annotate build-icm_wrapper.xml @ 0:9c8ffce71f7c draft default tip

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<tool id="build_icm_wrapper" name="Build-ICM" version="0.2">
  <description></description>
  <requirements>
    <requirement type="package" version="3.02">glimmer</requirement>
  </requirements>
  <command interpreter="python">
    build-icm_wrapper.py --biSequence $biSequence
    #if str($biDepth)
      --biDepth=$biDepth
    #end if
    #if $biNoStops
      --biNoStops
    #end if
    #if str($biPeriod)
      --biPeriod=$biPeriod
    #end if
    #if $biReverse
      --biReverse
    #end if
    #if str($biWidth)
      --biWidth=$biWidth
    #end if
    #if str($biTransTable)
      --biTransTable=$biTransTable
    #end if
    #if $biStopCodons
      --biStopCodons="$biStopCodons"
    #end if
    --biIcm $biIcm --logfile $logfile
  </command>

  <inputs>
    <param name="biSequence" type="data" format="fasta" label="DNA sequences to be analyzed" help="FASTA format" />

    <param name="biDepth" type="integer" value="7" optional="true" label="Depth of the ICM (-d, --depth)" help="The depth is the maximum number of positions in the context window that will be used to determine the probability of the predicted position. The default value is 7." />

    <param name="biNoStops" type="boolean" checked="false" label="Do not use any input strings with in-frame stop codons (-F, --no_stops)" help="" />

    <param name="biPeriod" type="integer" value="3" optional="true" label="Period of the ICM (-p, --period)" help="The period is the number of different submodels for different positions in the text in a cyclic pattern. E.g., if the period is 3, the first submodel will determine positions 1, 4, 7, etc; the second submodel will determine positions 2, 5, 8, etc; and the third submodel will determine positions 3, 6, 9, etc. For a non-periodic model, use a value of 1. The default value is 3." />

    <param name="biReverse" type="boolean" checked="false" label="Use the reverse of the input strings to build the ICM (-r, --reverse)" help="Note that this is merely the reverse and NOT the reverse-complement. In other words, the model is built in the backwards direction." />

<!--
    <param name="biText" type="boolean" optional="true" truevalue="true" falsevalue="false" checked="False" label="Output the model in a text format (-t, - -text)" help="This is for informational/debugging purposes only - the glimmer3 program cannot read models in this form." />

    <param name="biVerbose" type="integer" value="" optional="true" label="Verbose level (-v, - -verbose)" help="This controls extra debugging output: the higher the value the more output." />
-->

    <param name="biWidth" type="integer" value="12" optional="true" label="Width of the ICM (-w, --width)" help="The width includes the predicted position. The default value is 12." />

    <param name="biTransTable" type="integer" value="" optional="true" label="Use GenBank translation table number n to specify stop codons (-z, --trans_table)" help="" />

    <param name="biStopCodons" type="text" value="" optional="true" label="Specify allowable stop codons as a comma-separated list (-Z, --stop_codons)" help="Sample format: 'tag,tga,taa'. The default stop codons are tag, tga and taa." />
  </inputs>

  <outputs>
    <data name="logfile" format="txt" label="${tool.name} on ${on_string}: log" />
    <data name="biIcm" format="glimmer_icm" label="${tool.name} on ${on_string}: ICM" />
  </outputs>

  <tests>

  </tests>
  <help>
**What it does**

A probability model of coding sequences, called an interpolated context model or ICM, must be built. This is done by the program *build-icm* from a set of training sequences. These sequences can be obtained in several ways:

1) From known genes in the genome, e.g. genes identified by homology searches.
2) From long, non-overlapping ORFs in the genome as produced by the program *long-orfs*.
3) From genes in a highly similar species/strain.


**License and citation**

This Galaxy tool is Copyright © 2013 `CRS4 Srl.`_ and is released under the `MIT license`_.

.. _CRS4 Srl.: http://www.crs4.it/
.. _MIT license: http://opensource.org/licenses/MIT

If you use this tool in Galaxy, please cite |Cuccuru2013|_.

.. |Cuccuru2013| replace:: Cuccuru, G., Orsini, M., Pinna, A., Sbardellati, A., Soranzo, N., Travaglione, A., Uva, P., Zanetti, G., Fotia, G. (2013) Orione, a web-based framework for NGS analysis in microbiology. *Submitted*
.. _Cuccuru2013: http://orione.crs4.it/

This tool uses `Glimmer`_, which is licensed separately. Please cite |Delcher2007|_.

.. _Glimmer: http://ccb.jhu.edu/software/glimmer/index.shtml
.. |Delcher2007| replace:: Delcher, A. L., Bratke, K. A., Powers, E. C., Salzberg, S. L. (2007) Identifying bacterial genes and endosymbiont DNA with Glimmer. *Bioinformatics* 23(6), 673-679
.. _Delcher2007: http://bioinformatics.oxfordjournals.org/content/23/6/673
  </help>
</tool>