I've got my a dataset of single cells that were sequenced and generated the associated count files etc.
Up until know i've been using the Seurat package in R that is amazing at clustering cells itself (unsupervised), and it will then give you the genes differentially expressed between clusters A vs B etc.
One question I have though and can't find the solution is how to do "supervised" clustering (??) Basically I've got these cells that are for example Pax3+/CD146+ and these other cells that are Pax3+/CD146-. And these cells using the tSNE plot I can see fall in different clusters when I do conventional clustering (together with other unrelated cells). Does anyone know of a way that I can cluster all of the cells I want together in two different clusters (Pax3+ / CD146- & +) and then run differential expression testing (or even just get the gene lists) of those?