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I did an analysis via CPDB for a comprehensive list of cells in my dataset out of a spatial transcriptomics analysis.
Now, I have a csv file out of the analysis shows the PPI between all cells. Now, here is my question.
If there is a list of cells stored in the seurat object, should I do the analysis for some cells of interest separately from the scratch? I mean prepare Meta and Counts file just for those cells and do the statistical method for them? Or I should do the analysis for all cells and then, based on the output, I should limit the results to the cells of interest? I am wondering if these two approaches would make different results.
Best
The text was updated successfully, but these errors were encountered:
Statistical method uses empirical shuffling to calculate which ligand–receptor pairs display significant cell-type specificity. Therefore, for your case, running statistical method to all cells, then filtering the results to the cells of interest would be more suitable. However, if the cells of interest are in the same microenvironment, that should be OK to do the analysis on those cells separately. Hope this is helpful for you.
Hello there
I did an analysis via CPDB for a comprehensive list of cells in my dataset out of a spatial transcriptomics analysis.
Now, I have a csv file out of the analysis shows the PPI between all cells. Now, here is my question.
If there is a list of cells stored in the seurat object, should I do the analysis for some cells of interest separately from the scratch? I mean prepare Meta and Counts file just for those cells and do the statistical method for them? Or I should do the analysis for all cells and then, based on the output, I should limit the results to the cells of interest? I am wondering if these two approaches would make different results.
Best
The text was updated successfully, but these errors were encountered: