cluster cells using a NN-network and the Louvain algorithm.
doLouvainCluster( gobject, version = c("community", "multinet"), name = "louvain_clus", nn_network_to_use = "sNN", network_name = "sNN.pca", python_path = NULL, resolution = 1, weight_col = NULL, gamma = 1, omega = 1, louv_random = F, return_gobject = TRUE, set_seed = F, seed_number = 1234, ... )
| gobject | giotto object |
|---|---|
| version | implemented version of Louvain clustering to use |
| name | name for cluster |
| nn_network_to_use | type of NN network to use (kNN vs sNN) |
| network_name | name of NN network to use |
| python_path | [community] specify specific path to python if required |
| resolution | [community] resolution |
| weight_col | weight column name |
| gamma | [multinet] Resolution parameter for modularity in the generalized louvain method. |
| omega | [multinet] Inter-layer weight parameter in the generalized louvain method |
| louv_random | [community] Will randomize the node evaluation order and the community evaluation order to get different partitions at each call |
| return_gobject | boolean: return giotto object (default = TRUE) |
| set_seed | set seed |
| seed_number | number for seed |
| ... | additional parameters |
giotto object with new clusters appended to cell metadata
Louvain clustering using the community or multinet implementation of the louvain clustering algorithm.