# Tagged with #resource 1 documentation article | 0 announcements | 3 forum discussions

Created 2012-07-31 17:50:15 | Updated 2016-01-27 05:56:51 | Tags: known knownsites intermediate dbsnp resource

### 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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Created 2016-05-20 09:35:24 | Updated | Tags: variantrecalibrator vqsr resource training

Dear GATK team,

I am working with maize aDNA and would like to find SNPs called in aDNA samples that are at least as good as those in HapMap.

Am right to assume that variant recalibration is the correct tool for the job? My problem is that I can't find details about format of "resources" used for training. (I would like to see your hapmap.vcf but i can't log in to your ftp; it tells me that there can be only 25 users there).

Here is my question: Which components are important in resource vcf file; positions? variants? annotations? are SNP calls for each individual important? In other words, is the purpose of training "resource" to 1) find overlapping sites in my vcf and use annotations that are in my vcf or 2) is it the training resource annotations that are being used? If the former is true, would it be possible to use bed files instead? If the latter is true, do I need individual calls? HapMap for my organism has > 1000 individuals and is very heavy; if possible I would like to avoid downloading it all.

Best wishes, Rafal

Created 2016-01-25 00:47:12 | Updated | Tags: vqsr resource variant-recalibration

Hi, I am following through the best practice pipeline and I am confused of which files I should use as the resource to run VQSR.

I have downloaded 4 files and I just want to make sure which file is which database.

1000G_omni2.5.b37.vcf.gz = omni,vcf 1000G_phase1.snps.high_confidence.b37.vcf.gz = 1000G.vcf dbsnp_138.b37.vcf.gz = snp.vcf hapmap_3.3.b37.vcf.gz = hapmap.vcf

I am planning to unzipped them and run VQSR. Did I download the correct files? If not, could you tell me which files I need to use? Thank you.

Shane

Created 2012-12-10 23:46:19 | Updated 2012-12-11 02:31:16 | Tags: variantannotator resource

I would like to have certain annotations applied only if the variants in the resource and the target have the same genomic change. Ex: In Cosmic the following variants are present.

12      25398284        .       C       G       .       PASS    Genename=KRAS;MutationAA=p.G12A;MutationCDS=c.35G>C
12      25398284        .       C       A       .       PASS    Genename=KRAS;MutationAA=p.G12V;MutationCDS=c.35G>T
12      25398284        .       C       T       .       PASS    Genename=KRAS;MutationAA=p.G12D;MutationCDS=c.35G>A

However, in my VCF file I get the G12A annotation for all variants at this site even if the actual change is G12V or G12D.

Is this possible?