A collegue of mine recently suggested to try the louvain algorithm for clustering multiplex cytometry data. However, implementations of louvain are kind of rare in R. To my knowledge the only stand-alone implementation is included in the
So far i tried to use the adjacency matrix that the
umap function returns (
uwot package) to create a graph using
graph_from_adjacency_matrix function. I can run the louvain algorithm on the graph, but the result is always a few thousand clusters with a hand-full if cells. changing the resolution parameter does not change anything.
If i remember correctly,
findClusters function uses
louvain, however i don't want to use PCA reduction before clustering, which is requiered in
Seurat to find clusters.
Does anybody know of a different implementation of louvain or leiden algorithm that or an easier way to use
igraphsfunctions? I obviously don't have to use the matrix umap returned, but what would be a better approach to make my data "louvain-able"?