A paper I read recently mentioned in the methods that the authors performed copy number variation analysis on their single cell data, but neglected to mention the software used to perform the analysis. I've looked around and seen a lot of desktop and web-based tools, but few for R and few that specifically mention single cell RNAseq. Preferably, I'd be able to integrate this analysis into my downstream analysis R pipeline, but Python tools are fine too.
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written
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jrleary
1 answer
inferCNV or CONICSmat are probably the easiest to just pick up and try. It's important to remember that scRNA-seq data is sparse though, and you're not going to pickup small focal changes or get the high-resolution that you would with WGS or exome. It works better if you already have a list of CNAs from bulk WGS or such to feed in. You can, however, usually pick up changes in highly clonal cell populations fairly well. Certainly well enough to be of use.
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A few options are mentioned in a previous thread: Detecting copy number alterations based on RNA-seq data