If we want to cluster samples based on CNV data, a dataframe is needed. However, CNV segments in each sample are not the same. Maybe overlap or distinct. I think CNTools package migh solve this challenge. An example is shown as below. The result is a reduced segment data frame.
BiocManager::install("CNTools") data("sampleData") seg <- CNSeg(sampleData) rdseg <- getRS(seg, by = "region", imput = FALSE, XY = FALSE, what = "mean") View(rdseg@rs)
Input dataframe has six columns (“ID”,”chrom”,”loc.start”,”loc.end”,”num.mark”,”seg.mean”) including 277 samples and 54825 segments.

The result can be got from rdseg@rs, like this

Cheers
Also, we can use CNRegions from iClusterPlus package.
CNregions(sampleData)
Ref: https://www.rdocumentation.org/packages/CNTools
https://rdrr.io/bioc/iClusterPlus/man/CNregions.html
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