Hello.
When I read, let's say, 10 different samples consecutively with read10X, then make a Seurat object for each, of them, then merge them, like this
SeuratObject <- merge(object1, y = c(object2, object3, object4, object5, object6, object7, object8, object9, object10))
When I run my downstream analysis, I encounter a problem. Let's say all of these 10 samples are either treated or untreated. I would like on my UMAP projection, for example, to be able to highlight only the cells coming from the treated samples. Likewise, I would like to make a DESeq analysis between the cells in the same cluster, but treated vs untreated.
I saw that there is this tutorial : https://satijalab.org/seurat/articles/de_vignette
But I struggle to understand this part :
Since this dataset contains treatment information (control versus stimulated with interferon-beta), we can also ask what genes change in different conditions for cells of the same type. First, we create a column in the meta.data slot to hold both the cell type and treatment information and switch the current Idents to that column. Then we use FindMarkers() to find the genes that are different between control and stimulated CD14 monocytes.
How and when can I label my samples to do as I want ? I tried the add.cells.id argument in the merge function but it does not work. I assume the labelling would be done either in the merging or right after it but I can't find a way.
I would greatly appreciate some help, thank you.
