Hi,
I would like to get some clarification on whether I should be using the RNA assay or the SCT assay for differential expression analysis in Seurat. I have seen several issues on the GitHub and FAQ 4, however these usually refer to data that has been integrated using the Seurat workflow. In my case, I have not performed integration so have an RNA and SCT assay only. I have used Harmony for batch correction.
The choice of assay seems to make a large difference to the number of differentially expressed genes. I am using the logistic regression (LR) option of FindMarkers() with "donor" as a latent variable. In one example, using the SCT assay I get 372 positive cluster markers, compared with 690 positive cluster markers using the RNA assay. The genes identified using the SCT assay are also identified by the RNA assay, but I just get extra genes with the RNA assay.
Why would the RNA assay give me so many more genes? And which assay should I trust?
When plotting gene expression on the UMAP and in violin plots, am I ok to use the SCT assay, or should I again be using RNA?
Many thanks for helping to clear up this confusion!
Best wishes,
Lucy
Thanks, I saw this, but their question refers to integration analysis and discusses other effects specific to the integration workflow, so I wasn't sure whether this was also relevant for non-integrated data
This applies for any usage of SCTransform.