I have a question about how to decide on the clustering resolution to use for single-cell RNA-sequencing datasets that contain multiple activation states rather than discrete cell populations.
I have 10x Genomics scRNA-seq data from TCR-activated memory T cells from three donors (~2000-3000 cells/donor). When clustering is performed, the clusters represent distinct states of activation rather than discrete cell subsets. This means that it is not possible to use cell-specific marker genes to identify the optimal clustering resolution. I have also tried plotting clustering trees to find the optimal resolution, but the clustering is not particularly stable.
In this case, how would you decide on the clustering resolution to use and would you use the same clustering resolution for each of the three samples?