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Coverage bias in HaplotypeCaller
I am doing joint variant calling for Illumina paired end data of 150 monkeys. Coverage varies from 3-30 X with most individuals having around 4X coverage.
I was doing all the variant detection and hard-filtering (GATK Best Practices) process with both UnifiedGenotyper and Haplotype caller.
My problem is that HaplotypeCaller shows a much stronger bias for calling the reference allele in low coverage individuals than UnifiedGenotyper does. Is this a known issue?
In particular, consider pairwise differences across individuals:
The absolute values are lower for low coverage individuals than for high coverage, for both methods, since it is more difficult to make calls for them.
However, for UnifiedGenotyper, I can correct for this by calculating the "accessible genome size" for each pair of individuals by substracting from the total reference length all the filtered sites and sites where one of the two individuals has no genotype call (./.). If I do this, there is no bias in pairwise differences for UnifiedGenotyper. Values are comparable for low and high coverage individuals (If both pairs consist of members of similar populations).
However, for HaplotypeCaller, this correction does not remove bias due to coverage. Hence, it seems that for UnifiedGenotyper low coverage individuals are more likely to have no call (./.) but if there is a call it is not biased towards reference or alternative allele (at least compared to high coverage individuals). For HaplotypeCaller, on the other hand, it seems that in cases of doubt the genotype is more likely to be set to reference. I can imagine that this is an effect of looking for similar haplotypes in the population.
Can you confirm this behaviour? For population genetic analysis this effect is highly problematic. I would trade in more false positive if this removed the bias. Note that when running HaplotypeCaller, I used a value of 3*10^(-3) for the expected heterozygosity (--heterozygosity) which is the average cross individuals diversity and thus already at the higher-end for within individual heterozygosity. I would expect the problem to be even worse if I chose lower values.
Can you give me any recommendation, should I go back using UnifiedGenotyper or is there any way to solve this problem?
Many thanks in advance,