I have a vehicle vs. treatment dataset that I am working through and came across the following in the Seurat vignette that I don't quite understand and wanted to ask some questions about:
Here is the vignette : https://satijalab.org/seurat/v3.1/immune_alignment.html
Here is the section of code I would like to focus on:
DefaultAssay(immune.combined) <- "integrated" #Run the standard workflow for visualization and clustering immune.combined <- ScaleData(immune.combined, verbose = FALSE) immune.combined <- RunPCA(immune.combined, npcs = 30, verbose = FALSE) # t-SNE and Clustering immune.combined <- RunUMAP(immune.combined, reduction = "pca", dims = 1:20) immune.combined <- FindNeighbors(immune.combined, reduction = "pca", dims = 1:20) immune.combined <- FindClusters(immune.combined, resolution = 0.5)
Right after the integration steps and before the clustering steps, the DefaultAssay is changed to "integrated".
- What is this assay and how/why is it different than "RNA".
- What are the consequences of NOT changing it and leaving RNA as the default
- I noticed that when I leave my DefaultAssay as RNA and do not invoke command that the software finds more DE genes
in the downstream FindMarkers analysis. If I leave the default assay as RNA will I get the same results just less genes?
- Is it nessecary to change the DefaultAssay to "integrate" for a dataset like mine comparing two treatments that are