The current GATK version is 3.7-0
Examples: Monday, today, last week, Mar 26, 3/26/04

Howdy, Stranger!

It looks like you're new here. If you want to get involved, click one of these buttons!

Did you remember to?


1. Search using the upper-right search box, e.g. using the error message.
2. Try the latest version of tools.
3. Include tool and Java versions.
4. Tell us whether you are following GATK Best Practices.
5. Include relevant details, e.g. platform, DNA- or RNA-Seq, WES (+capture kit) or WGS (PCR-free or PCR+), paired- or single-end, read length, expected average coverage, somatic data, etc.
6. For tool errors, include the error stacktrace as well as the exact command.
7. For format issues, include the result of running ValidateSamFile for BAMs or ValidateVariants for VCFs.
8. For weird results, include an illustrative example, e.g. attach IGV screenshots according to Article#5484.
9. For a seeming variant that is uncalled, include results of following Article#1235.

Did we ask for a bug report?


Then follow instructions in Article#1894.

Formatting tip!


Surround blocks of code, error messages and BAM/VCF snippets--especially content with hashes (#)--with lines with three backticks ( ``` ) each to make a code block.
Powered by Vanilla. Made with Bootstrap.
Picard 2.9.0 is now available. Download and read release notes here.
GATK 3.7 is here! Be sure to read the Version Highlights and optionally the full Release Notes.

Best Practice V4

mikemike Member Posts: 103
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
Tagged:

Answers

  • Geraldine_VdAuweraGeraldine_VdAuwera Administrator, Dev Posts: 11,163 admin

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

    Geraldine Van der Auwera, PhD

  • mikemike Member Posts: 103

    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 Administrator, Dev Posts: 11,163 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

Sign In or Register to comment.