Wrapper for read_quality.py tool from the RSeQC package.

read_quality.xml

<tool id="read_quality" name="Read Quality">
	<description>determines Phred quality score</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_quality.py -i $input -o output -r $reduce
	</command>
	<inputs>
		<param name="input" type="data" format="bam,sam" label="input bam/sam file" />
		<param name="reduce" type="integer" label="Ignore Phred scores less than this amount (only applies to 'boxplot', default=1000)" value="1000" />
	</inputs>
	<outputs>
		<data format="r" name="outputr" from_work_dir="output.qual.r" />
		<data format="pdf" name="outputpdf" from_work_dir="output.qual.heatmap.pdf" />
		<data format="pdf" name="outputbxpdf" from_work_dir="output.qual.boxplot.pdf" />
	</outputs>
	<tests>
		<test>
			<param name="input" value="Pairend_nonStrandSpecific_36mer_Human_hg19.bam" />
			<output name="outputr" file="readqualout.qual.r" />
			<output name="outputpdf" file="readqualout.qual.heatmap.pdf" />
			<output name="outputbxpdf" file="readqualout.qual.boxplot.pdf" />
		</test>
	</tests>
	<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.

Ignore phred scores less than this number (default=1000)
	To avoid making huge vector in R, nucleotide with certain phred score represented less than this number will be ignored. Increase this number save more memory while reduce precision. This option only applies to the 'boxplot'.

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

1. output.qual.r
2. output.qual.boxplot.pdf
.. image:: http://dldcc-web.brc.bcm.edu/lilab/liguow/RSeQC/figure/36mer.qual.plot.png
3. output.qual.heatmap.pdf
.. image:: http://dldcc-web.brc.bcm.edu/lilab/liguow/RSeQC/figure/36mer.qual.heatmap.png
use different color to represent nucleotide density ("blue"=low density,"orange"=median density,"red"=high density")

	</help>
</tool>