comparison read_NVC.xml @ 32:580ee0c4bc4e

Fixes from Bjorn Gruning: create symlinks under $TMP and clean them up afterwards, replace R dependency with the Tool Shed R3 package, add --install-scripts, prepend tool-ids with rseqc

31:cc5eaa9376d8

<tool id="read_NVC" name="Read NVC" version="1.1">
	<description>to check the nucleotide composition bias</description>
	<requirements>
		<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> read_NVC.py -i $input -o output

		#if $nx
			-x
		#end if
	</command>
	<inputs>
		<param name="input" type="data" format="bam,sam" label="input bam/sam file" />
		<param name="nx" type="boolean" label="Include N,X in NVC plot" value="false" />
	</inputs>
	<outputs>
		<data format="xls" name="outputxls" from_work_dir="output.NVC.xls" label="${tool.name} on ${on_string} (XLS)" />
		<data format="r" name="outputr" from_work_dir="output.NVC_plot.r" label="${tool.name} on ${on_string} (R Script)" />
		<data format="pdf" name="outputpdf" from_work_dir="output.NVC_plot.pdf" label="${tool.name} on ${on_string} (PDF)" />
	</outputs>
    <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>
read_NVC.py
+++++++++++

This module is used to check the nucleotide composition bias. Due to random priming, certain
patterns are over represented at the beginning (5'end) of reads. This bias could be easily

Inputs
++++++++++++++

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

Include N,X in NVC plot
	Plots N and X alongside A, T, C, and G in plot.

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

This module is used to check the nucleotide composition bias. Due to random priming, certain patterns are over represented at the beginning (5'end) of reads. This bias could be easily examined by NVC (Nucleotide versus cycle) plot. NVC plot is generated by overlaying all reads together, then calculating nucleotide composition for each position of read (or each sequencing cycle). In ideal condition (genome is random and RNA-seq reads is randomly sampled from genome), we expect A%=C%=G%=T%=25% at each position of reads.

.. image:: http://rseqc.sourceforge.net/_static/logo.png

.. _RSeQC: http://rseqc.sourceforge.net/


	</help>
</tool>

32:580ee0c4bc4e

<tool id="rseqc_read_NVC" name="Read NVC" version="1.1">
    <description>to check the nucleotide composition bias</description>
    <requirements>
        <requirement type="package" version="3.0.1">R</requirement>
        <requirement type="package" version="1.7.1">numpy</requirement>
        <requirement type="package" version="2.3.7">rseqc</requirement>
    </requirements>
    <command>
        read_NVC.py -i $input -o output $nx
    </command>
    <stdio>
        <exit_code range="1:" level="fatal" description="An error occured during execution, see stderr and stdout for more information" />
        <regex match="[Ee]rror" source="both" description="An error occured during execution, see stderr and stdout for more information" />
    </stdio>
    <inputs>
        <param name="input" type="data" format="bam,sam" label="input bam/sam file" />
        <param name="nx" type="boolean" value="false" truevalue="-x" falsevalue="" label="Include N,X in NVC plot"/>
    </inputs>
    <outputs>
        <data format="xls" name="outputxls" from_work_dir="output.NVC.xls" label="${tool.name} on ${on_string} (XLS)" />
        <data format="txt" name="outputr" from_work_dir="output.NVC_plot.r" label="${tool.name} on ${on_string} (R Script)" />
        <data format="pdf" name="outputpdf" from_work_dir="output.NVC_plot.pdf" label="${tool.name} on ${on_string} (PDF)" />
    </outputs>
    <help>
read_NVC.py
+++++++++++

This module is used to check the nucleotide composition bias. Due to random priming, certain
patterns are over represented at the beginning (5'end) of reads. This bias could be easily

Inputs
++++++++++++++

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

Include N,X in NVC plot
    Plots N and X alongside A, T, C, and G in plot.

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

This module is used to check the nucleotide composition bias. Due to random priming, certain patterns are over represented at the beginning (5'end) of reads. This bias could be easily examined by NVC (Nucleotide versus cycle) plot. NVC plot is generated by overlaying all reads together, then calculating nucleotide composition for each position of read (or each sequencing cycle). In ideal condition (genome is random and RNA-seq reads is randomly sampled from genome), we expect A%=C%=G%=T%=25% at each position of reads.

.. image:: http://rseqc.sourceforge.net/_static/logo.png

.. _RSeQC: http://rseqc.sourceforge.net/


    </help>
</tool>