Hi all,
I have a conceptual question about this Seurat vignette.
In short, in the vignette they integrate single cell transcriptomics data from two different biological conditions stating that it will help with the following:
- Identify cell subpopulations that are present in both datasets
- Obtain cell type markers that are conserved in both control and stimulated cells
- Compare the datasets to find cell-type specific responses to stimulation
In my hands, celltype assignment works perfectly well using automated annotators such as SingleR no integration needed (at least with PBMC). And once I identify the cell-types, simply comparing the cells from the different conditions in each sub-populations would give me cell-type specific responses to stimulation. Especially for that last point, wouldn't integrating both conditions defeat the purpose of comparing them?
I totally get integrating different datasets to work around batch effect, but I'm really confused about integrating in this context. Can someone please explain the rationale of performing the analysis this way? Thanks!