Whole-genome sequencing and targeted amplicon captureΒΆ

CNVkit is designed for use on hybrid capture sequencing data, where off-target reads are present and can be used improve copy number estimates.

If necessary, CNVkit can be used on whole-genome sequencing (WGS) datasets by specifying the genome’s sequencing-accessible regions as the “targets”, avoiding “antitargets”, and using a gene annotation database to label genes in the resulting BED file:

cnvkit.py batch ... -t data/access-10000.hg19.bed -g data/access-10000.hg19.bed --split --annotate refFlat.txt


cnvkit.py target data/access-10000.hg19.bed --split --annotate refFlat.txt -o Targets.bed
cnvkit.py antitarget data/access-10000.hg19.bed -g data/access-10000.hg19.bed -o Background.bed

This produces a “target” binning of the entire sequencing-accessible area of the genome, and empty “antitarget” files which CNVkit will handle safely from version 0.3.4 onward.

Similarly, to use CNVkit on targeted amplicon sequencing data instead – although this is not recommended – you can exclude all off-target regions from the analysis by passing the target BED file as the “access” file as well:

cnvkit.py batch ... -t Targeted.bed -g Targeted.bed ...


cnvkit.py antitarget Targeted.bed -g Targeted.bed -o Background.bed

However, this approach does not collect any copy number information between targeted regions, so it should only be used if you have in fact prepared your samples with a targeted amplicon sequencing protocol. It also does not attempt to normalize each amplicon at the gene level, though this may be addressed in a future version of CNVkit.