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Filter samples of bad quality before running GermlineCNVCaller
Do you filter out samples of bad quality (e.g. high variability in read counts) before constructing the model in GermlineCNVCaller cohort mode as it is known from other CNV calling methods? Which metrics would you recommend to identify low quality samples? Or are these bad samples automatically leveled out if the cohort is just big enough?
I often observe a few samples making up a large proportion of all found copy-number variations (mainly false positives I guess) and I wonder if I can filter out these samples beforehand.