Plots and graphics¶
Plot probe log2 coverages and segmentation calls together.
cnvkit.py scatter Sample.cnr -s Sample.cns
--range (or their single-letter
equivalents) focus the plot on the specified region:
cnvkit.py scatter Sample.cnr -s Sample.cns -r chr7 cnvkit.py scatter Sample.cnr -s Sample.cns -r BRAF cnvkit.py scatter Sample.cnr -s Sample.cns -r chr7:140434347-140624540
In the latter two cases, the
-w) argument determines the size
of the chromosomal regions to show flanking the selected region.
Loss of heterozygosity (LOH) can be viewed alongside copy number by passing
variants as a VCF file with the
-v option. Heterozygous SNP allelic
frequencies are shown in a subplot below the CNV scatter plot. (Also see the
loh command, below.)
cnvkit.py scatter Sample.cnr -s Sample.cns -v Sample.vcf
The probe copy number values can also be plotted without segmentation calls:
cnvkit.py scatter Sample.cnr
This can be useful if CBS is unavailable, or for viewing the raw, un-corrected coverages when deciding which samples to use to build a profile, or simply to see the coverages without being helped/biased by the called segments.
--trend option (
-t) adds a smoothed trendline to the plot. This is
fairly superfluous if a valid segment file is given, but could be helpful if CBS
is not available, or if you’re skeptical of the segmentation in a region.
Plot allelic frequencies at each variant position in a VCF file. Divergence from 0.5 indicates loss of heterozygosity (LOH) in a tumor sample.
cnvkit.py loh Sample.vcf
Draw copy number (either raw probes (.cnn, .cnr) or segments (.cns)) on chromosomes as a diagram. If both the raw probes and segmentation calls are given, show them side-by-side on each chromosome (segments on the left side, probes on the right side).
cnvkit.py diagram Sample.cnr cnvkit.py diagram -s Sample.cns cnvkit.py diagram -s Sample.cns Sample.cnr
Draw copy number (either raw probes (.cnn, .cnr) or segments (.cns)) for multiple samples as a heatmap.
The segmentation calls alone will render much faster, and will probably be more useful to look at.
cnvkit.py heatmap *.cns cnvkit.py heatmap *.cnr # Slow!