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AntonioDeFalco / SCEVAN

R package that automatically classifies the cells in the scRNA data by segregating non-malignant cells of tumor microenviroment from the malignant cells. It also infers the copy number profile of malignant cells, identifies subclonal structures and analyses the specific and shared alterations of each subpopulation.
https://www.nature.com/articles/s41467-023-36790-9
GNU General Public License v3.0
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How to obtain quantitative metrics #45

Open ccruizm opened 1 year ago

ccruizm commented 1 year ago

Good day,

I like how accurate and fast the tool is! The pipeline assigns which cells are likely to be normal and which are malignant. I would like to know whether there is a way to score the cells based on the inferred presence or absence of CNV. Something similar to the approach described by Neftel et al 2019, quote directly: '...scored each cell for two CNA-based measures. ‘‘CNA signal’’ reflects the overall extent of CNAs, defined as the mean of the squares of CNA values across the genome. ‘‘CNA correlation’’ refers to the correlation between the CNA profile of each cell and the average CNA profile of all cells from the corresponding tumor, except for those classified by gene expression as non-malignant.' Is any info obtained from SCEVAN that could be used to compute those metrics?

Thanks in advance for your help!

Ilarius commented 4 months ago

Hello, maybe this could be computed from the value used for the generation of the heatmap. @AntonioDeFalco what do you think? It would be really nice to have a score, instead of a dicothomized value.