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<tool id="cnmops" name="cn.mops" version="1.0.0">
  <description>cnv caller</description>
  <requirements>
        <requirement type="package" version="1.16.2">bioconductor-cn.mops</requirement>
    </requirements>
  <command interpreter="Rscript">
   cnmops.R $args_file
  </command>
  <configfiles>
    <configfile name="args_file">target=$targetFile
padding=$padding
mapping_mode=$mapping_mode
#for $i in $inputs
bam=${i.input}
bam_bai=${i.input.metadata.bam_index}
#if str($i.label.value) != "":
bam_label=${$i.label.value}
#else
bam_label=${i.input.dataset.name}
#end if
#end for
output=$output
#if str($advanced_options.advanced_options_select) == "yes"
advanced_mode=TRUE
$advanced_options.prior_impact=$prior_impact
$advanced_options.cyc=$cyc
$advanced_options.norm=$norm
$advanced_options.norm_type=$norm_type
$advanced_options.upper_threshold=$upper_threshold
$advanced_options.lower_threshold=$lower_threshold
$advanced_options.min_width=$min_width
$advanced_options.seq_alg=$seq_alg
$advanced_options.min_read_count=$min_read_count
$advanced_options.use_median=$use_median
#end if
</configfile>
  </configfiles>
  <inputs>
    <param format="bed" name="targetFile" type="data" label="Target regions (BED)">
      <validator type="unspecified_build" />
    </param>
    <param name="padding" type="integer" value="100" label="Padding" help="Amount of padding (in bp) to add around each target region" />
    <param name="mapping_mode" type="select" label="Mapping mode" help="Select whether the mapping algorithm was run using paired or unpaired reads">
        <option value="paired" selected="true">paired</option>
        <option value="unpaired">unpaired</option>
    </param>
    <repeat name="inputs" title="BAM" min="2" help="Need to add more files? Use controls below.">
      <param format="bam" name="input" type="data" label="BAM file">
        <options>
          <filter type="data_meta" ref="targetFile" key="dbkey"/>
        </options>
      </param>
      <param name="label" type="text" size="30" value="" label="Label" help="Label to use in the output. If not given, the dataset name will be used instead">
        <validator type="regex" message="Spaces are not allowed">^\S*$</validator>
      </param>
    </repeat>
    
    <!-- Advanced options -->
    <conditional name="advanced_options">
      <param name="advanced_options_select" type="select" label="Show advanced options">
        <option value="yes">Yes</option>
        <option value="no" selected="true">No</option>
      </param>
      <when value="yes">
        <param name="prior_impact" type="integer" value="10" label="Prior impact" help="Positive real value that reflects how strong the prior assumption affects the result. The higher the value the more samples will be assumed to have copy number 2." />
        <param name="cyc" type="integer" value="20" label="Cycles" help="Positive integer that sets the number of cycles for the algorithm. Usually after less than 15 cycles convergence is reached." />
        <param name="norm" type="boolean" truevalue="TRUE" falsevalue="FALSE" checked="true" label="Apply normalization" help="" />
        <param name="norm_type" type="select" label="Normalization type" help="Mode of the normalization technique. Read counts will be scaled sample-wise.">
          <option value="poisson" selected="true">poisson</option>
          <option value="mean">mean</option>
          <option value="min">min</option>
          <option value="median">median</option>
          <option value="quant">quant</option>
          <option value="mode">mode</option>
        </param>
        <param name="upper_threshold" type="float" value="0.55" label="Cut-off for copy number gains" help="All CNV calling values above this value will be called as gain. The value should be set close to the log2 of the expected foldchange for copy number 3 or 4." />
        <param name="lower_threshold" type="float" value="-0.8" label="Cut-off for copy number losses" help="All CNV calling values below this value will be called as loss. The value should be set close to the log2 of the expected foldchange for copy number 1 or 0." />
        <param name="min_width" type="integer" value="5" label="Minimum width" help="Minimum number of segments a CNV should span." />
        <param name="seq_alg" type="select" label="Segmentation algorithm" help="">
          <option value="fast" selected="false">fast</option>
          <option value="DNAcopy">DNAcopy</option>
        </param>
        <param name="min_read_count" type="integer" value="1" label="Minimum read count" help="If all samples are below this value the algorithm will return the prior knowledge. This prevents the algorithm from being applied to segments with very low coverage." />
        <param name="use_median" type="boolean" truevalue="TRUE" falsevalue="FALSE" checked="false" label="Use median" help="Whether median instead of mean of a target region should be used for the CNV call." />
    </when>
      <when value="no" />
    </conditional>
  </inputs>
  <outputs>
    <data format="bed" name="output" label="${tool.name} on ${on_string}" />
  </outputs>
  <help>

**What it does**

This tool uses cn.mops (Copy Number estimation by a Mixture Of PoissonS) to call copy number variations
and aberrations (CNVs and CNAs) from targeted next generation sequencing (NGS) data.

**Output format**

========== ========================
Column     Description
---------- ------------------------
chr        Chromosome
starts     Start of CNV region
ends       End of CNV region
sampleName Name of the sample with CNV
median     Median value of CNV
mean       Mean value of CNV
CN         Copy number class (see below)
========== ========================

Copy number classes are identified as follows::

 CN2: normal copy number for diploid samples
 CN1: heterozygous deletion 
 CN0: homozygous deletion 
 CN3 - CN8: amplifications
 
For non-tumor samples the highest copy number class is 8 - higher copy numbers have not been reported.
CN8 is expected to have 4 times as many reads (for times as high coverage) as CN2.
For tumor samples very high copy numbers have been observed (e.g. CN64),
therefore the parameters of cn.mops have to be adjusted to allow for high copy numbers.
A way to set the parameters is given in https://gist.github.com/gklambauer/8955203

**License and citation**

This Galaxy tool is Copyright © 2015 `CRS4 Srl.`_ and is released under the `MIT license`_.

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

You can use this tool only if you agree to the license terms of: `cn.mops`_.

.. _cn.mops: http://bioconductor.org/packages/release/bioc/html/cn.mops.html

If you use this tool, please cite:

- |Cuccuru2014|_
- |Klambauer2012|_.

.. |Cuccuru2014| replace:: Cuccuru, G., Orsini, M., Pinna, A., Sbardellati, A., Soranzo, N., Travaglione, A., Uva, P., Zanetti, G., Fotia, G. (2014) Orione, a web-based framework for NGS analysis in microbiology. *Bioinformatics* 30(13), 1928-1929
.. _Cuccuru2014: http://bioinformatics.oxfordjournals.org/content/30/13/1928
.. |Klambauer2012| replace:: Klambauer, G., *et al.* (2012) cn.MOPS: Mixture of Poissons for Discovering Copy Number Variations in Next Generation Sequencing Data with a Low False Discovery Rate. *Nucleic Acids Research* 40, e69
.. _Klambauer2012: http://http://nar.oxfordjournals.org/content/40/9/e69
  </help>
  <citations>
    <citation type="doi">10.1093/bioinformatics/btu135</citation>
    <citation type="doi">10.1093/nar/gks003</citation>
  </citations>
</tool>