Coverage Uniformity

The DRAGEN CNV pipeline provides a measure of the quality of the data for a sample. The CNV pipeline assumes that post-normalization target counts are independently and identically distributed (IID). Coverage in most high-quality WGS samples is uniform enough for the CNV caller to produce accurate calls, but some samples violate the IID assumption in a manner and to a degree that leads to unusually high numbers of false positive calls. For such samples, there are local correlations of coverage bias extending across multiple target intervals so that most or all the target counts in a given genomic region will be artifactually elevated (or, alternatively, depressed), and the strength of the bias is sufficient for the region to be identified as a distinct copy number segment and assigned an incorrect copy number. The CoverageUniformity metric quantifies the degree of local coverage correlation in the sample to help identify poor-quality samples. CoverageUniformity is present in the VCF header when WGS self-normalization method is selected. This metric is only available for germline samples.

A larger value for this metric means the coverage in a sample is less uniform, which indicates that the sample has more nonrandom noise, and could be considered poor quality. The CoverageUniformity metric depends on factors other than sample quality, such as the cnv-interval-width setting and sample mean coverage. DRAGEN recommends using this score to compare the quality of samples from similar mean coverage and the same command line options. Because of this, DRAGEN CNV only provides the metric and does not take any action based on it.