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Status for dealing with paired-end reads

Hi all, new here and its my first post, so sorry if its not relevant enough.

I have been thinking about the same problem that occurred here twice already, and i cannot seem to come to a conclusion on what do to. The problem is how to interpret paired-end reads overlapping regions. Some "commercial" software does the merging prior to any further analysis and then reports a variants coverage in relation to the merged reads. This makes sense for me, since i get a single-molecule coverage. Here in GATK as i've read in posts:
http://gatkforums.broadinstitute.org/gatk/discussion/5559/haplotype-caller-and-overlapping-paired-end-reads
http://gatkforums.broadinstitute.org/gatk/discussion/1745/does-unifiedgenotyper-count-overlapping-paired-end-reads-as-two-separate-reads
It seems that the information from the overlap is modelled (to account for varying base qualities and possible differences) but the reported coverage seems inflated. When i run the same sample through the "commercial" counterpart and GATK i get higher coverages on variants consistently.

The real problem i have with this is, that when dealing with standards and accreditations one wants to claim that variants are given for regions with coverage above 30X. But for the HaplotypeCaller, what does that mean? Should it be 60X (which would be too strict in many cases and undercut a lot of data from WES projects).

To boil it down - is there a way to bring the coverage to a value reflecting the molecules sequenced (so consider the overlap phred scores but also change the coverage to 1) or should there be some step of read-merging prior?

Sorry for a long and convoluted post, hope to hear from you!
Piotr

Issue · Github
by Sheila

Issue Number
1109
State
closed
Last Updated
Assignee
Array
Milestone
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Closed By
vdauwera

Best Answers

Answers

  • starnasstarnas AarhusMember

    Hi Jean and Geraldine, thank you for your answers!

    Ran DepthOfCoverage yesterday, seems to do the job in returning the per-molecule coverage (though it is slow for a whole exome).
    Weirdly though when compared to .vcf DP field (same sample, generated from same bam file) i get both higher and lower values.
    This may be due to what you've mentioned - adapted coverage from Piccard. Since i am not (yet) familiar what adapted means, would you say that DepthOfCoverage is the least distorted method of reporting the sequenced depth?

    Again, I appreciate your time devoted to my considerations.

    Best
    Piotr

  • starnasstarnas AarhusMember

    Hi all

    After trying the tools you've suggested i have my answer how to get the coverage in many ways, so i guess this discussion is locked.
    However, i have to say thank you!
    So thank You!

    Best
    Piotr

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