I'm trying to decide which of the default
Seurat v3 clustering algorithms is the most effective. The 3 R-based options are: 1)Louvain, 2) Louvain w/ multilevel refinement, and 3) SLM. The documentation is very vague about what the differences between the algorithms are, and gives no hint as to which algorithm one should use in different situations. I've always just used the original Louvain because it's the default, but are there situations / data that would be better represented using one of the other two algorithms?