view emboss_cpgplot.xml @ 10:9b98d3d903c6 draft

planemo upload for repository https://github.com/galaxyproject/tools-devteam/tree/master/tools/emboss_5 commit fc158bfe5f5927dc199321a2cf43310373cbc8ba
author devteam
date Fri, 12 Aug 2016 19:17:10 -0400
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<tool id="EMBOSS: cpgplot15" name="cpgplot" version="5.0.0">
  <description>Plot CpG rich areas</description>
  <requirements><requirement type="package" version="5.0.0">emboss</requirement></requirements>
  <command interpreter="perl">emboss_cpgplot_wrapper.pl cpgplot -sequence $input1 -window $window -minlen $minlen -minpc $minpc -outfile $outfile -graph png -goutfile $goutfile -outfeat $outfeat -minoe $minoe -auto</command>
  <inputs>
    <param format="data" name="input1" type="data">
      <label>On query</label>
    </param>
    <param name="window" type="integer" value="100">
      <label>Window Size</label>
    </param>
    <param name="minlen" type="integer" value="200">
      <label>Minimum length</label>
    </param>
    <param name="minoe" type="float" value="0.6">
      <label>Minimum average observed to expected ratio</label>
    </param>
    <param name="minpc" type="float" value="50.0">
      <label>Minimum average percentage of G plus C</label>
    </param>
  </inputs>
  <outputs>
    <data format="cpgplot" name="outfile" />
    <data format="png" name="goutfile" />
    <data format="gff" name="outfeat" />
  </outputs>
  <code file="emboss_format_corrector.py" />
  <help>
    You can view the original documentation here_.
    
    .. _here: http://emboss.sourceforge.net/apps/release/5.0/emboss/apps/cpgplot.html

------

**Citation**

For the underlying tool, please cite `Rice P, Longden I, Bleasby A. EMBOSS: the European Molecular Biology Open Software Suite. Trends Genet. 2000 Jun;16(6):276-7. &lt;http://www.ncbi.nlm.nih.gov/pubmed/10827456&gt;`_

If you use this tool in Galaxy, please cite `Blankenberg D, Taylor J, Schenck I, He J, Zhang Y, Ghent M, Veeraraghavan N, Albert I, Miller W, Makova KD, Hardison RC, Nekrutenko A. A framework for collaborative analysis of ENCODE data: making large-scale analyses biologist-friendly. Genome Res. 2007 Jun;17(6):960-4. &lt;http://www.ncbi.nlm.nih.gov/pubmed/17568012&gt;`_
  </help>
</tool>