Best approach to finding correlation between two genes from MAGIC imputed single-cell RNA-seq data
Hi, I have single-cell RNA-seq data from two conditions that has been run through the Seurat pipeline, had macrophage cells extracted and MAGIC imputation performed to restore the data to its underlying expression structure so that relationships between genes can be found. So essentially I have a count matrix containing the gene expression of each cell within my data that’s been imputed to remove noise and technical dropout.
I want to observe the correlation between specific transcription factors and targets in my two conditions but I’m not sure what the best method to use is. I know of the correlatePairs function from scran but I’m uncertain if its the best approach for imputed data or if there may be another method is considered better, especially as the corrolatePairs function seems to limit the p_values which makes comparison a bit ambiguous across conditions.
There are a few discussions on this topic but I couldn’t find much on whether the approaches are valid for imputed single cell data, so any insight on this issue is appreciated.
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