identified (or “called”) using GWAS data where a series of single nucleotide polymorphisms (SNPs) or “intensity” probes are interrogated for their occurrence in a state other than the expected disomic (i.e. 2 copy) state. Typically, the intensity of the probe signal that is expected when two copies of the probe are present is compared with the observed intensity, which is expected to be enhanced for duplications, or suppressed for deletions. These probes are routinely included in GWAS chips and thus, as GWAS technology became more accessible, there was an up-swell in CNV identification efforts. However, this method of CNV calling from GWAS microarrays can be associated with relatively high error rates. For instance, in a previous study, we demonstrated the relatively modest concordance in CNV detection using three widely utilized software packages with varying algorithms. In that study, we implemented statistical measures that enhance the reliability of the detected CNVs using multiple algorithms and further, validated the CNVs identified using statistical programs by quantitative Polymerase Chain Reaction (qPCR) in the laboratory (Lin et al., 2011).
