Best Practice V4

mikemike Posts: 103Member
edited November 2012 in Ask the GATK team

Hi:

for the best practice V4, for the step: 2. Raw reads to analysis-ready reads at phase I, I only have lane-level sample data (each sample in one lane, no sample in multi-lanes), so I only did the Fast: lane-level realignment (at known sites only) and lane-level recalibration, which is

for each lane.bam
    dedup.bam <- MarkDuplicate(lane.bam)
    realigned.bam <- realign(dedup.bam) [at only known sites, if possible, otherwise skip]
    recal.bam <- recal(realigned.bam)

Since I do not have multi-lane samples, I do not have to run Fast + per-sample processing, Better: per-sample realignment with known indels and recalibration, or Best: multi-sample realignment with known sites and recalibration, right? It seems that all of these schemes, Better, Best etc, are only for situation when some samples run at multiple lanes, is my understanding correct?

at the paragraph for Fast + per-sample processing, it mentioned: cross-lane realignment, not sure what it means exactly. if every sample of mine are in a single lane, it does not need, right?

Thanks

Mike

Post edited by Geraldine_VdAuwera on
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Answers

  • Geraldine_VdAuweraGeraldine_VdAuwera Posts: 6,973Administrator, GATK Developer admin

    That's right, if each sample is in a single lane you can use a simplified workflow.

    Geraldine Van der Auwera, PhD

  • mikemike Posts: 103Member

    Hi, Geraldine:

    Thanks a lot for the comments. As I mentioned in my original post, could you explain a bit what is cross-lane realignment, not sure what it means exactly and why have to do that.

    Thanks again,

    Mike

  • Geraldine_VdAuweraGeraldine_VdAuwera Posts: 6,973Administrator, GATK Developer admin

    Cross-lane realignment just means realignment of data from all lanes belonging to a sample. This helps ensure that indels will be realigned the same way in all the reads for the sample. It's not really needed If you have a db of known indels, but if you don't have one it really helps.

    Geraldine Van der Auwera, PhD

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