391304348&#009;0.00217391304348" />
+                </assert_contents>
+            </output>
+        </test>
+        <!-- Unable to test with collections at the moment (requires type="data_collection" on the input)
+        <test>
+            <param name="inputs">
+                <collection type="list">
+                    <element name="read_1" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.R1.fastq" />
+                    <element name="read_2" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.R2.fastq" />
+                </collection>
+            </param>
+            <output name="output" file="output.read_hexamer.2.txt" />
+        </test>
+        -->
+    </tests>
+
+    <help><![CDATA[
+read_hexamer.py
++++++++++++++++++++++
+
+Calculate hexamer (6mer) frequency. If ‘-r’ was specified, hexamer frequency
+is also calculated for the reference genome. If ‘-g’ was provided, hexamer
+frequency is also calculated for the mRNA sequences.
+
+Inputs
+++++++++++++++
+
+Input reads file
+    Read sequences in fasta or fastq format.
+
+Reference Genome
+    Reference genome sequence in fasta format.
+
+Reference Gene
+    Reference mRNA sequences in fasta format.
+
+
+Outputs
+++++++++++++++
+
+Tabular file of hexamer frequences in for each input.
+
+@ABOUT@
+
+]]>
+    </help>
+
+    <expand macro="citations" />
+
+</tool>
diff -r f242ee103277 -r 09846d5169fa read_quality.xml
--- a/read_quality.xml	Tue May 03 16:36:57 2016 -0400
+++ b/read_quality.xml	Tue Mar 14 10:23:21 2017 -0400
@@ -1,15 +1,11 @@
-<tool id="rseqc_read_quality" name="Read Quality" version="2.4galaxy1">
+<tool id="rseqc_read_quality" name="Read Quality" version="@WRAPPER_VERSION@">
     <description>determines Phred quality score</description>
 
     <macros>
         <import>rseqc_macros.xml</import>
     </macros>
 
-    <requirements>
-        <expand macro="requirement_package_r" />
-        <expand macro="requirement_package_numpy" />
-        <expand macro="requirement_package_rseqc" />
-    </requirements>
+    <expand macro="requirements" />
 
     <expand macro="stdio" />
 
@@ -17,29 +13,33 @@
 
     <command><![CDATA[
         read_quality.py
-            --input-file $input
+            --input-file '${input}'
             --out-prefix output
-            -r $reduce
-            --mapq $mapq
+            -r ${reduce}
+            --mapq ${mapq}
         ]]>
     </command>
 
     <inputs>
-        <param name="input" type="data" format="bam,sam" label="input bam/sam file" help="(--input-file)"/>
+        <expand macro="bam_sam_param" />
         <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" />
+        <expand macro="mapq_param" />
+        <expand macro="rscript_output_param" />
     </inputs>
 
     <outputs>
-        <data format="txt" name="outputr" from_work_dir="output.qual.r" label="${tool.name} on ${on_string} (R Script)" />
-        <data format="pdf" name="outputheatpdf" from_work_dir="output.qual.heatmap.pdf" label="${tool.name} on ${on_string} (Heatmap PDF)" />
-        <data format="pdf" name="outputboxpdf" from_work_dir="output.qual.boxplot.pdf" label="${tool.name} on ${on_string} (Boxplot PDF)" />
+        <data format="pdf" name="outputheatpdf" from_work_dir="output.qual.heatmap.pdf" label="${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)" />
+        <expand macro="rscript_output_data" filename="output.qual.r" />
     </outputs>
 
     <tests>
         <test>
             <param name="input" value="pairend_strandspecific_51mer_hg19_random.bam"/>
+            <param name="rscript_output" value="true" />
             <output name="outputr" file="output.qual.r"/>
+            <output name="outputheatpdf" file="output.qual.heatmap.pdf" compare="sim_size" />
+            <output name="outputboxpdf" file="output.qual.boxplot.pdf" compare="sim_size" />
         </test>
     </tests>
 
@@ -70,30 +70,20 @@
 
 1. output.qual.r
 2. output.qual.boxplot.pdf
-    .. image:: http://rseqc.sourceforge.net/_images/36mer.qual.plot.png
+    .. image:: $PATH_TO_IMAGES/36mer.qual.plot.png
         :height: 600 px
         :width: 600 px
         :scale: 80 %
 3. output.qual.heatmap.pdf
-    .. image:: http://rseqc.sourceforge.net/_images/36mer.qual.heatmap.png
+    .. image:: $PATH_TO_IMAGES/36mer.qual.heatmap.png
         :height: 600 px
         :width: 600 px
         :scale: 80 %
 
 Heatmap: use different color to represent nucleotide density ("blue"=low density,"orange"=median density,"red"=high density")
 
------
-
-About RSeQC
-+++++++++++
+@ABOUT@
 
-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.
-
-.. image:: http://rseqc.sourceforge.net/_static/logo.png
-
-.. _RSeQC: http://rseqc.sourceforge.net/
 ]]>
     </help>
 
diff -r f242ee103277 -r 09846d5169fa rseqc_macros.xml
--- a/rseqc_macros.xml	Tue May 03 16:36:57 2016 -0400
+++ b/rseqc_macros.xml	Tue Mar 14 10:23:21 2017 -0400
@@ -1,8 +1,12 @@
 <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>
+    <token name="@WRAPPER_VERSION@">2.6.4</token>
+
+    <xml name="requirements">
+        <requirements>
+            <requirement type="package" version="2.6.4">rseqc</requirement>
+        </requirements>
+    </xml>
 
     <xml name="stdio">
         <stdio>
@@ -11,32 +15,141 @@
         </stdio>
     </xml>
 
+    <!-- Params -->
+    <xml name="bam_param">
+        <param name="input" type="data" label="Input .bam file" format="bam" help="(--input-file)"/>
+    </xml>
+
+    <xml name="bam_sam_param">
+        <param name="input" type="data" label="Input .bam/.sam file" format="bam,sam" help="(--input-file)"/>
+    </xml>
+
+    <xml name="refgene_param">
+        <param name="refgene" type="data" format="bed" label="Reference gene model" help="(--refgene)"/>
+    </xml>
+
+    <xml name="mapq_param">
+        <param name="mapq" type="integer" label="Minimum mapping quality" value="30" help="Minimum mapping quality for an alignment to be considered as &quot;uniquely mapped&quot; (--mapq)"/>
+    </xml>
+
+    <xml name="readlength_param">
+        <param name="readlength" type="integer" value="" label="Alignment length" optional="false" help="Alignment length of read, usually set to the orignial read length (--read-align-length)"/>
+    </xml>
+
+    <xml name="readnum_param">
+        <param name="readnum" type="integer" label="Number of aligned reads" value="1000000" help="Number of aligned reads with mismatches used to calculate the mismatch profile (--read-num)"/>
+    </xml>
+
+    <xml name="sample_size_param">
+        <param name="sample_size" type="integer" label="Number of reads sampled from SAM/BAM file (default = 200000)" value="200000" min="1" help="(--sample-size)"/>
+    </xml>
+
+    <xml name="min_intron_param">
+        <param name="min_intron" type="integer" value="50" label="Minimum intron length (bp, default=50)" help="(--min-intron)" />
+    </xml>
+
+    <xml name="layout_param">
+        <param name="layout" type="select" label="Sequencing layout" help="(--sequencing)">
+            <option value="SE" selected="true">Single-end</option>
+            <option value="PE">Paired-end</option>
+        </param>
+    </xml>
+
+    <xml name="strand_type_param">
+        <conditional name="strand_type">
+            <param name="strand_specific" type="select" label="Strand-specific?">
+                <option value="none" selected="true">None</option>
+                <option value="pair">Pair-End RNA-seq</option>
+                <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)" help="(--strand)">
+                    <option value="sd" selected="true"> 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)" help="(--strand)">
+                    <option value="s" selected="true">positive --> positive; negative --> negative</option>
+                    <option value="d">positive --> negative; negative --> positive</option>
+                </param>
+            </when>
+            <when value="none"></when>
+        </conditional>
+    </xml>
+
+    <xml name="multihits_param">
+        <conditional name="multihits_type">
+            <param name="multihits_type_selector" type="select" label="Reads with multiple hits" help="(--skip-multi-hits)">
+                <option value="use_multihits" selected="true">Count Mutliple Hit Reads</option>
+                <option value="skip_multihits">Skip Multiple Hit Reads/Only Use Uniquely Mapped Reads</option>
+            </param>
+            <when value="skip_multihits">
+                <expand macro="mapq_param" />
+            </when>
+            <when value="use_multihits" />
+        </conditional>
+    </xml>
+
+    <xml name="rscript_output_param">
+        <param name="rscript_output" type="boolean" value="false" label="Output R-Script"
+            help="Output the R-Script used to generate the plots" />
+    </xml>
+
+
+    <!-- Output -->
+
+    <xml name="pdf_output_data" token_filename="output.pdf">
+        <data format="pdf" name="outputpdf" from_work_dir="@FILENAME@" label="${tool.name} on ${on_string} (pdf)" />
+    </xml>
+
+    <xml name="xls_output_data" token_filename="output.xls">
+        <data format="xls" name="outputxls" from_work_dir="@FILENAME@" label="${tool.name} on ${on_string} (xls)" />
+    </xml>
+
+    <xml name="rscript_output_data" token_filename="output.r">
+        <data format="txt" name="outputr" from_work_dir="@FILENAME@" label="${tool.name} on ${on_string} (rscript)">
+            <filter>rscript_output</filter>
+        </data>
+    </xml>
+
+    <!-- Command -->
+    <token name="@MULTIHITS@">
+<![CDATA[
+#if str($multihits_type.multihits_type_selector) == "skip_multihits"
+    --skip-multi-hits
+    --mapq=${multihits_type.mapq}
+#end if
+]]>
+    </token>
+
+    <token name="@ABOUT@">
+
+-----
+
+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.
+
+.. image:: $PATH_TO_IMAGES/logo.png
+
+.. _RSeQC: http://rseqc.sourceforge.net/
+
+
+    </token>
+
     <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>
+            <citation type="doi">10.1093/bioinformatics/bts356</citation>
         </citations>
     </xml>
 </macros>
diff -r f242ee103277 -r 09846d5169fa static/images/36mer.qual.heatmap.png
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diff -r f242ee103277 -r 09846d5169fa static/images/36mer.qual.plot.png
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diff -r f242ee103277 -r 09846d5169fa static/images/Aug_26.geneBodyCoverage.curves.png
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diff -r f242ee103277 -r 09846d5169fa static/images/Aug_26.geneBodyCoverage.heatMap.png
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diff -r f242ee103277 -r 09846d5169fa static/images/NVC_plot.png
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diff -r f242ee103277 -r 09846d5169fa static/images/RelativeError.png
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diff -r f242ee103277 -r 09846d5169fa static/images/clipping_good.png
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diff -r f242ee103277 -r 09846d5169fa static/images/duplicate.png
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diff -r f242ee103277 -r 09846d5169fa static/images/geneBody_coverage.png
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diff -r f242ee103277 -r 09846d5169fa static/images/geneBody_workflow.png
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diff -r f242ee103277 -r 09846d5169fa static/images/inner_distance.png
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diff -r f242ee103277 -r 09846d5169fa static/images/junction.png
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diff -r f242ee103277 -r 09846d5169fa static/images/junction_saturation.png
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diff -r f242ee103277 -r 09846d5169fa static/images/logo.png
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diff -r f242ee103277 -r 09846d5169fa static/images/mismatch_profile.png
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diff -r f242ee103277 -r 09846d5169fa static/images/out.deletion_profile.png
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diff -r f242ee103277 -r 09846d5169fa static/images/out.insertion_profile.R1.png
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diff -r f242ee103277 -r 09846d5169fa static/images/out.insertion_profile.R2.png
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diff -r f242ee103277 -r 09846d5169fa static/images/read_gc.png
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diff -r f242ee103277 -r 09846d5169fa static/images/saturation.png
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diff -r f242ee103277 -r 09846d5169fa static/images/saturation_eg.png
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diff -r f242ee103277 -r 09846d5169fa test-data/bamstats.txt
--- a/test-data/bamstats.txt	Tue May 03 16:36:57 2016 -0400
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,23 +0,0 @@
-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 f242ee103277 -r 09846d5169fa test-data/output.DupRate_plot.pdf
Binary file test-data/output.DupRate_plot.pdf has changed
diff -r f242ee103277 -r 09846d5169fa test-data/output.DupRate_plot.r
--- a/test-data/output.DupRate_plot.r	Tue May 03 16:36:57 2016 -0400
+++ b/test-data/output.DupRate_plot.r	Tue Mar 14 10:23:21 2017 -0400
@@ -4,11 +4,11 @@
 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')
+plot(pos_occ,log10(pos_uniqRead),ylab='Number of Reads (log10)',xlab='Occurrence of read',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))
+legend(300,ym,legend=c('Sequence-based','Mapping-based'),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))))
+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*pos_occ)),round(pos_uniqRead[2]*100/sum(pos_uniqRead*pos_occ)),round(pos_uniqRead[3]*100/sum(pos_uniqRead*pos_occ)),round(pos_uniqRead[4]*100/sum(pos_uniqRead*pos_occ))))
 mtext(4, text = "Reads %", line = 2)
 dev.off()
diff -r f242ee103277 -r 09846d5169fa test-data/output.FPKM.xls
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.FPKM.xls	Tue Mar 14 10:23:21 2017 -0400
@@ -0,0 +1,8 @@
+#chrom	st	end	accession	mRNA_size	gene_strand	Frag_count	FPM	FPKM
+chr1	11873	14409	NR_046018	1652.0	+	1.0	50000.0	30266.3438257
+chr1	14361	29370	NR_024540	1769.0	-	2.0	100000.0	56529.1124929
+chr1	17368	17436	NR_106918	68.0	-	0.0	0.0	0.0
+chr1	17368	17436	NR_107062	68.0	-	0.0	0.0	0.0
+chr1	34610	36081	NR_026818	1130.0	-	0.0	0.0	0.0
+chr1	34610	36081	NR_026820	1130.0	-	0.0	0.0	0.0
+chr1	69090	70008	NM_001005484	918.0	+	0.0	0.0	0.0
diff -r f242ee103277 -r 09846d5169fa test-data/output.GC_plot.pdf
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diff -r f242ee103277 -r 09846d5169fa test-data/output.NVC_plot.pdf
Binary file test-data/output.NVC_plot.pdf has changed
diff -r f242ee103277 -r 09846d5169fa test-data/output.RNA_fragment_size.txt
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.RNA_fragment_size.txt	Tue Mar 14 10:23:21 2017 -0400
@@ -0,0 +1,8 @@
+chrom	tx_start	tx_end	symbol	frag_count	frag_mean	frag_median	frag_std
+chr1	11873	14409	NR_046018	1	0	0	0
+chr1	14361	29370	NR_024540	14	66.5	51.0	41.1195990809
+chr1	17368	17436	NR_106918	0	0	0	0
+chr1	17368	17436	NR_107062	0	0	0	0
+chr1	34610	36081	NR_026818	0	0	0	0
+chr1	34610	36081	NR_026820	0	0	0	0
+chr1	69090	70008	NM_001005484	0	0	0	0
diff -r f242ee103277 -r 09846d5169fa test-data/output.bamstats.txt
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.bamstats.txt	Tue Mar 14 10:23:21 2017 -0400
@@ -0,0 +1,22 @@
+
+#==================================================
+#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 f242ee103277 -r 09846d5169fa test-data/output.clipping_profile.pdf
Binary file test-data/output.clipping_profile.pdf has changed
diff -r f242ee103277 -r 09846d5169fa test-data/output.clipping_profile.r
--- a/test-data/output.clipping_profile.r	Tue May 03 16:36:57 2016 -0400
+++ b/test-data/output.clipping_profile.r	Tue Mar 14 10:23:21 2017 -0400
@@ -1,5 +1,6 @@
 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")
+read_pos=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)
+clip_count=c(16.0,12.0,11.0,8.0,7.0,6.0,1.0,1.0,1.0,1.0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1.0,1.0,1.0,2.0,3.0,4.0,4.0)
+nonclip_count= 40 - clip_count
+plot(read_pos, nonclip_count*100/(clip_count+nonclip_count),col="blue",main="clipping profile",xlab="Position of read",ylab="Non-clipped %",type="b")
 dev.off()
diff -r f242ee103277 -r 09846d5169fa test-data/output.clipping_profile.xls
--- a/test-data/output.clipping_profile.xls	Tue May 03 16:36:57 2016 -0400
+++ b/test-data/output.clipping_profile.xls	Tue Mar 14 10:23:21 2017 -0400
@@ -1,18 +1,52 @@
-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
+Position	Clipped_nt	Non_clipped_nt
+0	16.0	24.0
+1	12.0	28.0
+2	11.0	29.0
+3	8.0	32.0
+4	7.0	33.0
+5	6.0	34.0
+6	1.0	39.0
+7	1.0	39.0
+8	1.0	39.0
+9	1.0	39.0
+10	0	40.0
+11	0	40.0
+12	0	40.0
+13	0	40.0
+14	0	40.0
+15	0	40.0
+16	0	40.0
+17	0	40.0
+18	0	40.0
+19	0	40.0
+20	0	40.0
+21	0	40.0
+22	0	40.0
+23	0	40.0
+24	0	40.0
+25	0	40.0
+26	0	40.0
+27	0	40.0
+28	0	40.0
+29	0	40.0
+30	0	40.0
+31	0	40.0
+32	0	40.0
+33	0	40.0
+34	0	40.0
+35	0	40.0
+36	0	40.0
+37	0	40.0
+38	0	40.0
+39	0	40.0
+40	0	40.0
+41	0	40.0
+42	0	40.0
+43	0	40.0
+44	1.0	39.0
+45	1.0	39.0
+46	1.0	39.0
+47	2.0	38.0
+48	3.0	37.0
+49	4.0	36.0
+50	4.0	36.0
diff -r f242ee103277 -r 09846d5169fa test-data/output.deletion_profile.pdf
Binary file test-data/output.deletion_profile.pdf has changed
diff -r f242ee103277 -r 09846d5169fa test-data/output.deletion_profile.r
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.deletion_profile.r	Tue Mar 14 10:23:21 2017 -0400
@@ -0,0 +1,5 @@
+pdf("output.deletion_profile.pdf")
+pos=c(0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100)
+value=c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0)
+plot(pos,value,type='b', col='blue',xlab="Read position (5'->3')", ylab='Deletion count')
+dev.off()
diff -r f242ee103277 -r 09846d5169fa test-data/output.deletion_profile.txt
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.deletion_profile.txt	Tue Mar 14 10:23:21 2017 -0400
@@ -0,0 +1,102 @@
+read_position	deletion_count
+0	0
+1	0
+2	0
+3	0
+4	0
+5	0
+6	0
+7	0
+8	0
+9	0
+10	0
+11	0
+12	0
+13	0
+14	0
+15	0
+16	0
+17	0
+18	0
+19	0
+20	0
+21	0
+22	0
+23	0
+24	0
+25	0
+26	0
+27	0
+28	0
+29	0
+30	0
+31	0
+32	0
+33	0
+34	0
+35	0
+36	0
+37	0
+38	0
+39	0
+40	0
+41	0
+42	0
+43	0
+44	0
+45	0
+46	0
+47	0
+48	0
+49	0
+50	0
+51	0
+52	0
+53	0
+54	0
+55	0
+56	0
+57	0
+58	0
+59	0
+60	0
+61	0
+62	0
+63	0
+64	0
+65	0
+66	0
+67	0
+68	0
+69	0
+70	0
+71	0
+72	0
+73	0
+74	0
+75	0
+76	0
+77	0
+78	0
+79	0
+80	0
+81	0
+82	0
+83	0
+84	0
+85	0
+86	0
+87	0
+88	0
+89	0
+90	0
+91	0
+92	0
+93	0
+94	0
+95	0
+96	0
+97	0
+98	0
+99	0
+100	0
diff -r f242ee103277 -r 09846d5169fa test-data/output.geneBodyCoverage.curves.pdf
Binary file test-data/output.geneBodyCoverage.curves.pdf has changed
diff -r f242ee103277 -r 09846d5169fa test-data/output.geneBodyCoverage.r
--- a/test-data/output.geneBodyCoverage.r	Tue May 03 16:36:57 2016 -0400
+++ b/test-data/output.geneBodyCoverage.r	Tue Mar 14 10:23:21 2017 -0400
@@ -1,8 +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)
+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])
+plot(x,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 f242ee103277 -r 09846d5169fa test-data/output.geneBodyCoverage.txt
--- a/test-data/output.geneBodyCoverage.txt	Tue May 03 16:36:57 2016 -0400
+++ b/test-data/output.geneBodyCoverage.txt	Tue Mar 14 10:23:21 2017 -0400
@@ -1,2 +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
+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 f242ee103277 -r 09846d5169fa test-data/output.geneBodyCoverage2.curves.pdf
Binary file test-data/output.geneBodyCoverage2.curves.pdf has changed
diff -r f242ee103277 -r 09846d5169fa test-data/output.geneBodyCoverage2.r
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.geneBodyCoverage2.r	Tue Mar 14 10:23:21 2017 -0400
@@ -0,0 +1,5 @@
+pdf('output.geneBodyCoverage.pdf')
+x=1:100
+y=c(0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0)
+plot(x,y/7,xlab="percentile of gene body (5'->3')",ylab='average wigsum',type='s')
+dev.off()
diff -r f242ee103277 -r 09846d5169fa test-data/output.geneBodyCoverage2.txt
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.geneBodyCoverage2.txt	Tue Mar 14 10:23:21 2017 -0400
@@ -0,0 +1,101 @@
+percentile	count
+0	0.0
+1	0.0
+2	0.0
+3	0.0
+4	0.0
+5	0.0
+6	0.0
+7	0.0
+8	0.0
+9	0.0
+10	0.0
+11	0.0
+12	0.0
+13	0.0
+14	0.0
+15	0.0
+16	0.0
+17	0.0
+18	0.0
+19	0.0
+20	0.0
+21	0.0
+22	0.0
+23	0.0
+24	0.0
+25	1.0
+26	0.0
+27	0.0
+28	1.0
+29	0.0
+30	0.0
+31	0.0
+32	0.0
+33	0.0
+34	0.0
+35	0.0
+36	0.0
+37	0.0
+38	1.0
+39	1.0
+40	1.0
+41	0.0
+42	0.0
+43	1.0
+44	1.0
+45	1.0
+46	0.0
+47	0.0
+48	0.0
+49	0.0
+50	0.0
+51	0.0
+52	0.0
+53	0.0
+54	0.0
+55	0.0
+56	0.0
+57	0.0
+58	0.0
+59	0.0
+60	0.0
+61	0.0
+62	0.0
+63	0.0
+64	0.0
+65	0.0
+66	0.0
+67	0.0
+68	0.0
+69	0.0
+70	0.0
+71	0.0
+72	0.0
+73	0.0
+74	0.0
+75	0.0
+76	0.0
+77	0.0
+78	0.0
+79	1.0
+80	1.0
+81	1.0
+82	0.0
+83	1.0
+84	1.0
+85	1.0
+86	0.0
+87	0.0
+88	0.0
+89	0.0
+90	0.0
+91	0.0
+92	0.0
+93	0.0
+94	0.0
+95	0.0
+96	0.0
+97	0.0
+98	0.0
+99	0.0
diff -r f242ee103277 -r 09846d5169fa test-data/output.infer_experiment.txt
--- a/test-data/output.infer_experiment.txt	Tue May 03 16:36:57 2016 -0400
+++ b/test-data/output.infer_experiment.txt	Tue Mar 14 10:23:21 2017 -0400
@@ -1,6 +1,6 @@
 
 
 This is PairEnd Data
+Fraction of reads failed to determine: 0.0000
 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 f242ee103277 -r 09846d5169fa test-data/output.inner_distance_plot.pdf
Binary file test-data/output.inner_distance_plot.pdf has changed
diff -r f242ee103277 -r 09846d5169fa test-data/output.inner_distance_plot.r
--- a/test-data/output.inner_distance_plot.r	Tue May 03 16:36:57 2016 -0400
+++ b/test-data/output.inner_distance_plot.r	Tue Mar 14 10:23:21 2017 -0400
@@ -1,11 +1,11 @@
+out_file = 'output'
 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())
+write(x=c("Name","Mean","Median","sd"), sep="	", file=stdout(),ncolumns=4)
+write(c(out_file,frag_mean,frag_median,frag_sd),sep="	", file=stdout(),ncolumns=4)
 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 f242ee103277 -r 09846d5169fa test-data/output.insertion_profile.pdf
Binary file test-data/output.insertion_profile.pdf has changed
diff -r f242ee103277 -r 09846d5169fa test-data/output.insertion_profile.r
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.insertion_profile.r	Tue Mar 14 10:23:21 2017 -0400
@@ -0,0 +1,6 @@
+pdf("output.insertion_profile.pdf")
+read_pos=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)
+insert_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)
+noninsert_count= 40 - insert_count
+plot(read_pos, insert_count*100/(insert_count+noninsert_count),col="blue",main="Insertion profile",xlab="Position of read",ylab="Insertion %",type="b")
+dev.off()
diff -r f242ee103277 -r 09846d5169fa test-data/output.insertion_profile.xls
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.insertion_profile.xls	Tue Mar 14 10:23:21 2017 -0400
@@ -0,0 +1,52 @@
+Position	Insert_nt	Non_insert_nt
+0	0	40.0
+1	0	40.0
+2	0	40.0
+3	0	40.0
+4	0	40.0
+5	0	40.0
+6	0	40.0
+7	0	40.0
+8	0	40.0
+9	0	40.0
+10	0	40.0
+11	0	40.0
+12	0	40.0
+13	0	40.0
+14	0	40.0
+15	0	40.0
+16	0	40.0
+17	0	40.0
+18	0	40.0
+19	0	40.0
+20	0	40.0
+21	0	40.0
+22	0	40.0
+23	0	40.0
+24	0	40.0
+25	0	40.0
+26	0	40.0
+27	0	40.0
+28	0	40.0
+29	0	40.0
+30	0	40.0
+31	0	40.0
+32	0	40.0
+33	0	40.0
+34	0	40.0
+35	0	40.0
+36	0	40.0
+37	0	40.0
+38	0	40.0
+39	0	40.0
+40	0	40.0
+41	0	40.0
+42	0	40.0
+43	0	40.0
+44	0	40.0
+45	0	40.0
+46	0	40.0
+47	0	40.0
+48	0	40.0
+49	0	40.0
+50	0	40.0
diff -r f242ee103277 -r 09846d5169fa test-data/output.junctionSaturation_plot.pdf
Binary file test-data/output.junctionSaturation_plot.pdf has changed
diff -r f242ee103277 -r 09846d5169fa test-data/output.junctionSaturation_plot.r
--- a/test-data/output.junctionSaturation_plot.r	Tue May 03 16:36:57 2016 -0400
+++ b/test-data/output.junctionSaturation_plot.r	Tue Mar 14 10:23:21 2017 -0400
@@ -1,8 +1,8 @@
 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)
+y=c(0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1)
 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)
+w=c(0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,2)
 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))
diff -r f242ee103277 -r 09846d5169fa test-data/output.mismatch_profile.pdf
diff -r f242ee103277 -r 09846d5169fa test-data/output.mismatch_profile.r
diff -r f242ee103277 -r 09846d5169fa test-data/output.mismatch_profile.xls
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.mismatch_profile.xls	Tue Mar 14 10:23:21 2017 -0400
@@ -0,0 +1,1 @@
+Total reads used: 0
diff -r f242ee103277 -r 09846d5169fa test-data/output.qual.boxplot.pdf
Binary file test-data/output.qual.boxplot.pdf has changed
diff -r f242ee103277 -r 09846d5169fa test-data/output.qual.heatmap.pdf
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.qual.heatmap.pdf	Tue Mar 14 10:23:21 2017 -0400
@@ -0,0 +1,62 @@
+pdf('output.qual.boxplot.pdf')
+p0<-rep(c(33,37,38,39,40,41,42,43,44,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(119,2,3,2,5,6,8,6,2,3,11,16,6,26,11,13,25,39,7,40,33,33,58,51,116,87,55,256,54,323,263,140,812,654,1119)/1000)
+p1<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(105,2,2,2,4,8,6,21,3,1,1,8,13,13,16,16,14,29,32,18,50,30,57,66,73,97,105,60,253,57,330,270,142,801,630,1069)/1000)
+p2<-rep(c(33,35,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(109,1,1,3,2,7,11,14,13,2,4,3,8,14,21,27,17,14,26,39,11,37,28,74,64,55,86,106,62,234,56,326,269,147,787,645,1081)/1000)
+p3<-rep(c(33,37,38,39,40,41,42,43,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(108,1,6,4,2,9,12,7,3,3,9,14,13,24,20,8,24,46,14,43,28,59,67,75,88,107,51,285,56,293,239,139,802,660,1084)/1000)
+p4<-rep(c(33,35,37,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(97,1,1,3,9,8,11,5,4,2,4,10,16,19,24,7,8,35,43,19,49,29,51,67,51,93,107,43,306,65,345,223,123,789,661,1075)/1000)
+p5<-rep(c(33,37,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(96,3,2,5,11,6,8,2,7,2,12,17,15,16,12,11,25,31,12,32,36,59,70,69,74,99,56,277,59,343,249,111,845,650,1081)/1000)
+p6<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(86,2,4,2,6,12,8,10,1,7,7,9,11,14,26,14,9,14,53,17,34,41,55,71,76,76,117,62,238,62,339,229,155,798,607,1131)/1000)
+p7<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(76,1,4,4,6,11,9,13,5,5,6,6,17,19,20,17,8,19,45,15,30,33,60,68,58,76,99,59,291,54,349,251,129,818,602,1120)/1000)
+p8<-rep(c(33,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(74,1,2,3,1,5,6,6,7,7,2,4,11,11,16,24,13,9,24,48,19,33,39,63,67,68,78,104,66,284,62,329,240,147,749,649,1132)/1000)
+p9<-rep(c(33,37,38,39,40,41,42,43,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(98,1,2,2,6,11,19,10,5,3,8,18,19,24,14,5,18,53,21,41,39,56,79,64,70,93,57,291,42,334,259,143,795,616,1087)/1000)
+p10<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(71,3,3,4,3,5,6,7,2,3,5,13,14,6,17,21,12,27,40,16,34,39,46,64,78,103,103,63,279,37,314,239,118,805,674,1129)/1000)
+p11<-rep(c(33,34,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(76,1,4,3,3,7,10,11,8,5,6,3,12,13,18,21,16,18,21,46,21,32,41,77,56,77,103,105,54,269,40,320,247,144,796,621,1098)/1000)
+p12<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(87,3,2,1,7,12,8,6,5,13,8,11,9,16,23,13,14,22,40,21,53,48,51,59,77,84,126,75,282,48,306,254,151,808,586,1074)/1000)
+p13<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(76,5,1,3,6,3,7,8,4,3,10,12,14,13,23,12,19,25,43,17,52,42,63,57,92,91,114,61,281,45,342,256,132,812,586,1073)/1000)
+p14<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(81,1,5,4,4,10,11,9,3,5,5,6,18,21,29,26,14,27,51,17,54,47,51,65,84,84,118,66,291,46,316,244,149,782,579,1080)/1000)
+p15<-rep(c(33,36,37,38,39,40,41,42,43,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(87,1,2,5,2,10,17,12,9,7,2,10,10,12,20,18,21,27,50,17,50,54,42,82,57,84,103,54,285,41,342,265,115,822,582,1085)/1000)
+p16<-rep(c(33,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(118,4,3,7,7,11,10,5,6,8,11,18,19,30,34,13,34,47,14,62,49,55,83,82,96,101,51,283,45,346,249,152,843,521,985)/1000)
+p17<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(73,2,5,6,7,9,11,7,5,4,11,19,13,15,33,18,17,42,57,25,46,65,67,94,68,93,117,67,279,53,306,295,132,844,504,993)/1000)
+p18<-rep(c(33,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(72,1,2,3,5,4,16,13,14,2,8,2,18,19,27,37,27,18,29,57,21,47,57,62,87,81,89,111,57,293,49,319,270,142,858,495,990)/1000)
+p19<-rep(c(33,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(78,1,1,5,3,3,13,10,13,5,7,5,14,15,24,30,23,23,24,57,19,72,49,70,70,72,91,124,60,298,52,347,270,147,841,486,980)/1000)
+p20<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(71,4,5,3,10,9,10,12,5,9,6,23,14,19,33,27,21,34,60,16,47,57,55,82,84,109,117,44,305,45,335,265,146,856,510,954)/1000)
+p21<-rep(c(33,37,38,39,40,41,42,43,44,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(80,5,4,5,4,6,10,7,4,11,14,19,18,32,25,29,32,75,19,58,56,66,81,79,102,133,52,332,44,306,260,152,879,486,917)/1000)
+p22<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(80,2,5,2,11,11,13,4,4,5,8,12,15,21,34,27,18,44,58,26,72,62,72,90,84,97,137,51,324,54,332,254,143,857,492,881)/1000)
+p23<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(78,3,4,1,9,9,3,8,9,9,5,12,20,19,37,30,23,38,69,29,64,51,71,95,92,99,133,52,320,51,340,275,152,868,467,856)/1000)
+p24<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(73,1,2,3,6,14,19,7,3,3,10,24,15,26,38,27,15,34,71,17,62,72,75,86,84,108,128,65,304,41,356,239,139,864,494,876)/1000)
+p25<-rep(c(33,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(100,1,1,6,3,6,14,19,11,9,7,11,5,8,25,21,35,16,18,39,61,19,65,42,62,91,83,80,105,38,318,50,372,289,135,847,504,884)/1000)
+p26<-rep(c(33,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(72,1,1,4,2,12,10,17,11,5,3,3,21,25,29,34,34,19,38,55,20,55,59,82,96,99,106,133,45,299,71,339,265,157,822,474,882)/1000)
+p27<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(73,1,2,5,3,17,16,6,5,7,11,7,16,14,30,31,16,45,71,29,50,62,72,78,77,107,132,62,273,47,366,277,161,892,462,877)/1000)
+p28<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(91,3,2,2,7,10,6,9,9,6,11,15,17,19,33,20,10,30,54,20,68,48,73,84,72,114,131,60,321,60,356,270,159,874,496,840)/1000)
+p29<-rep(c(33,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(92,1,5,5,4,6,8,7,10,4,7,7,16,26,24,33,20,22,36,49,15,53,65,71,79,80,112,127,63,320,49,359,292,141,837,455,900)/1000)
+p30<-rep(c(33,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(105,1,2,5,4,2,15,8,13,8,6,7,19,24,21,30,22,17,35,53,13,52,61,45,93,74,87,120,60,302,41,331,272,131,877,513,931)/1000)
+p31<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(117,3,5,3,11,23,24,10,5,7,6,8,13,12,40,18,18,40,41,12,45,57,72,86,71,75,125,68,299,55,302,264,154,874,464,973)/1000)
+p32<-rep(c(33,35,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(120,1,7,3,4,9,13,19,8,5,3,10,17,25,13,19,18,23,33,49,25,41,51,72,74,56,95,112,60,291,58,281,267,145,916,463,993)/1000)
+p33<-rep(c(33,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(89,1,4,9,13,7,8,7,8,6,8,8,18,20,12,34,26,14,31,50,17,45,65,58,68,77,84,110,66,289,54,284,282,164,871,489,1003)/1000)
+p34<-rep(c(33,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(162,1,3,4,4,14,15,24,17,2,6,9,16,15,20,37,20,12,34,49,12,42,50,54,66,62,81,121,56,265,50,292,258,127,878,506,1015)/1000)
+p35<-rep(c(33,37,38,39,40,41,42,43,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(79,5,1,3,3,13,8,6,7,11,15,19,11,17,25,16,34,49,16,37,45,69,72,76,79,101,48,303,38,326,254,140,811,619,1043)/1000)
+p36<-rep(c(33,37,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(78,3,4,3,8,5,6,8,6,5,13,18,18,32,19,22,39,43,17,39,45,68,77,74,69,118,47,272,47,332,262,139,833,562,1068)/1000)
+p37<-rep(c(33,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(96,1,3,1,5,5,6,6,8,4,7,3,12,9,18,35,15,24,27,57,20,40,53,70,81,89,91,117,46,262,44,298,251,130,817,588,1059)/1000)
+p38<-rep(c(33,37,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(102,5,5,4,10,11,12,3,3,7,8,18,15,22,20,17,20,50,21,46,43,71,70,80,91,110,51,239,34,339,258,119,820,614,1058)/1000)
+p39<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(100,3,5,3,6,10,12,12,5,5,10,6,21,18,28,14,16,33,38,18,45,56,58,71,65,79,109,57,253,47,310,263,129,854,616,1017)/1000)
+p40<-rep(c(33,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(97,1,4,3,1,5,14,7,11,2,5,2,9,6,19,21,18,21,30,37,22,37,64,40,69,53,89,104,66,281,42,355,233,137,771,615,1095)/1000)
+p41<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(130,5,2,6,10,10,19,20,5,5,4,12,16,17,28,14,12,25,42,16,42,39,57,61,73,84,110,49,261,48,315,254,125,761,643,1028)/1000)
+p42<-rep(c(33,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(108,2,1,2,1,5,4,12,13,7,6,7,3,6,14,19,20,22,15,22,52,14,50,45,57,67,72,78,119,51,272,45,284,226,127,831,604,1054)/1000)
+p43<-rep(c(33,35,36,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(124,2,2,1,2,5,13,17,10,1,6,4,14,11,19,31,14,14,24,30,12,42,41,54,64,74,82,112,68,250,49,308,261,142,775,557,1060)/1000)
+p44<-rep(c(33,35,37,38,39,40,41,42,43,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(106,1,1,4,4,10,9,9,7,9,6,8,8,16,21,12,18,24,50,14,43,43,56,55,100,87,109,51,261,51,308,217,139,759,562,1041)/1000)
+p45<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(120,3,3,2,9,7,12,9,6,4,1,10,9,15,26,11,16,22,35,16,26,45,50,60,56,67,74,62,247,50,282,243,123,747,618,1061)/1000)
+p46<-rep(c(33,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(116,1,2,3,2,10,15,10,1,2,6,6,10,9,13,8,14,29,26,12,31,42,59,41,57,88,92,58,257,43,304,236,133,707,612,1016)/1000)
+p47<-rep(c(33,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(130,1,2,4,2,6,8,18,21,3,5,5,7,12,15,17,7,7,23,43,9,28,32,44,42,56,68,83,54,225,38,289,181,133,713,594,991)/1000)
+p48<-rep(c(33,35,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(105,1,5,2,6,9,10,23,1,5,3,3,9,9,30,13,7,18,27,12,28,24,49,42,63,75,81,45,226,43,274,217,147,676,571,925)/1000)
+p49<-rep(c(33,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(99,3,1,3,5,5,16,3,3,6,7,4,13,15,11,3,10,34,16,20,37,46,41,52,66,85,35,201,45,253,201,119,685,497,913)/1000)
+p50<-rep(c(33,43,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71),times=c(82,2,3,5,3,4,5,13,9,5,11,14,3,35,17,21,41,34,67,67,31,184,49,241,167,93,639,515,797)/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(119,0,0,0,2,3,2,5,6,8,6,2,0,3,11,16,6,26,11,13,25,39,7,40,33,33,58,51,116,87,55,256,54,323,263,140,812,654,1119,105,0,0,0,2,2,2,4,8,6,21,3,1,1,8,13,13,16,16,14,29,32,18,50,30,57,66,73,97,105,60,253,57,330,270,142,801,630,1069,109,0,1,0,1,3,2,7,11,14,13,2,4,3,8,14,21,27,17,14,26,39,11,37,28,74,64,55,86,106,62,234,56,326,269,147,787,645,1081,108,0,0,0,1,6,4,2,9,12,7,0,3,3,9,14,13,24,20,8,24,46,14,43,28,59,67,75,88,107,51,285,56,293,239,139,802,660,1084,97,0,1,0,1,0,3,9,8,11,5,4,2,4,10,16,19,24,7,8,35,43,19,49,29,51,67,51,93,107,43,306,65,345,223,123,789,661,1075,96,0,0,0,3,0,2,5,11,6,8,2,7,2,12,17,15,16,12,11,25,31,12,32,36,59,70,69,74,99,56,277,59,343,249,111,845,650,1081,86,0,0,0,2,4,2,6,12,8,10,1,7,7,9,11,14,26,14,9,14,53,17,34,41,55,71,76,76,117,62,238,62,339,229,155,798,607,1131,76,0,0,0,1,4,4,6,11,9,13,5,5,6,6,17,19,20,17,8,19,45,15,30,33,60,68,58,76,99,59,291,54,349,251,129,818,602,1120,74,0,0,1,2,3,1,5,6,6,7,7,2,4,11,11,16,24,13,9,24,48,19,33,39,63,67,68,78,104,66,284,62,329,240,147,749,649,1132,98,0,0,0,1,2,2,6,11,19,10,0,5,3,8,18,19,24,14,5,18,53,21,41,39,56,79,64,70,93,57,291,42,334,259,143,795,616,1087,71,0,0,0,3,3,4,3,5,6,7,2,3,5,13,14,6,17,21,12,27,40,16,34,39,46,64,78,103,103,63,279,37,314,239,118,805,674,1129,76,1,0,0,4,3,3,7,10,11,8,5,6,3,12,13,18,21,16,18,21,46,21,32,41,77,56,77,103,105,54,269,40,320,247,144,796,621,1098,87,0,0,0,3,2,1,7,12,8,6,5,13,8,11,9,16,23,13,14,22,40,21,53,48,51,59,77,84,126,75,282,48,306,254,151,808,586,1074,76,0,0,0,5,1,3,6,3,7,8,4,3,10,12,14,13,23,12,19,25,43,17,52,42,63,57,92,91,114,61,281,45,342,256,132,812,586,1073,81,0,0,0,1,5,4,4,10,11,9,3,5,5,6,18,21,29,26,14,27,51,17,54,47,51,65,84,84,118,66,291,46,316,244,149,782,579,1080,87,0,0,1,2,5,2,10,17,12,9,0,7,2,10,10,12,20,18,21,27,50,17,50,54,42,82,57,84,103,54,285,41,342,265,115,822,582,1085,118,0,0,0,0,4,3,7,7,11,10,5,6,8,11,18,19,30,34,13,34,47,14,62,49,55,83,82,96,101,51,283,45,346,249,152,843,521,985,73,0,0,0,2,5,6,7,9,11,7,5,4,11,19,13,15,33,18,17,42,57,25,46,65,67,94,68,93,117,67,279,53,306,295,132,844,504,993,72,0,0,1,2,3,5,4,16,13,14,2,8,2,18,19,27,37,27,18,29,57,21,47,57,62,87,81,89,111,57,293,49,319,270,142,858,495,990,78,0,0,1,1,5,3,3,13,10,13,5,7,5,14,15,24,30,23,23,24,57,19,72,49,70,70,72,91,124,60,298,52,347,270,147,841,486,980,71,0,0,0,4,5,3,10,9,10,12,5,9,6,23,14,19,33,27,21,34,60,16,47,57,55,82,84,109,117,44,305,45,335,265,146,856,510,954,80,0,0,0,5,4,5,4,6,10,7,4,0,11,14,19,18,32,25,29,32,75,19,58,56,66,81,79,102,133,52,332,44,306,260,152,879,486,917,80,0,0,0,2,5,2,11,11,13,4,4,5,8,12,15,21,34,27,18,44,58,26,72,62,72,90,84,97,137,51,324,54,332,254,143,857,492,881,78,0,0,0,3,4,1,9,9,3,8,9,9,5,12,20,19,37,30,23,38,69,29,64,51,71,95,92,99,133,52,320,51,340,275,152,868,467,856,73,0,0,0,1,2,3,6,14,19,7,3,3,10,24,15,26,38,27,15,34,71,17,62,72,75,86,84,108,128,65,304,41,356,239,139,864,494,876,100,0,1,1,6,3,6,14,19,11,9,7,11,5,8,25,21,35,16,18,39,61,19,65,42,62,91,83,80,105,38,318,50,372,289,135,847,504,884,72,0,0,1,1,4,2,12,10,17,11,5,3,3,21,25,29,34,34,19,38,55,20,55,59,82,96,99,106,133,45,299,71,339,265,157,822,474,882,73,0,0,0,1,2,5,3,17,16,6,5,7,11,7,16,14,30,31,16,45,71,29,50,62,72,78,77,107,132,62,273,47,366,277,161,892,462,877,91,0,0,0,3,2,2,7,10,6,9,9,6,11,15,17,19,33,20,10,30,54,20,68,48,73,84,72,114,131,60,321,60,356,270,159,874,496,840,92,0,0,1,5,5,4,6,8,7,10,4,7,7,16,26,24,33,20,22,36,49,15,53,65,71,79,80,112,127,63,320,49,359,292,141,837,455,900,105,0,0,1,2,5,4,2,15,8,13,8,6,7,19,24,21,30,22,17,35,53,13,52,61,45,93,74,87,120,60,302,41,331,272,131,877,513,931,117,0,0,0,3,5,3,11,23,24,10,5,7,6,8,13,12,40,18,18,40,41,12,45,57,72,86,71,75,125,68,299,55,302,264,154,874,464,973,120,0,1,0,7,3,4,9,13,19,8,5,3,10,17,25,13,19,18,23,33,49,25,41,51,72,74,56,95,112,60,291,58,281,267,145,916,463,993,89,0,0,1,4,9,13,7,8,7,8,6,8,8,18,20,12,34,26,14,31,50,17,45,65,58,68,77,84,110,66,289,54,284,282,164,871,489,1003,162,0,0,1,3,4,4,14,15,24,17,2,6,9,16,15,20,37,20,12,34,49,12,42,50,54,66,62,81,121,56,265,50,292,258,127,878,506,1015,79,0,0,0,5,1,3,3,13,8,6,0,7,11,15,19,11,17,25,16,34,49,16,37,45,69,72,76,79,101,48,303,38,326,254,140,811,619,1043,78,0,0,0,3,0,4,3,8,5,6,8,6,5,13,18,18,32,19,22,39,43,17,39,45,68,77,74,69,118,47,272,47,332,262,139,833,562,1068,96,0,0,1,3,1,5,5,6,6,8,4,7,3,12,9,18,35,15,24,27,57,20,40,53,70,81,89,91,117,46,262,44,298,251,130,817,588,1059,102,0,0,0,5,0,5,4,10,11,12,3,3,7,8,18,15,22,20,17,20,50,21,46,43,71,70,80,91,110,51,239,34,339,258,119,820,614,1058,100,0,0,0,3,5,3,6,10,12,12,5,5,10,6,21,18,28,14,16,33,38,18,45,56,58,71,65,79,109,57,253,47,310,263,129,854,616,1017,97,0,0,1,4,3,1,5,14,7,11,2,5,2,9,6,19,21,18,21,30,37,22,37,64,40,69,53,89,104,66,281,42,355,233,137,771,615,1095,130,0,0,0,5,2,6,10,10,19,20,5,5,4,12,16,17,28,14,12,25,42,16,42,39,57,61,73,84,110,49,261,48,315,254,125,761,643,1028,108,0,2,1,2,1,5,4,12,13,7,6,7,3,6,14,19,20,22,15,22,52,14,50,45,57,67,72,78,119,51,272,45,284,226,127,831,604,1054,124,0,2,2,0,1,2,5,13,17,10,1,6,4,14,11,19,31,14,14,24,30,12,42,41,54,64,74,82,112,68,250,49,308,261,142,775,557,1060,106,0,1,0,1,4,4,10,9,9,7,0,9,6,8,8,16,21,12,18,24,50,14,43,43,56,55,100,87,109,51,261,51,308,217,139,759,562,1041,120,0,0,0,3,3,2,9,7,12,9,6,4,1,10,9,15,26,11,16,22,35,16,26,45,50,60,56,67,74,62,247,50,282,243,123,747,618,1061,116,0,0,0,1,2,3,2,10,15,10,1,2,6,6,10,9,13,8,14,29,26,12,31,42,59,41,57,88,92,58,257,43,304,236,133,707,612,1016,130,0,0,1,2,4,2,6,8,18,21,3,5,5,7,12,15,17,7,7,23,43,9,28,32,44,42,56,68,83,54,225,38,289,181,133,713,594,991,105,0,1,0,0,5,2,6,9,10,23,1,5,3,3,9,9,30,13,7,18,27,12,28,24,49,42,63,75,81,45,226,43,274,217,147,676,571,925,99,0,0,0,0,3,1,3,5,5,16,3,3,6,7,4,13,15,11,3,10,34,16,20,37,46,41,52,66,85,35,201,45,253,201,119,685,497,913,82,0,0,0,0,0,0,0,0,0,2,0,3,5,3,4,5,13,9,5,11,14,3,35,17,21,41,34,67,67,31,184,49,241,167,93,639,515,797)
+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 f242ee103277 -r 09846d5169fa test-data/output.saturation.pdf
Binary file test-data/output.saturation.pdf has changed
diff -r f242ee103277 -r 09846d5169fa test-data/output.tin.summary.txt
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.tin.summary.txt	Tue Mar 14 10:23:21 2017 -0400
@@ -0,0 +1,2 @@
+Bam_file	TIN(mean)	TIN(median)	TIN(stdev)
+input.bam	8.87096774194	8.87096774194	0.0
diff -r f242ee103277 -r 09846d5169fa test-data/output.tin.xls
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.tin.xls	Tue Mar 14 10:23:21 2017 -0400
@@ -0,0 +1,8 @@
+geneID	chrom	tx_start	tx_end	TIN
+NR_046018	chr1	11873	14409	0.0
+NR_024540	chr1	14361	29370	8.87096774194
+NR_106918	chr1	17368	17436	0.0
+NR_107062	chr1	17368	17436	0.0
+NR_026818	chr1	34610	36081	0.0
+NR_026820	chr1	34610	36081	0.0
+NM_001005484	chr1	69090	70008	0.0
diff -r f242ee103277 -r 09846d5169fa test-data/output2.geneBodyCoverage.curves.pdf
Binary file test-data/output2.geneBodyCoverage.curves.pdf has changed
diff -r f242ee103277 -r 09846d5169fa test-data/output2.geneBodyCoverage.heatMap.pdf
Binary file test-data/output2.geneBodyCoverage.heatMap.pdf has changed
diff -r f242ee103277 -r 09846d5169fa test-data/output2.geneBodyCoverage.r
--- a/test-data/output2.geneBodyCoverage.r	Tue May 03 16:36:57 2016 -0400
+++ b/test-data/output2.geneBodyCoverage.r	Tue Mar 14 10:23:21 2017 -0400
@@ -1,8 +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)
-d2_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)
-d3_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)
-data_matrix <- matrix(c(d1_pairend_strandspecific_51mer_hg19_chr1_1_100000_bam,d2_pairend_strandspecific_51mer_hg19_chr1_1_100000_bam,d3_pairend_strandspecific_51mer_hg19_chr1_1_100000_bam), byrow=T, ncol=100)
-rowLabel <- c("d1_pairend_strandspecific_51mer_hg19_chr1_1_100000_bam","d2_pairend_strandspecific_51mer_hg19_chr1_1_100000_bam","d3_pairend_strandspecific_51mer_hg19_chr1_1_100000_bam")
+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)
+pairend_strandspecific_51mer_hg19_chr1_1_100000_bam.1 <- 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)
+pairend_strandspecific_51mer_hg19_chr1_1_100000_bam.2 <- 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)
+data_matrix <- matrix(c(pairend_strandspecific_51mer_hg19_chr1_1_100000_bam,pairend_strandspecific_51mer_hg19_chr1_1_100000_bam.1,pairend_strandspecific_51mer_hg19_chr1_1_100000_bam.2), byrow=T, ncol=100)
+rowLabel <- c("pairend_strandspecific_51mer_hg19_chr1_1_100000_bam","pairend_strandspecific_51mer_hg19_chr1_1_100000_bam.1","pairend_strandspecific_51mer_hg19_chr1_1_100000_bam.2")
 
 
 pdf("output.geneBodyCoverage.heatMap.pdf")
@@ -14,8 +14,8 @@
 pdf("output.geneBodyCoverage.curves.pdf")
 x=1:100
 icolor = colorRampPalette(c("#7fc97f","#beaed4","#fdc086","#ffff99","#386cb0","#f0027f"))(3)
-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])
-lines(x,d2_pairend_strandspecific_51mer_hg19_chr1_1_100000_bam,type='l',col=icolor[2])
-lines(x,d3_pairend_strandspecific_51mer_hg19_chr1_1_100000_bam,type='l',col=icolor[3])
-legend(0,1,fill=icolor[1:3], legend=c('d1_pairend_strandspecific_51mer_hg19_chr1_1_100000_bam','d2_pairend_strandspecific_51mer_hg19_chr1_1_100000_bam','d3_pairend_strandspecific_51mer_hg19_chr1_1_100000_bam'))
+plot(x,pairend_strandspecific_51mer_hg19_chr1_1_100000_bam,type='l',xlab="Gene body percentile (5'->3')", ylab="Coverage",lwd=0.8,col=icolor[1])
+lines(x,pairend_strandspecific_51mer_hg19_chr1_1_100000_bam.1,type='l',col=icolor[2])
+lines(x,pairend_strandspecific_51mer_hg19_chr1_1_100000_bam.2,type='l',col=icolor[3])
+legend(0,1,fill=icolor[1:3], legend=c('pairend_strandspecific_51mer_hg19_chr1_1_100000_bam','pairend_strandspecific_51mer_hg19_chr1_1_100000_bam.1','pairend_strandspecific_51mer_hg19_chr1_1_100000_bam.2'))
 dev.off()
diff -r f242ee103277 -r 09846d5169fa test-data/output2.geneBodyCoverage.txt
--- a/test-data/output2.geneBodyCoverage.txt	Tue May 03 16:36:57 2016 -0400
+++ b/test-data/output2.geneBodyCoverage.txt	Tue Mar 14 10:23:21 2017 -0400
@@ -1,4 +1,4 @@
 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
-d2_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
-d3_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
+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
+pairend_strandspecific_51mer_hg19_chr1_1_100000_bam.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	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
+pairend_strandspecific_51mer_hg19_chr1_1_100000_bam.2	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	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 f242ee103277 -r 09846d5169fa test-data/output_read_count.xls
--- a/test-data/output_read_count.xls	Tue May 03 16:36:57 2016 -0400
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,47 +0,0 @@
-#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 f242ee103277 -r 09846d5169fa test-data/pairend_strandspecific_51mer_hg19_chr1_1-100000.R1.fastq
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/pairend_strandspecific_51mer_hg19_chr1_1-100000.R1.fastq	Tue Mar 14 10:23:21 2017 -0400
@@ -0,0 +1,80 @@
+@seq.11990047/1
+ACGGCCGACTTGGATCACACTCTTGCAGGGCCATCAGGCACCAAAGGGATT
++
+hgffghhhhfhhchfhghhhhhhhggahh[chffhfhghhhhhhafehfeh
+@seq.14614493/1
+AGAGGAGGACGAGGACGACTGGGAATCGTAGGGGGCTCCATGACACCTTCC
++
+hhgghehehghgghhaffffcggchghhhhgfhfhahghhhghhghhhhhe
+@seq.24018133/1
+CGGGTGGATTTTCTGTGGGTTTGTTAAGTGGTCAGAAATTCTCAATTTTTT
++
+`aggggecfffa\\^Ua``\af`fffcffffafaffcffffec``fWfffe
+@seq.10608403/1
+GTATGGCCAGAGGGCAGGGCCGAGGGGTGTGGGCGGGAGGCCCGGCCTGGC
++
+_dd_]bfggfgcg[egdbdbdXc`cfggaagdgggf^ggfdfggggggggg
+@seq.10820209/1
+GTGCTGGCCCCAGTTTTCTAACCAGGTGTTGAATGAACTGGATGGACTCTG
++
+ghhccgfgghhhdhfhhghhhfffdf_hfhhhffhhhgdchhhhhgfhahh
+@seq.1537155/1
+GGGAGTGTGCAGAGACTGGAGGGGATGACAGTCACCCTCTGTTTTCTGTGG
++
+aag`hhhhhgghhhhhhfhhchgfacchhhhah]hhdcafhhhhffachhg
+@seq.25274725/1
+AGGGTGTGGGGCAAGGCAGTGAGTGAAGAGTTGGGATGAGTGAGTTAGGGC
++
+hhhhdhhhhhhffffcfdffff_fdffffffhchahhhhchgfhhfhfhhh
+@seq.26326595/1
+GGGAAGGGGGTGCTTCTGCATGGGAAGCACAGACAGCGCTGCCTCTCCCTT
++
+Wbfdf]ddggggdgggdfdfWggdggf]fffadfffffVfffgfgfdgggg
+@seq.28833653/1
+TGGGGCCAGGGGACTATGACACACCACTTGGCTTAGACTGAGGAGCTCTGT
++
+_cffafhdghhhhhhhhhhhghhaffhhhhdhfhhehhhhhhgghfhghhh
+@seq.25049090/1
+AGGGCGAGATTGATTGTTAATTGCTAGCATGAACCGCGTGGGCTTCTCAGG
++
+fdffbfdddb[_afffacdggafdbc[fcfcgggfgffccfgagggggfgc
+@seq.23476912/1
+GGCCTCTCCACCATGTGCTCCACCTCGTGCTGGACCTTAAGAGATACCAAT
++
+fgggggeggecfefffd^^aY]fdfcaggggfdefdggggggggggggggg
+@seq.28059536/1
+GGGATGAGGAGAGGGCAGGAAGGCATTTCCTGGGTAGTGGAGTGCTGTGTT
++
+B_bbea[_V[WZVY`\Pacaaebecd]]fddbaed[decbe]fd`fggggg
+@seq.13270875/1
+TGCCCCGAGTTTGTCAAGAATGTCCCAGTAACCAGGGGACACACAGTGAAG
++
+ffffafgagcggggfgfcfffccfcffg]ggggfgcgggggggggggggcf
+@seq.2214586/1
+GTGGGAGGGGCTGAAGTGAGAGCCCAACTTGGAAGCTTTTACTCCTGGGAG
++
+gghghghhhhhhhhhhffefafhfhhhhhgghhhghhehhhhehhhhhhhh
+@seq.31061198/1
+GAGGAGCTAGGGTTTCTCATAAAACTCCCTGATAGAAGACGACTTTTGATA
++
+cd\WaaaRcaacJdd[dff_f_ffcfddfff_dafffcd[cd\aW\eedcc
+@seq.13835843/1
+GGGGAGGCAGAGGTTGCAGTGAGCCGAGATCATGTCACTGCACTCCAGGCT
++
+ggcgafggfgggggggfgggagggagggefgdffffdadeggggggggegg
+@seq.13539256/1
+GTGGGGAAACCTAGAATTGCTGTAGAGAAAATGCCCTAGAGCAGCTCTAGA
++
+hfhhchfhhhfhghhhhhhhhghghhhgfhhhhhhhhhghhhhfhhhhfhh
+@seq.5556605/1
+GGGATGAGGCCAAATCTTTCTGAATCTGAGATAGCCTCTCAGCCTATGCAT
++
+hfhchhchhhehhhhhhhhdhh_hghchgfhdhhhhhhhhhchhghhhhhh
+@seq.32597077/1
+GAGAGACGGGGTTTCACCATGTTGGCCAGGATGGTCTTGATCTCTTGACCT
++
+dcba]fffcdfdWccf\``S_da_cdc_fdafggggfffcfcfcfddafff
+@seq.20367385/1
+TTAAGTGCACTCAAATAATGTGATTTTATGAGGCTATAGGAGAAAAAAATT
++
+fdddZ`dc[cdadJ_ddScad[[^\^ddadad__daa^a^\]QY\T^ZZZY
diff -r f242ee103277 -r 09846d5169fa test-data/pairend_strandspecific_51mer_hg19_chr1_1-100000.R1.fastq.gz
Binary file test-data/pairend_strandspecific_51mer_hg19_chr1_1-100000.R1.fastq.gz has changed
diff -r f242ee103277 -r 09846d5169fa test-data/pairend_strandspecific_51mer_hg19_chr1_1-100000.R2.fastq
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/pairend_strandspecific_51mer_hg19_chr1_1-100000.R2.fastq	Tue Mar 14 10:23:21 2017 -0400
@@ -0,0 +1,80 @@
+@seq.11990047/2
+CCCGTGGGCAGAGCAAAGGAAGGGCACAGCGCCAGGCAGTGGTGCAGCTGC
++
+hfadfddd`]f[fa_fh]hhcagffhWhhhh]eeehhhha^hfhhhhghhf
+@seq.14614493/2
+TCCCCTCCCAAGGAAGTAGGTCTGAGCAGCTTGTCCTGGCTGTGTCCATGT
++
+hhhhhhhhhehhhhehehhhghhehfhahhdhfdhhfhhhdf]f_ffbdfa
+@seq.24018133/2
+TACCACTATTTTATGAACCAAGTATAACAAGATACTTGAAATGGAAACTAT
++
+fLffddhhhhag_gefafffhaefhfffffchffhhggahhhhRhhgccgh
+@seq.10608403/2
+GGGACCTGCTGTTCCATCGGCTCTCTCTTGCTGATGGACAAGGGGGCATCA
++
+hefchhhfda`]]b]a^aLa^[Za^WdWb[faff]fd]defQacffdRd]f
+@seq.10820209/2
+GCCCGGGGAAAACATGCATCACAGTTCATCTCGAGTCAGCAGGATTTTGAC
++
+ffcddeed]eaTfccfffffceee]ffdcdcee[efdaffffdSfhhdc]d
+@seq.1537155/2
+TNNATCAATCAGCAGGNNNCGTGCACTCTCTTTGAGCCACCACAGAAAACA
++
+VBBVT^WZ^^I[]V]YBBBIVS[W[eeKceccaccUfaffff_afghg`gd
+@seq.25274725/2
+GGCNCCTCCNTGCCCTNCTNAAAANNCAATCACAGCTCCCTAACAGTCCTG
++
+^UZB]]]Y]B][IS[[B]]BW][XBB\WaadddddhhghgffffaGVV[Se
+@seq.26326595/2
+CATGCGTGCCCTGCTCGANATCCAATCACAGCTCCCTAACACTCCTGAATC
++
+^K^K_YT[YVe_eLe[INBTYZUV^S`babhacfhhccghhahghhdaghW
+@seq.28833653/2
+CAGCAGCTATTTCCTGNTNACTCAANCAATGGCCCCATTTCCCTGGTGGAA
++
+fLdYfeYdddXbbabSBWBTY[[[]BdeedfffffghhhghdfgLfbfddg
+@seq.25049090/2
+CTNCCCTTANTCCGAANGCNGCTCNNCTGATTGGTTAATTTTTGCGTAGCT
++
+VVBNZT[]]BSHZWS[BZHBTQPOBBZUZO]bZ^^hfehffff[fcfd_]g
+@seq.23476912/2
+TNACTGATTNCTCTCCACTNTAGANNCTGAGAAGCCCACGCTGTTCATGCT
++
+`Ba_a^]^\Bbab\aa`b`BV]^VBBZV[Z`a^abffYfaa^e^dedbdd]
+@seq.28059536/2
+CGTNTGACTCTAGACCNTNNGAAGCCCACGCGGTTCATTCTAGCAAGTAAC
++
+ZXZBY`\`]][dcKcUBVBBWNVV]ghchfdcc]ecccLa`edecf_cfdf
+@seq.13270875/2
+TAGATTATCAACAGGGGAGAGATAGCATTTCCTGAAGGCTTCCTAGGTGCC
++
+eghggd_hhhfahhg\K^[[ffafchehg_ffWffhgceghhhhhffLfcY
+@seq.2214586/2
+GNNTGCANANATAGANNTTNCCACACTGCCTTGCACAGGAGCACTGCGGGG
++
+VBBSITZBVBTTRHXBBZYBVUUVHH[QV[chhghacKaa_eeeeghgghg
+@seq.31061198/2
+GNCGGAAAAAAAAATTNNNNAAAATNCGTCTGCTATCAGGGAGTTTTATGA
++
+VB[NV^\_]_`hfccXBBBBTUT[TBa_aLTRNQQaYcaeaKa^adcS\Vd
+@seq.13539256/2
+CCTATTTTTTTTTTTTTTTTTGACACAGGTTCTCTGTCACCCAGCCTGGGG
++
+hhhhhhhhhhhghhhghhghfccWKVVYZRd[_[aZQYZ^``WT`[L^^Q\
+@seq.13835843/2
+TCCATCTTTTTTTTTTTTTTTTTGACACAGGTTCTCTGTCACCCAGCCTGG
++
+ghhhggffhhhhhhhhhhhghhh]fMPLPVW^^WXUZ\WXL[VVJY`\Wbb
+@seq.5556605/2
+GCAGCTANGNCCATCNNNTTTGAAANCCAGATTTCGTTTTAAACCAGAGGA
++
+fLfLf]VBTBI]]]]BBB[^WW[]XBdede`eedeffhhehffhhhhahee
+@seq.20367385/2
+ATTTGGCAGAGAAGCAAACACCAGTCGGAGAGCTGGGGCCCTCCCAGCCCT
++
+W_\_^W___WdcfceVIW[T^aa\[aaacaQYYSZY`KK````^[GaQZ\Y
+@seq.17373919/2
+TTTTTGTTTTTTTTTTTTTTTGAGTCAGAATCTCGCTCTGTTGCCCAGGCT
++
+hgghhhhhhSfffffhgh`h__Wb`ZZZ_]PVPUSVYVQVaWWacaQa^BB
diff -r f242ee103277 -r 09846d5169fa tin.xml
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/tin.xml	Tue Mar 14 10:23:21 2017 -0400
@@ -0,0 +1,144 @@
+<tool id="rseqc_tin" name="Transcript Integrity Number" version="@WRAPPER_VERSION@">
+    <description>
+        evaluates RNA integrity at a transcript level
+    </description>
+
+    <macros>
+        <import>rseqc_macros.xml</import>
+    </macros>
+
+    <expand macro="requirements" />
+
+    <expand macro="stdio" />
+
+    <version_command><![CDATA[tin.py --version]]></version_command>
+
+    <!-- Generate output files here because tin.py removes all instances of "bam"
+    in the filename -->
+    <command><![CDATA[
+        #import re
+        ln -sf '${input}' 'input.bam' &&
+        ln -sf '${input.metadata.bam_index}' 'input.bam.bai' &&
+        tin.py -i 'input.bam' --refgene='${refgene}' --minCov=${minCov}
+        --sample-size=${samplesize} ${subtractbackground}
+        ]]>
+    </command>
+
+    <inputs>
+        <expand macro="bam_param" />
+        <expand macro="refgene_param" />
+        <param name="minCov" type="integer" value="10" label="Minimum coverage (default=10)"
+            help="Minimum number of reads mapped to a transcript (--minCov)." />
+        <param name="samplesize" type="integer" value="100" label="Sample size (default=100)"
+            help="Number of equal-spaced nucleotide positions picked from mRNA.
+            Note: if this number is larger than the length of mRNA (L), it will
+            be halved until is's smaller than L. (--sample-size)." />
+        <param name="subtractbackground" type="boolean" value="false" falsevalue=""
+            truevalue="--subtract-background" label="Subtract background noise
+            (default=No)" help="Subtract background noise (estimated from
+            intronic reads). Only use this option if there are substantial
+            intronic reads (--subtract-background)." />
+    </inputs>
+
+    <outputs>
+        <data name="outputsummary" format="tabular" from_work_dir="input.summary.txt" label="TIN on ${on_string} (summary)" />
+        <data name="outputxls" format="xls" from_work_dir="input.tin.xls" label="TIN on ${on_string} (tin)" />
+    </outputs>
+
+    <!-- PDF Files contain R version, must avoid checking for diff -->
+    <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="outputsummary" file="output.tin.summary.txt"/>
+            <output name="outputxls" file="output.tin.xls"/>
+        </test>
+    </tests>
+
+    <help><![CDATA[
+## tin.py
+
+This program is designed to evaluate RNA integrity at transcript level. TIN
+(transcript integrity number) is named in analogous to RIN (RNA integrity
+number). RIN (RNA integrity number) is the most widely used metric to
+evaluate RNA integrity at sample (or transcriptome) level. It is a very
+useful preventive measure to ensure good RNA quality and robust,
+reproducible RNA sequencing. However, it has several weaknesses:
+
+* RIN score (1 <= RIN <= 10) is not a direct measurement of mRNA quality.
+  RIN score heavily relies on the amount of 18S and 28S ribosome RNAs, which
+  was demonstrated by the four features used by the RIN algorithm: the
+  “total RNA ratio” (i.e. the fraction of the area in the region of 18S and
+  28S compared to the total area under the curve), 28S-region height, 28S
+  area ratio and the 18S:28S ratio24. To a large extent, RIN score was a
+  measure of ribosome RNA integrity. However, in most RNA-seq experiments,
+  ribosome RNAs were depleted from the library to enrich mRNA through either
+  ribo-minus or polyA selection procedure.
+
+* RIN only measures the overall RNA quality of an RNA sample. However, in  real
+  situation, the degradation rate may differs significantly among
+  transcripts, depending on factors such as “AU-rich sequence”, “transcript
+  length”, “GC content”, “secondary structure” and the “RNA-protein
+  complex”. Therefore, RIN is practically not very useful in downstream
+  analysis such as adjusting the gene expression count.
+
+* RIN has very limited sensitivity to measure substantially degraded RNA
+  samples such as preserved clinical tissues. (ref:
+  http://www.illumina.com/documents/products/technotes/technote-truseq-rna-access.pdf).
+
+To overcome these limitations, we developed TIN, an algorithm that is able
+to measure RNA integrity at transcript level. TIN calculates a score (0 <=
+TIN <= 100) for each expressed transcript, however, the medTIN (i.e.
+meidan TIN score across all the transcripts) can also be used to measure
+the RNA integrity at sample level. Below plots demonstrated TIN is a
+useful metric to measure RNA integrity in both transcriptome-wise and
+transcript-wise, as demonstrated by the high concordance with both RIN and
+RNA fragment size (estimated from RNA-seq read pairs).
+
+
+## Inputs
+
+Input BAM/SAM file
+    Alignment file in BAM/SAM format.
+
+Reference gene model
+    Gene Model in BED format. Must be standard 12-column BED file.
+
+Minimum coverage
+    Minimum number of reads mapped to a tracript (default is 10).
+
+Sample size
+    Number of equal-spaced nucleotide positions picked from mRNA. Note: if
+    this number is larger than the length of mRNA (L), it will be halved until
+    it’s smaller than L (default is 100).
+
+Subtract background
+    Subtract background noise (estimated from intronic reads). Only use this
+    option if there are substantial intronic reads.
+
+
+## Outputs
+
+Text
+    Table that includes the gene identifier (geneID), chromosome (chrom),
+    transcript start (tx_start), transcript end (tx_end), and transcript
+    integrity number (TIN).
+
+Example output:
+
+------  -----  ----------  ---------  -------------
+geneID  chrom  tx_start    tx_end     TIN
+------  -----  ----------  ---------  -------------
+ABCC2   chr10   101542354  101611949  67.6446525761
+IPMK    chr10   59951277   60027694   86.383618429
+RUFY2   chr10   70100863   70167051   43.8967503948
+------  -----  ----------  ---------  -------------
+
+@ABOUT@
+
+]]>
+    </help>
+
+    <expand macro="citations" />
+
+</tool>
diff -r f242ee103277 -r 09846d5169fa tool_dependencies.xml
--- a/tool_dependencies.xml	Tue May 03 16:36:57 2016 -0400
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,12 +0,0 @@
-<?xml version="1.0"?>
-<tool_dependency>
-    <package name="R" version="3.0.3">
-        <repository changeset_revision="afc48696ee5c" 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="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" />
-    </package>
-</tool_dependency>