<tool id="read_GC" name="Read GC">
	<description>determines GC% and read count</description>
	<requirements>
		<requirement type="package" version="2.15.1">R</requirement>
		<requirement type="package" version="2.3.7">rseqc</requirement>
	</requirements>
	<command interpreter="python"> 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" />
	</outputs>
	<help>
		.. image:: https://code.google.com/p/rseqc/logo?cct=1336721062

-----

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
++++++++++++++

Input BAM/SAM file
	Alignment file in BAM/SAM format.

Output
++++++++++++++

1. output.GC.xls: Two column, plain text file, first column is GC%, second column is read count
2. output.GC_plot.r: R script to generate pdf file.
3. output.GC_plot.pdf: graphical output generated from R script. 

.. image:: http://dldcc-web.brc.bcm.edu/lilab/liguow/RSeQC/figure/read_gc.png

	</help>
</tool>