--- a/read_GC.xml	Thu Jul 11 12:33:27 2013 -0400
+++ b/read_GC.xml	Wed Oct 02 02:20:04 2013 -0400
@@ -1,31 +1,28 @@
-<tool id="read_GC" name="Read GC">
+<tool id="read_GC" name="Read GC" version="1.1">
 	<description>determines GC% and read count</description>
 	<requirements>
-		<requirement type="package" version="2.15.1">R</requirement>
+		<requirement type="package" version="2.11.0">R</requirement>
+		<requirement type="package" version="1.7.1">numpy</requirement>
 		<requirement type="package" version="2.3.7">rseqc</requirement>
 	</requirements>
-	<command interpreter="python"> read_GC.py -i $input -o output
+	<command> read_GC.py -i $input -o output
 	</command>
 	<inputs>
 		<param name="input" type="data" format="bam,sam" label="input bam/sam file" />
 	</inputs>
 	<outputs>
-		<data format="xls" name="outputxls" from_work_dir="output.dup.pos.DupRate.xls"/>
-		<data format="xls" name="outputseqxls" from_work_dir="output.dup.seq.DupRate.xls"/>
-		<data format="r" name="outputr" from_work_dir="output.DupRate_plot.r" />
-		<data format="pdf" name="outputpdf" from_work_dir="output.DupRate_plot.pdf" />
+		<data format="xls" name="outputxls" from_work_dir="output.GC.xls" label="${tool.name} on ${on_string} (XLS)"/>
+		<data format="r" name="outputr" from_work_dir="output.GC_plot.r" label="${tool.name} on ${on_string} (R Script)" />
+		<data format="pdf" name="outputpdf" from_work_dir="output.GC_plot.pdf" label="${tool.name} on ${on_string} (PDF)" />
 	</outputs>
+    <stdio>
+        <exit_code range="1:" level="fatal" description="An error occured during execution, see stderr and stdout for more information" />
+        <regex match="[Ee]rror" source="both" description="An error occured during execution, see stderr and stdout for more information" />
+    </stdio>
 	<help>
-		.. image:: https://code.google.com/p/rseqc/logo?cct=1336721062
+read_GC.py
+++++++++++
 
------
-
-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.
 
 Inputs
 ++++++++++++++
@@ -40,7 +37,24 @@
 2. output.GC_plot.r: R script to generate pdf file.
 3. output.GC_plot.pdf: graphical output generated from R script. 
 
-.. image:: http://dldcc-web.brc.bcm.edu/lilab/liguow/RSeQC/figure/read_gc.png
+.. image:: http://rseqc.sourceforge.net/_images/read_gc.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/
+
 
 	</help>
 </tool>