I have a control dataset and a drug treatment dataset that was integrated following the seurat integration vignette. I then scaled the integrated and data and ran PCA followed by clustering.
I want to show which genes are differentially expressed for a given cluster, and importantly by how much.
For the first part ran the DEG's using the raw counts with FindMarkers and got a DEG list for that cluster.
Im curious how its possible to transfer this information to a heatmap. Basically Id like to have a list of DEGs as columns and the cells as rows.
I have created this with a 50 cell subset for my first cluster that you can view here:
The problem is that this heatmap was made using the raw counts from the treated dataset, so I dont think it really shows what I want to show. There would be no comparison between Vehicle and Treatment in here, although the gene list that I used for the columns came from the DEG list that I ran with FindMarkers
So then I plotted the integrated data for the same cell types and got this heatmap:
I dont understand exactly what this data is representing. What are these values that the integrated data stores for each gene and cell in the integrated data set that is represented on this plot? And since this plot is only for the treated cells, what does this represent?
I have the list of genes being DE in this cluster (columns); but is there a way to show how much the expression change is (compared to vehicle) in each cell in this figure? I don't get the feeling like thats what im looking at in the second plot
