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.

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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 ##################################################################### #版权所有 转载请告知 版权归作者所有 如有侵权 一经发现 必将追究其法律责 #Author: Jason

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