doLouvainCluster community

cluster cells using a NN-network and the Louvain algorithm from the community module in Python

.doLouvainCluster_community(
  gobject,
  spat_unit = NULL,
  feat_type = NULL,
  name = "louvain_clus",
  nn_network_to_use = "sNN",
  network_name = "sNN.pca",
  python_path = NULL,
  resolution = 1,
  weight_col = NULL,
  louv_random = FALSE,
  return_gobject = TRUE,
  set_seed = FALSE,
  seed_number = 1234,
  ...
)

Arguments

gobject

giotto object

spat_unit

spatial unit (e.g. "cell")

feat_type

feature type (e.g. "rna", "dna", "protein")

name

name for cluster, default to "louvain_clus"

nn_network_to_use

type of NN network to use (kNN vs sNN), default to "sNN"

network_name

name of NN network to use, default to "sNN.pca"

python_path

specify specific path to python if required

resolution

resolution, default = 1

weight_col

weight column to use for edges

louv_random

Will randomize the node evaluation order and the community evaluation order to get different partitions at each call (default = FALSE)

return_gobject

logical. return giotto object (default = TRUE)

set_seed

set seed (default = FALSE)

seed_number

number for seed

...

additional params to pass

Value

giotto object with new clusters appended to cell metadata

Details

This function is a wrapper for the Louvain algorithm implemented in Python, which can detect communities in graphs of nodes (cells). See the readthedocs page for more information.

Set weight_col = NULL to give equal weight (=1) to each edge.