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.

On the difference between MarkDuplicates and picard_MarkDuplicatesWithMateCigar

From Samtools Announce MailingList:

This tool can replace MarkDuplicates if the input SAM/BAM has Mate CIGAR (MC) optional tags pre-computed (see the tools RevertOriginalBaseQualitiesAndAddMateCigar and FixMateInformation). This allows the new tool to perform a streaming duplicate marking routine (i.e. a single-pass). This tool cannot be used with alignments that have large gaps or reference skips, which happens frequently in RNA-seq data.

Dataset collections - processing large numbers of datasets at once

This will be added shortly

Inputs, outputs, and parameters

Either a SAM file or a BAM file must be supplied. Galaxy automatically coordinate-sorts all uploaded BAM files.

From Picard documentation( http://broadinstitute.github.io/picard/):

MINIMUM_DISTANCE=Integer      The minimum distance to buffer records to account for clipping on the 5' end of the
                              records.Set this number to -1 to use twice the first read's read length (or 100,
                              whichever is smaller).  Default value: -1. This option can be set to 'null' to clear the
                              default value.

SKIP_PAIRS_WITH_NO_MATE_CIGAR=Boolean
                              Skip record pairs with no mate cigar and include them in the output.  Default value:
                              true. This option can be set to 'null' to clear the default value. Possible values:
                              {true, false}

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:
                              TOTAL_MAPPED_REFERENCE_LENGTH. 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.

Additional information

Additional information about Picard tools is available from Picard web site at http://broadinstitute.github.io/picard/ .