Germline analysisΒΆ

CNVkit can be used with exome sequencing of constitutional (non-tumor) samples, for example to detect germline copy number alterations associated with heritable conditions. However, note that CNVkit is less accurate in detecting CNVs smaller than 1 Mbp, typically only detecting variants that span multiple exons or captured regions. When used on exome or target panel datasets, CNVkit will not detect the small CNVs that are more common in populations.

To use CNVkit to detect medium-to-large CNVs or unbalanced SVs in constitutional samples:

  • The call command can be used directly without specifying the --purity and --ploidy values, as the defaults will be correct for mammalian cells. (For non-diploid species, use the correct --ploidy, of course.) The default --method threshold assigns integer copy number similarly to --method clonal, but with smaller thresholds for calling single-copy changes. The default thresholds allow for mosaicism in CNVs, which have smaller log2 value than a single-copy CNV would indicate. (They’re more common than often thought.)
  • The --filter option in call can be used to reduce the number of false-positive segments returned. To use the ci (recommended) or sem filters, first run each sample’s segmented .cns file through segmetrics with the --ci option, which adds upper and lower confidence limits to the .cns output that call --filter ci can then use.
  • The --drop-low-coverage option (see Tumor analysis) should not be used; it will typically remove germline deep deletions altogether, which is not desirable.
  • For using CNVkit with whole-genome sequencing datasets, see Whole-genome sequencing and targeted amplicon capture.