Tagged with #genotype
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I have an inbred mouse strain that I am sequencing and there should be little to NO heterozygosity. Yet with the default settings of UGT -heterozygosity (which is 0.001) many homs are being called as hets. When 230/250 reads are alternate and 20/250 are reference, it calls a het, even though it should be homozygous alternate.

What do you recommendations for this setting for inbred animals?

thanks, GATK is great!

Vivek

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Hi. I have converted the tsv file from Complete genomics(CGA tool) to vcf format. but, when I run programs, it says some error in my vcf format. I carefully examined the vcf file and found, in some SNVs the GT is 1|.(dot). Is it a valid vcf file or is there any problem in vcf file? The program showed the error in those lines in which GT is 1|.(dot) i.e half genotype information. The line looks like this:

1   55164   .   C   A   .   .   NS=1;AN=1;AC=1;CGA_XR=dbsnp.103|rs3091274;CGA_RPT=L2|L2|49.7;CGA_SDO=2  GT:PS:FT:HQ:EHQ:CGA_CEHQ:GL:CGA_CEGL:DP:AD:CGA_RDP  1/.:.:VQLOW:30,.:30,.:8,.:-30,0,0:-8,0,0:18:18,.:0

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While running VariantEval, I'm trying to stratify by a JexlExpression by setting using

-ST Sample -ST JexlExpression -select "GQ>20"

This fails with a "variable does not exist" error despite the GQ existing in all genotypes in the vcf. Looking at the code it seems that the pathway that loads the JexlExpression in the VariantEval class specifically does not provide the genotype as context (only the VariantContext) and thus, the context for the Jexl does not include GT and the error is produced.

My question is: Is this a feature or a bug? It seems possible to add the genotype (when the VC only has one, or loop over the genotypes and either OR or AND the results (perhaps another input similar to -isr?), but perhaps I'm missing something subtle?

Would you like this behavior or are you happy with the current operation of jexlExpression?

Cheers!

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Hi,

I am observing the following scenario at one particular SNP (C/G) using two different enrichment technologies: (I am using IGV syntax: ALLELE|number of reads w/ allele|%of total reads|+strand reads|- strand reads) - technology1:
C: 15 47% 15+,0- G: 17 53% 17+,0- - technology2:
C: 17 37% 13+,4- G: 29 63% 26+,3- As you can see both technologies have good coverage of the SNP and also good representation of each allele. SNP(C/G) does not get called in technology1.

My questions are: 1- Does the GATK algorithm have some sort of constraint on the proportion of reads coming from only one strand (as with technology1) in order to try to predict or discard duplicates? 2- I know that the base call of a particular base is bounded by the mapping quality of its read. If my --stand_call_conf is 30 and one of the bases at this SNP position has MQ<30 does this avoid this position getting called? Or is it more like the avg(MQ) has to be >30 (meaning more than one read at this position is taken into account)?

Thanks for any clarification, Gene

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Hello,

I'm sorry if I'm being dense (I'm new to all this and it is making me feel very dense indeed!), but having read the section on 'Selecting an appropriate quality score threshold' on the 'Best Practice Variant Detection' page, I am still unclear as to whether you mean I should be looking for a QUAL score of at least 30 in a deep coverage data set and should filter out any suggested SNPs that don't meet this, or a GQ score of 30 in each individual sample genotyped at the SNP in question and I only need to filter out individual samples that don't meet this threshold.

Please can you clarify?

I have pasted the bit of text I read below, just to make it clear to which bit I am referring.

Many thanks!

A common question is the confidence score threshold to use for variant detection. We recommend:

Deep (> 10x coverage per sample) data: we recommend a minimum confidence score threshold of Q30.

Shallow (< 10x coverage per sample) data: because variants have by necessity lower quality with shallower coverage we recommend a minimum confidence score of Q4 in projects with 100 samples or fewer and Q10 otherwise.

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I was running UnifiedGenotyper on a set of 26 bam files. There was one particular position where I was comparing calls to the actual pileup and I noticed a major discrepancy. There was a no-call ("./.") for that position for one of the bam files while most other samples had calls. That non-called sample, though, had a very convincing variant in the pileup, with lots of high quality coverage at that position.

I then tried running just that bam file alone through UnifiedGenotyper, or that bam file along with two others. In both cases, the 1/1 variant is called properly with the following genotype field:

GT:AD:DP:GQ:MQ0:PL 1/1:0,66:66:99:0:2337,187,0

This seems to me to be a serious bug. Is this anything that's been noted before?

I am running GATKLite version 2.1-3-ge1dbcc8

Gene

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Dear all, I'm trying to run UnifiedGenotyper only at specific sites (a small subset of dbSNP) but I only get empty output. My command is

java -jar GATK.jar \
 -R hg19.fa -I file1.bam -I file2.bam \
-T UnifiedGenotyper \
-nct 8 -stand_call_conf 20.0 \
-glm BOTH -o output.vcf \
-U ALLOW_SEQ_DICT_INCOMPATIBILITY \
-L dbsnpsubset.vcf \
-out_mode EMIT_ALL_SITES

How should I run GATK to call (alternate or reference) on all given sites?

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I've tried to get genotype for all sites provided in interval file using haplotypeCaller. If using unifiedGenotyper, I can get the result by setting "output_mode EMIT_ALL_SITES". But haplotypeCaller doesn't report as expected by "output_mode EMIT_ALL_SITES". Even though I set "genotypeFullActiveRegion" or "fullHaplotype", haplotypeCaller doesn't seem to emit genotype at all sites. How to get desirable result using haplotypeCaller? Thanks!

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Hello the team,

For some genotypes, it seems are wrong, I know it's model based, and base q, map q, etc are considered in the model. I also read this link: http://gatkforums.broadinstitute.org/discussion/1235/why-didnt-the-unified-genotyper-call-my-snp-i-can-see-it-right-there-in-igv#latest But my case are special, the format is (ref allele count)/(alternative allele count) genotype call: 22/24 0/0 109/125 0/0 85/109 0/0 26/32 0/0 40/161 0/0 195/6 1/1 239/5 1/1 83/6 1/1 46/28 1/1

In one case, the two variants are adjacent to each other. In some case, they are one base indels.

Thanks,

Jim

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