GATK

Tagged with #variant recalibration
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Sorry, there are no publicly available documents of this type with the tag #variant recalibration. Try one of the other types.

Haplotype Score Region

Hi Everyone,

I had a few questions about the haplotype score.

In the technical documentation it states that "Higher scores are indicative of regions with bad alignments, often leading to artifactual SNP and indel calls. Note that the Haplotype Score is only calculated for sites with read coverage."

How is the haplotype group for each variant site determined? e.g. Does it take the closest two variants to the query site and then treat the query variant + closest two variants as the haplotype group?

Also, in the case of multiallelic SNPs (>2 SNPs), haplotype score is inappropriate since it only looks at whether a site can be explained by the segregation of two and only two haplotypes, correct? So multiallelic snps will be assigned poor haplotype scores OR will these sites not be annotated at all? If we have a case where there is a truly biallelic SNP and a couple of samples have some reads that are erroneously calling a third allele, this variant site will be assigned a poor haplotype score overall, correct?

Thanks,

MC

Variant Recalibration - Number of Whole Exome Samples Needed and Where?

Hello,

I've just made a long needed update to the most recent version of GATK. I had been toying with the variant quality score recalibrator before but now that I have a great deal more exomes at my disposal I'd like to fully implement it in a meaningful way.

The phrase I'm confused about is "In our testing we've found that in order to achieve the best exome results one needs to use an exome callset with at least 30 samples." How exactly do I arrange these 30+ exomes?

Is there any difference or reason to choose one of the following two workflows over the other?

  1. Input 30+ exomes in the "-I" argument of either the UnifiedGenotyper or HaplotypeCaller and then with my multi-sample VCF perform the variant recalibration procedure and then split the individual call sets out of the multi-sample vcf with SelectVariants?

  2. Take 30+ individual vcf files, merge them together, and then perform variant recalibration on the merged vcf and then split the individual call sets out of the multi-sample vcf with SelectVariants?

  3. Or some third option I'm missing

Any help is appreciated.

Thanks

VariantRecalibrator: ERROR stack trace

Hi, I'm encountering this error running VariantRecalibrator with data from 3 samples (I'm testing): Maybe is the problem due to small sample size?

##### ERROR ------------------------------------------------------------------------------------------
##### ERROR stack trace 
java.lang.NullPointerException
        at org.broadinstitute.sting.gatk.walkers.variantrecalibration.VariantDataManager.selectWorstVariants(VariantDataManager.java:179)
        at org.broadinstitute.sting.gatk.walkers.variantrecalibration.VariantRecalibrator.onTraversalDone(VariantRecalibrator.java:306)
        at org.broadinstitute.sting.gatk.walkers.variantrecalibration.VariantRecalibrator.onTraversalDone(VariantRecalibrator.java:107)
        at org.broadinstitute.sting.gatk.executive.Accumulator$StandardAccumulator.finishTraversal(Accumulator.java:129)
        at org.broadinstitute.sting.gatk.executive.LinearMicroScheduler.execute(LinearMicroScheduler.java:97)
        at org.broadinstitute.sting.gatk.GenomeAnalysisEngine.execute(GenomeAnalysisEngine.java:281)
        at org.broadinstitute.sting.gatk.CommandLineExecutable.execute(CommandLineExecutable.java:113)
        at org.broadinstitute.sting.commandline.CommandLineProgram.start(CommandLineProgram.java:237)
        at org.broadinstitute.sting.commandline.CommandLineProgram.start(CommandLineProgram.java:147)
        at org.broadinstitute.sting.gatk.CommandLineGATK.main(CommandLineGATK.java:94)
##### ERROR ------------------------------------------------------------------------------------------
##### ERROR A GATK RUNTIME ERROR has occurred (version 2.2-16-g9f648cb):
##### ERROR
##### ERROR Please visit the wiki to see if this is a known problem
##### ERROR If not, please post the error, with stack trace, to the GATK forum
##### ERROR Visit our website and forum for extensive documentation and answers to 
##### ERROR commonly asked questions http://www.broadinstitute.org/gatk
##### ERROR
##### ERROR MESSAGE: Code exception (see stack trace for error itself)
##### ERROR ------------------------------------------------------------------------------------------

Thanks

how can vqsr applied on small data set?

We have data from target sequencing genes (only targeted two genes). We analyzed the data by GATK pipeline. Since the data set is too small, we tried hard filtration on both SNP and indels. At the same time, we sequenced the same sample by whole exome sequencing and filter SNP by VQSR. The quality of VQSR results is much better than hard filtration results. For economic reason, we need to develop analysis pipeline for target sequencing, is it ok to incorporate the target sequencing data into an exome sequencing data (merge the VCF files), do VQSR? I just worried the true sites in target sequencing data have different features compared to true sites in whole exome sequencing data.