Tagged with #depthperallelebysample
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Created 2014-10-17 19:19:39 | Updated 2014-10-29 15:40:36 | Tags: coveragebysample depthofcoverage depthperallelebysample ad dp
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This document covers the use of various tools and metrics associated with depth of coverage.

Note that at the moment this document is incomplete; in future we will add more details pertaining to the DepthOfCoverage and DiagnoseTargets analysis tools. For now, this just gives you some keys to understanding the coverage annotations given in the AD and DP fields of the VCF files output by the variant calling tools.

Coverage annotations: DP and AD

The variant callers generate two main coverage annotation metrics: the allele depth per sample (AD) and overall depth of coverage (DP, available both per sample and across all samples, with important differences), controlled by the following annotator modules:

  • DepthPerAlleleBySample (AD): outputs the depth of coverage of each allele per sample.
  • Coverage (DP): outputs the filtered depth of coverage for each sample and the unfiltered depth of coverage across all samples.

At the sample level, these annotations are highly complementary metrics that provide two important ways of thinking about the depth of the data available for a given sample at a given site. The key difference is that the AD metric is based on unfiltered read counts while the sample-level DP is based on filtered read counts (see tool documentation for a list of read filters that are applied by default for each tool). As a result, they should be interpreted differently.

The sample-level DP is in some sense reflective of the power I have to determine the genotype of the sample at this site, while the AD tells me how many times I saw each of the REF and ALT alleles in the reads, free of any bias potentially introduced by filtering the reads. If, for example, I believe there really is a an A/T polymorphism at a site, then I would like to know the counts of A and T bases in this sample, even for reads with poor mapping quality that would normally be excluded from the statistical calculations going into GQ and QUAL.

Note that because the AD includes reads and bases that were filtered by the caller (and in case of indels, is based on a statistical computation), it should not be used to make assumptions about the genotype that it is associated with. Ultimately, the phred-scaled genotype likelihoods (PLs) are what determines the genotype calls.

TO BE CONTINUED... meanwhile, check out the DepthOfCoverage and DiagnoseTargets tool docs.

Created 2012-07-23 23:55:29 | Updated 2012-07-23 23:55:29 | Tags: depthperallelebysample gatkdocs
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A new tool has been released!

Check out the documentation at DepthPerAlleleBySample.

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Created 2012-11-29 17:51:33 | Updated | Tags: unifiedgenotyper depthperallelebysample
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I found some strange entries for indels in my VCF file created by the Unified Genotyper. For example:

4 184513470 . TC T 4009 PASS AC=4;AF=0.250;AN=16;BaseQRankSum=1.972;DP=1315;DS;FS=3.466;HaplotypeScore=537.6937;MLEAC=4;MLEAF=0.250;MQ=52.55;MQ0=0;MQRankSum=-10.581;QD=4.55;ReadPosRankSum=-10.128;SB=-3.500e+01;set=variant2 GT:AD:DP:GQ:PL 0/1:230,0:239:99:282,0,5011 0/0:92,0:95:99:0,133,2435

The first sample has genotype 0/1 with a good GQ value. However, according the allele depth field, there is no read supporting the deletion. When I look at the reads using the IGV, I find some reads supporting the deletion for the first sample (and even some for the second one).

Moreover, when I looked at the AD values for SNPs, I noticed the the sum of all AD values is much less than the coverage shown in the IGV. I filtered duplicated reads in the IGV.

Can someone please give an explanation? This link http://www.broadinstitute.org/gatk/gatkdocs/org_broadinstitute_sting_gatk_walkers_annotator_DepthPerAlleleBySample.html explains the difference between AD and DP, but does not help in my case.

Best greetings, Hans-Ulrich