Dear all,
 
I used 3 different segmentation algorithms (DNAcopy, GLAD and HomHMM from snapCGH package) to assess copy number variation in my data and I want to have a criteria to choose the best CNVs found. There are cases where all the 3 algorithms find the same CNV, cases where only 2 algorithms find the same CNV and cases where only 1 algorithm finds a CNV. 
 
Somebody could argue that a good criteria should be to exclude CNVs found with only 1 algorithm but I found that sometimes those CNVs are really there when I make a visual inspection of the data. 
I thought about making a Mann-Whitney test for each CNV to compare the log2-ratios between n probes from the CNV with (c-n) probes from the control region, where 'c' represents the total number of probes for that chromosome that are not in any CNV on that array. After correcting for multiple testing, a p-value is assign for each CNV giving me a criteria to choose the best CNVs found. 
 
Any comments on my approach and alternative ones will be very much appreciated.
Thanks in advance.
 

Best regards,
João Fadista

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