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VQSR for small exome data sets
Hi, I'm working with trios and small-pedigrees (up to six individuals). The VQSR section of the 'best practice' document states that 'in order to achieve the best exome results one needs an exome callset with at least 30 samples', and suggests to add additional samples such as 1000 genomes BAMs.
I' a little confused about two aspects:
1) the addition of 1000G BAMs being suggested in the VQSR section. If we need the 1000G call sets, we'd have to run these through the HaplotypeCaller or UnifiedGenotyper stages? Please forgive the question - I'm not trying to find fault in your perfect document, but please confirm as it would dramatically increase compute time (though only once), and overlaps with my next point of confusion:
2) I can understand how increasing the number of individuals from a consistent cohort, or maybe even from very similar experimental platforms, improves the outcome of the VQSR stage. However, the workshop video comments that the variant call properties are highly dependent on individual experiments (design, coverage, technical, etc). So I can't understand how the overall result is improved when I add variant calls from 30 1000G exomes (with their own typical variant quality distributions) to my trio's sample variant calls (also with their own, but very different to the 1000G's, quality distribution).
Hopefully I'm missing an important point somewhere?
Many thanks in advance,