comparison picard_MarkDuplicates.xml @ 3:52fdfc45590a draft

planemo upload for repository https://github.com/galaxyproject/tools-devteam/tree/master/tools/picard commit 00a7926c285bc4a339bd7deebf40b28f39c7d947-dirty

3:52fdfc45590a

<tool name="MarkDuplicates" id="picard_MarkDuplicates" version="@TOOL_VERSION@.0">
  <description>examine aligned records in BAM datasets to locate duplicate molecules</description>
  <macros>
    <import>picard_macros.xml</import>
  </macros>
  <expand macro="requirements" />
  <command>
    @java_options@
    
    java -jar \$JAVA_JAR_PATH/picard.jar
    MarkDuplicates
    
    INPUT="${inputFile}"
    OUTPUT="${outFile}"
    
    METRICS_FILE="${metrics_file}"
    #for $element in $comments:
      COMMENT="${element.comment}"
    #end for
    REMOVE_DUPLICATES="${remove_duplicates}"
    ASSUME_SORTED="${assume_sorted}"
    
    DUPLICATE_SCORING_STRATEGY="${duplicate_scoring_strategy}"
    
    #import pipes
    READ_NAME_REGEX=${ pipes.quote( str( $read_name_regex ) ) or "''" }
    OPTICAL_DUPLICATE_PIXEL_DISTANCE="${optical_duplicate_pixel_distance}"
    
    VALIDATION_STRINGENCY="${validation_stringency}"
    QUIET=true
    VERBOSITY=ERROR
  
  </command>
  <inputs>
    <param format="bam" name="inputFile" type="data" label="Select SAM/BAM dataset or dataset collection" help="If empty, upload or import a SAM/BAM dataset"/>
    <repeat name="comments" title="Comment" min="0" help="You can provide multiple comments">
      <param name="comment" type="text" size="50" label="Add this comment to BAM dataset"/>
    </repeat>
    <param name="remove_duplicates" type="boolean" label="If true do not write duplicates to the output file instead of writing them with appropriate flags set" help="REMOVE_DUPLICATES; default=False"/>
    <param name="assume_sorted" type="boolean" label="Assume the input file is already sorted" checked="true" truevalue="true" falsevalue="false" help="ASSUME_SORTED; default=True"/>

    <param name="duplicate_scoring_strategy" type="select" label="The scoring strategy for choosing the non-duplicate among candidates" help="DUPLICATE_SCORING_STRATEGY; default=SUM_OF_BASE_QUALITIES">
      <option value="SUM_OF_BASE_QUALITIES">SUM_OF_BASE_QUALITIES</option>
      <option value="TOTAL_MAPPED_REFERENCE_LENGTH">TOTAL_MAPPED_REFERENCE_LENGTH</option>
    </param>


    <param name="read_name_regex" type="text" size="40" value="[a-zA-Z0-9]+:[0-9]:([0-9]+):([0-9]+):([0-9]+).*." label="Regular expression that can be used to parse read names in the incoming SAM/BAM dataset" help="READ_NAME_REGEX; Read names are parsed to extract three variables: tile/region, x coordinate and y coordinate. These values are used to estimate the rate of optical duplication in order to give a more accurate estimated library size. See help below for more info; default=[a-zA-Z0-9]+:[0-9]:([0-9]+):([0-9]+):([0-9]+).*.">
      <sanitizer>
        <valid initial="string.printable">
        </valid>
      </sanitizer>
    </param>
    <param name="optical_duplicate_pixel_distance" type="integer" value="100" min="0" max="500" label="The maximum offset between two duplicte clusters in order to consider them optical duplicates" help="OPTICAL_DUPLICATE_PIXEL_DISTANCE; default=100"/>

   <expand macro="VS" />
    
  </inputs> 
  
  <outputs>
    <data format="txt" name="metrics_file" label="${tool.name} on ${on_string}: MarkDuplicate metrics"/>
    <data format="bam" name="outFile" label="${tool.name} on ${on_string}: MarkDuplicates BAM output"/>
  </outputs>
  
  <tests>
    <test>
      <param name="inputFile" value="picard_MarkDuplicates.bam" ftype="bam"/>
      <param name="comment" value="test-run"/>
      <param name="assume_sorted" value="True"/>
      <param name="remove_duplicates" value="True"/>
      <param name="read_name_regex" value="[a-zA-Z0-9]+:[0-9]:([0-9]+):([0-9]+):([0-9]+).*."/>
      <param name="optical_duplicate_pixel_distance" value="100"/>
      <param name="duplicate_scoring_strategy" value="SUM_OF_BASE_QUALITIES"/>
      <param name="validation_stringency" value="LENIENT"/>
      <output name="outFile" file="picard_MarkDuplicates_test1.bam" ftype="bam" lines_diff="2"/>
    </test>
  </tests>
  
  <stdio>
    <exit_code range="1:"  level="fatal"/>
  </stdio>
  
  <help>

**Purpose**

Examines aligned records in the supplied SAM or BAM dataset to locate duplicate molecules. All records are then written to the output file with the duplicate records flagged.

@dataset_collections@

@description@

  COMMENT=String  
  CO=String                     Comment(s) to include in the output file's header.  This option may be specified 0 or 
                                more times. 

  REMOVE_DUPLICATES=Boolean     If true do not write duplicates to the output file instead of writing them with 
                                appropriate flags set.  Default value: false.  
  
  READ_NAME_REGEX=String        Regular expression that can be used to parse read names in the incoming SAM file. Read 
                                names are parsed to extract three variables: tile/region, x coordinate and y coordinate. 
                                These values are used to estimate the rate of optical duplication in order to give a more 
                                accurate estimated library size. Set this option to null to disable optical duplicate 
                                detection. The regular expression should contain three capture groups for the three 
                                variables, in order. It must match the entire read name. Note that if the default regex 
                                is specified, a regex match is not actually done, but instead the read name  is split on 
                                colon character. For 5 element names, the 3rd, 4th and 5th elements are assumed to be 
                                tile, x and y values. For 7 element names (CASAVA 1.8), the 5th, 6th, and 7th elements 
                                are assumed to be tile, x and y values.  Default value: 
                                [a-zA-Z0-9]+:[0-9]:([0-9]+):([0-9]+):([0-9]+).*.
                                
  DUPLICATE_SCORING_STRATEGY=ScoringStrategy
  DS=ScoringStrategy            The scoring strategy for choosing the non-duplicate among candidates.  Default value: 
                                SUM_OF_BASE_QUALITIES. Possible values: {SUM_OF_BASE_QUALITIES, TOTAL_MAPPED_REFERENCE_LENGTH} 
  
  OPTICAL_DUPLICATE_PIXEL_DISTANCE=Integer
                                The maximum offset between two duplicte clusters in order to consider them optical 
                                duplicates. This should usually be set to some fairly small number (e.g. 5-10 pixels) 
                                unless using later versions of the Illumina pipeline that multiply pixel values by 10, in 
                                which case 50-100 is more normal.  Default value: 100. 

@more_info@

  </help>
</tool>