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 igraph
package.
So far i tried to use the adjacency matrix that the umap
function returns (uwot
package) to create a graph using igraphs
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, Seurats
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 igraphs
functions? I obviously don't have to use the matrix umap returned, but what would be a better approach to make my data "louvain-able"?