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BamUtil: recab (view source)

Revision as of 01:10, 6 March 2016

1,246 bytes added ,  01:10, 6 March 2016
→‎Parameters
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<pre>
 
Required General Parameters :
 
Required General Parameters :
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--in <infile>  : input BAM file name
+
        --in <infile>  : input BAM file name
−
--out <outfile> : output recalibration file name
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        --out <outfile> : output recalibration file name
−
Optional General Parameters :  
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Optional General Parameters :
−
--log <logfile> : log and summary statistics (default: [outfile].log)
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        --log <logfile> : log and summary statistics (default: [outfile].log)
−
--verbose      : Turn on verbose mode
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        --verbose      : Turn on verbose mode
−
--noeof        : do not expect an EOF block on a bam file.
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        --noeof        : do not expect an EOF block on a bam file.
−
--params        : print the parameter settings
+
        --params        : print the parameter settings
    
Recab Specific Required Parameters
 
Recab Specific Required Parameters
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--refFile <reference file>    : reference file name
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        --refFile <reference file>    : reference file name
−
Recab Specific Optional Parameters :  
+
Recab Specific Optional Parameters :
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--dbsnp <known variance file> : dbsnp file of positions
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        --dbsnp <known variance file> : dbsnp file of positions
−
--minBaseQual <minBaseQual>  : minimum base quality of bases to recalibrate (default: 5)
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        --minBaseQual <minBaseQual>  : minimum base quality of bases to recalibrate (default: 5)
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--maxBaseQual <maxBaseQual>  : maximum recalibrated base quality (default: 50)
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        --maxBaseQual <maxBaseQual>  : maximum recalibrated base quality (default: 50)
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--blended <weight>            : blended model weight
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                                        qualities over this value will be set to this value.
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--fitModel                    : check if the logistic regression model fits the data
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                                        This setting is applied after binning (if applicable).
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                                overriden by fast, but automatically applied by useLogReg
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        --blended <weight>            : blended model weight
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--fast                        : use a compact representation that only allows:
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        --fitModel                    : check if the logistic regression model fits the data
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                                  * at most 256 Read Groups
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                                        overriden by fast, but automatically applied by useLogReg
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                                  * maximum quality 63
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        --fast                        : use a compact representation that only allows:
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                                  * at most 127 cycles
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                                          * at most 256 Read Groups
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                                overrides fitModel, but is overridden by useLogReg
+
                                          * maximum quality 63
−
                                uses up to about 2.25G more memory than running without --fast.
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                                          * at most 127 cycles
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--keepPrevDbsnp              : do not exclude entries where the previous base is in dbsnp when
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                                        overrides fitModel, but is overridden by useLogReg
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                                building the recalibration table
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                                        uses up to about 2.25G more memory than running without --fast.
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                                By default they are excluded from the table.
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        --keepPrevDbsnp              : do not exclude entries where the previous base is in dbsnp when
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--keepPrevNonAdjacent        : do not exclude entries where the previous base is not adjacent
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                                        building the recalibration table
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                                (not a Cigar M/X/=) when building the recalibration table
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                                        By default they are excluded from the table.
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                                By default they are excluded from the table (except the first cycle).
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        --keepPrevNonAdjacent        : do not exclude entries where the previous base is not adjacent
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--useLogReg                  : use logistic regression calculated quality for the new quality
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                                        (not a Cigar M/X/=) when building the recalibration table
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                                automatically applies fitModel and overrides fast.
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                                        By default they are excluded from the table (except the first cycle).
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--qualField <quality tag>    : tag to get the starting base quality
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        --useLogReg                  : use logistic regression calculated quality for the new quality
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                                (default is to get it from the Quality field)
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                                        automatically applies fitModel and overrides fast.
−
--storeQualTag <quality tag>  : tag to store the previous quality into
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        --qualField <quality tag>    : tag to get the starting base quality
−
--buildExcludeFlags <flag>    : exclude reads with any of these flags set when building the
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                                        (default is to get it from the Quality field)
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                                recalibration table
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        --storeQualTag <quality tag>  : tag to store the previous quality into
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--applyExcludeFlags <flag>    : do not apply the recalibration table to any reads with any of these flags set
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        --buildExcludeFlags <flag>    : exclude reads with any of these flags set when building the
 +
                                        recalibration table.  Default is 0xF04
 +
        --applyExcludeFlags <flag>    : do not apply the recalibration table to any reads with any of these flags set
 +
        Quality Binning Parameters (optional):
 +
          Bin qualities by phred score, into the ranges specified by binQualS or binQualF (both cannot be used)
 +
          Ranges are specified by comma separated minimum phred score for the bin, example: 1,17,20,30,40,50,70
 +
          The first bin always starts at 0, so does not need to be specified.
 +
          By default, the bin value is the low end of the range.
 +
                --binQualS  : Bin the Qualities as specified (phred): minQualOfBin2, minQualofBin3...
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                --binQualF  : Bin the Qualities based on the specified file
 +
                --binMid    : Use the mid point of the quality bin range for the quality value of the bin.
 +
                --binHigh    : Use the high end of the quality bin range for the quality value of the bin.
 +
 
 
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Retrieved from "http://genome.sph.umich.edu/wiki/Special:MobileDiff/14127"

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