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is it necessary to run GATK tools for .bams with GATK-related @PG entries

Hi GATK Team,

I'm analyzing WGS data from the TCGA. Looking at the header of the .bam files, I see the following @PG entries:

@PG ID:GATK TableRecalibration VN:1.6-2-gc2b74ec CL:default_platform=illumina force_platform=null window_size_nqs=5 solid_recal_mode=SET_Q_ZERO solid_nocall_strategy=THROW_EXCEPTION context_size=8 homopolymer_nback=7 recal_file=D1DVJACXX-4.csv preserve_qscores_less_than=5 smoothing=1 max_quality_score=50 doNotWriteOriginalQuals=false no_pg_tag=false fail_with_no_eof_marker=false skipUQUpdate=false Covariates=[ReadGroupCovariate, QualityScoreCovariate, CycleCovariate, DinucCovariate]
@PG ID:GATK TableRecalibration.1 VN:1.6-2-gc2b74ec CL:default_platform=illumina force_platform=null window_size_nqs=5 solid_recal_mode=SET_Q_ZERO solid_nocall_strategy=THROW_EXCEPTION context_size=8 homopolymer_nback=7 recal_file=C1940ACXX-1.csv preserve_qscores_less_than=5 smoothing=1 max_quality_score=50 doNotWriteOriginalQuals=false no_pg_tag=false fail_with_no_eof_marker=false skipUQUpdate=false Covariates=[ReadGroupCovariate, QualityScoreCovariate, CycleCovariate, DinucCovariate]
@PG ID:GATK TableRecalibration.2 VN:1.6-2-gc2b74ec CL:default_platform=illumina force_platform=null window_size_nqs=5 solid_recal_mode=SET_Q_ZERO solid_nocall_strategy=THROW_EXCEPTION context_size=8 homopolymer_nback=7 recal_file=D1DFCACXX-1.csv preserve_qscores_less_than=5 smoothing=1 max_quality_score=50 doNotWriteOriginalQuals=false no_pg_tag=false fail_with_no_eof_marker=false skipUQUpdate=false Covariates=[ReadGroupCovariate, QualityScoreCovariate, CycleCovariate, DinucCovariate]
@PG ID:GATK TableRecalibration.3 VN:1.6-2-gc2b74ec CL:default_platform=illumina force_platform=null window_size_nqs=5 solid_recal_mode=SET_Q_ZERO solid_nocall_strategy=THROW_EXCEPTION context_size=8 homopolymer_nback=7 recal_file=D1D4DACXX-3.csv preserve_qscores_less_than=5 smoothing=1 max_quality_score=50 doNotWriteOriginalQuals=false no_pg_tag=false fail_with_no_eof_marker=false skipUQUpdate=false Covariates=[ReadGroupCovariate, QualityScoreCovariate, CycleCovariate, DinucCovariate]
@PG ID:bwa PN:bwa VN:0.5.9-r16
@PG ID:GATK IndelRealigner VN:1.3-8-gb0e6afe CL:knownAlleles=[] LODThresholdForCleaning=5.0 consensusDeterminationModel=USE_READS entropyThreshold=0.15 maxReadsInMemory=150000 maxIsizeForMovement=3000 maxPositionalMoveAllowed=200 maxConsensuses=30 maxReadsForConsensuses=120 maxReadsForRealignment=20000 noOriginalAlignmentTags=false nWayOut=null generate_nWayOut_md5s=false check_early=false noPGTag=false keepPGTags=false indelsFileForDebugging=null statisticsFileForDebugging=null SNPsFileForDebugging=null

, which seem to show the IndelRealigner and BaseRecalibrator have already been run on the .bam. Is it safe then to skip re-running these processing steps and to use this .bam directly into downstream tools like MuTect? I noticed also that there's not a @PG for MarkDuplicates. Is it safe to assume this step was done?

Thanks a lot for your time,
Steve

Best Answers

Answers

  • newGATKusernewGATKuser CaseMember

    Hi @pdexheimer,

    Thanks very much for your helpful reply. I just have a quick follow-up question. Is it critical that I RevertSam the "raw" .bam? I had not known of this tool before you mentioned it, but I now understand it serves to wipe the slate clean before I do pre-processing steps. Would the results be different if I run MarkDuplicates, IndelRealigner, BaseRecalibrator directly on the .bam without RevertSam at the beginning? Sorry if this is a naive question. I'm pretty new to GATK.

    Sincerely,
    Steve

  • newGATKusernewGATKuser CaseMember

    Thanks @pdexheimer. I really appreciate the information. To be safe, I'll add RevertSam to the beginning of my pipeline then.

  • newGATKusernewGATKuser CaseMember

    Hi again @pdexheimer,

    Sorry for the continuous questions. I recently came across the PPT presentation "Somatic Variant Discovery" in the google drive:
    https://drive.google.com/a/case.edu/folderview?id=0BwTg3aXzGxEDVk5RcEF3WW1SQWM&usp=sharing#
    It seems to suggest doing a 2nd IndelRealigner step (using the tumor/normal pair) after per-sample pre-processing is finished. I guess I'm confused about whether stacking these steps is OK. Like you mentioned, the base qualities are changed after BQSR and IR, and BQSR and IR both depend on base qualities. It seems to me there might be a "missing" revert BQSR step in that workflow, before doing the 2nd pair-wise IR and BQSR?

    Thanks for your patient help,
    Steve

  • pdexheimerpdexheimer Member ✭✭✭✭

    I don't remember that presentation off the top of my head (and don't have time to go digging right now, sorry), but a couple of thoughts:

    1) IR modifies mapping qualities, not base qualities. The feedback loop you're envisioning doesn't quite exist
    2) Pre-HaplotypeCaller, IR was a much more critical step - much of its functionality is wrapped up in the HC step now. I seem to remember an "if you have CPU hours to burn" step in one of the Best Practices that was to run IR over your entire cohort, to normalize the mapping of reads around indels. So maybe stacking IR runs won't hurt as much as I was thinking previously

  • newGATKusernewGATKuser CaseMember

    Hi @pdexheimer, thanks for your time. I appreciate it. I see, I think I misunderstood the first time but I get it now.

  • newGATKusernewGATKuser CaseMember

    Hi @Geraldine_VdAuwera ,

    Thank you for the information. I look forward to using MuTect2!

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