I have run a Seurat pipeline to integrate 4 different scRNA datasets, and have been able to successfully run FindAllMarkers() for my clusters. In total, 12 clusters were found, and we are fairly confident about the identity of 10 of them. However, for 2 of the clusters, only a handful of genes are found, and don't really have good separation between groups:
DIFF | GENE
0.196 FADS2
0.173 PTPRF
0.17 TMA7
0.167 MT-ND2
0.164 MT-ND1
0.157 ERGIC1
0.156 SCD
0.153 SEC61A1
0.15 ASPH
In cases like this, where this aren't good markers for a group, what is the typical procedure? Lower the resolution of the cluster identifier and run again?
In the case that you run through a series of resolutions, and particular group is identified with few markers, is it safe to 'clump' it in with the group closest to it spatially?
Sure, if you feel that it's not worth separating. How granular people try to get with their annotations/subpopulations varies wildly, so you should rely on your expert knowledge of the biology/experiment to determine if that separation is valuable or meaningful.