Dear GATK Team,
First of all, thank you for putting the two CNV calling tutorials together - this is the best WES CNV pipeline I have used. I have two questions:
1. When using CallCopyRatioSegments the default parameters are --neutral-segment-copy-ratio-lower-bound 0.9 and --neutral-segment-copy-ratio-upper-bound 1.1, which correspond to heterozygous copy number gain or loss in 20% of cells. This seems quite high number and I am wondering whether my data will allow me to call, for example heterozygous copy number gain or loss in 5% of cells by changing the parameters to --neutral-segment-copy-ratio-lower-bound 0.975 --neutral-segment-copy-ratio-upper-bound 1.025? In order to do so, I need to understand what my background it and make sure my calls are not just noise. Do you have a suggestion how I can define the background level and set a generic or sample-specific threshold to confidently call CNV gains and losses with lower frequencies?
2. The output from ModelSegments has a column called NUM_POINTS_COPY_RATIO - what does this parameter mean? I noticed that for some segments with very high or vary low copy ratio values, this number is very low. For example here for a sample with monosomy 7, e.g. line 2 and 4 in bold, NUM_POINTS_COPY_RATIO is 1:
CONTIG START END NUM_POINTS_COPY_RATIO MEAN_LOG2_COPY_RATIO CALL
chr7 31127 6764353 916 -0.969624 -
chr7 6765438 6766161 1 -29.219897 -
chr7 6805656 73111427 3213 -0.971284 -
chr7 73184300 73184960 1 -29.526709 -
chr7 73192104 76627026 571 -0.983072 -
chr7 76627027 76979097 3 -11.067441 -
chr7 76980343 77056891 14 -4.802967 -
chr7 77058881 77736804 89 -1.367833 -
chr7 77749237 144318694 5364 -0.980015 -
chr7 144362468 144372526 6 -11.344774 -
Do I need to exclude lines with low NUM_POINTS_COPY_RATIO values from the analysis? I see you have them in the tutorial too but haven't discussed what they mean. I was thinking to exclude all sites with <100 NUM_POINTS_COPY_RATIO but since I don't completely understand the parameter, I am a bit reluctant to do it. I would really appreciate your advice.
Thank you, Bilyana
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