doLouvainCluster_community: doLouvainCluster_community
In drieslab/Giotto_site_suite: Spatial Single-Cell Transcriptomics Toolbox

doLouvainCluster_community

R Documentation

doLouvainCluster_community

Description

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

Usage

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`	boolean: return giotto object (default = TRUE)
`set_seed`	set seed (default = FALSE)
`seed_number`	number for seed

Details

This function is a wrapper for the Louvain algorithm implemented in Python, which can detect communities in graphs of nodes (cells). See the https://python-louvain.readthedocs.io/en/latest/index.htmlreadthedocs page for more information.

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