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UnifiedGenotyper producing different genotype quality profiles for homozygote and heterozygote calls

I have a VCF containing 7.4m SNPs over 70 individuals from an F2 intercross, called by the UnifiedGenotyper v2.3.6. I am trying to set appropriate thresholds for filtering these SNPs. The attached plots summarise the individual calls from this data set, with depth on the x-axis, genotype quality on the y-axis and frequency of particular DP+GQ combinations shown in greyscale. The first plot shows 0/1 (heterozygote) calls, the second shows 0/0 (homozyote) calls (the 1/1 plot looks similar to the 0/0 plot).

The homozygote plot shows a clear relationship between minimum depth and maximum GQ; it is impossible to get high GQs at low depth. However, this is not the case for heterozygotes. This makes intuitive sense to me - at low depth, one cannot be sure that a call really is homozygote; perhaps the other allele simply hasn't been sequenced. But we can have more confidence in a low depth heterozygote, as both alleles have been seen.

However, I am wondering what your recommendations for best practice are here; do you recommend using the same GQ thresholds for homozygote and heterozygote calls, or different thresholds? If the same thresholds, it seems like there will be a bias at low coverage; many (quite possibly real) homozygote calls will be excluded, which will make it appear that there is an excess of heterozygosity in low coverage individuals.

Also, there seems to be a periodicity in the homozygote (but not the heterozygote) GQ values; GQ values divisible by three have a different distribution to other GQ values. I assume this doesn't affect the results too much (after all, the scale is fairly arbitrary in the first place) but I'd be interested to know what causes this, if it is known.

Thanks for your help,

John Davey

Best Answer


  • Thanks Geraldine. We are working on non-model species so using the VariantRecalibrator is tricky, but it's good to know that these kinds of profiles can be handled by it. I will look into producing a high quality set of SNPs for this data to use for calibration.

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