Tagged with #known
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Comments (22)

1. Notes on known sites

Why are they important?

Each tool uses known sites differently, but what is common to all is that they use them to help distinguish true variants from false positives, which is very important to how these tools work. If you don't provide known sites, the statistical analysis of the data will be skewed, which can dramatically affect the sensitivity and reliability of the results.

In the variant calling pipeline, the only tools that do not strictly require known sites are UnifiedGenotyper and HaplotypeCaller.

Human genomes

If you're working on human genomes, you're in luck. We provide sets of known sites in the human genome as part of our resource bundle, and we can give you specific Best Practices recommendations on which sets to use for each tool in the variant calling pipeline. See the next section for details.

Non-human genomes

If you're working on genomes of other organisms, things may be a little harder -- but don't panic, we'll try to help as much as we can. We've started a community discussion in the forum on What are the standard resources for non-human genomes? in which we hope people with non-human genomics experience will share their knowledge.

And if it turns out that there is as yet no suitable set of known sites for your organisms, here's how to make your own for the purposes of BaseRecalibration: First, do an initial round of SNP calling on your original, unrecalibrated data. Then take the SNPs that you have the highest confidence in and use that set as the database of known SNPs by feeding it as a VCF file to the base quality score recalibrator. Finally, do a real round of SNP calling with the recalibrated data. These steps could be repeated several times until convergence. Good luck!

Some experimentation will be required to figure out the best way to find the highest confidence SNPs for use here. Perhaps one could call variants with several different calling algorithms and take the set intersection. Or perhaps one could do a very strict round of filtering and take only those variants which pass the test.

2. Recommended sets of known sites per tool

Summary table

Tool dbSNP 129 - - dbSNP >132 - - Mills indels - - 1KG indels - - HapMap - - Omni
RealignerTargetCreator X X
IndelRealigner X X
BaseRecalibrator X X X
(UnifiedGenotyper/ HaplotypeCaller) X
VariantRecalibrator X X X X
VariantEval X

RealignerTargetCreator and IndelRealigner

These tools require known indels passed with the -known argument to function properly. We use both the following files:

  • Mills_and_1000G_gold_standard.indels.b37.sites.vcf
  • 1000G_phase1.indels.b37.vcf (currently from the 1000 Genomes Phase I indel calls)

BaseRecalibrator

This tool requires known SNPs and indels passed with the -knownSites argument to function properly. We use all the following files:

  • The most recent dbSNP release (build ID > 132)
  • Mills_and_1000G_gold_standard.indels.b37.sites.vcf
  • 1000G_phase1.indels.b37.vcf (currently from the 1000 Genomes Phase I indel calls)

UnifiedGenotyper / HaplotypeCaller

These tools do NOT require known sites, but if SNPs are provided with the -dbsnp argument they will use them for variant annotation. We use this file:

  • The most recent dbSNP release (build ID > 132)

VariantRecalibrator

For VariantRecalibrator, please see the FAQ article on VQSR training sets and arguments.

VariantEval

This tool requires known SNPs passed with the -dbsnp argument to function properly. We use the following file:

  • A version of dbSNP subsetted to only sites discovered in or before dbSNP BuildID 129, which excludes the impact of the 1000 Genomes project and is useful for evaluation of dbSNP rate and Ti/Tv values at novel sites.
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Comments (5)

Hi, For both IndelRealigner/RealignerTargetCreator, there is an option for known indel sites as below:

-known /path/to/indels.vcf

However, from the bundle files collection such as from hg19, there are several vcf files:

1000G_indels_for_realignment.hg19.vcf
1000G_omni2.5.hg19.sites.vcf
1000G_omni2.5.hg19.vcf
dbsnp_132.hg19.excluding_sites_after_129.vcf
dbsnp_132.hg19.vcf
hapmap_3.3.hg19.sites.vcf
hapmap_3.3.hg19.vcf
indels_mills_devine.hg19.sites.vcf
indels_mills_devine.hg19.vcf
NA12878.HiSeq.WGS.bwa.cleaned.raw.subset.hg19.sites.vcf
NA12878.HiSeq.WGS.bwa.cleaned.raw.subset.hg19.vcf

amongst them, just based on the names, 1000G_indels_for_realignment.hg19.vcf and indels_mills_devine.hg19.sites.vcf look like the files supposed to use for IndelRealigner/RealignerTargetCreator, Could you clarify the exact files for this purpose?

Since for old version, I have used 1000G_phase1.indels.hg19.vcf and Mills_and_1000G_gold_standard.indels.hg19.sites.vcf. and I compared the new and old files, quite different now.

Thanks

Mike

Comments (23)

Hi all!

I'm currently working on high-coverage non-human data (mammals).

After mapping via BWA, soritng and merging, my pipeline goes like this:

  1. Remove duplicates via MarkDuplicates.
  2. RealignerTargetCreator
  3. IndelRealigner using the --consensusDeterminationModel USE_SW flag
  4. Fix Mates

I currently want to begin the recalibration step before doing the actual variant calls via UnifiedGenotyper.

Since I'm working on non-human data, there is no thorough database I can trust as an input vcf file for the recalibration step.

What is your recommendation for this for non-human data?

Thank you very much!

Sagi

Comments (26)

We're trying to put together some recommendations for folks who want to use GATK tools on non-human genomes. But we really don't have much experience with non-human genomes, so we're hoping that those of you in the GATK community who do will chime in and help your fellow scientists find the answers for a few common problems.

The most common problem seems to be finding sets of known sites for organisms like Drosophila, dogs, and various plants. If you know of such resources, please share your knowledge by commenting in this thread. You could earn upvotes and warm fuzzy feelings!