doLeidenCluster: doLeidenCluster
In RubD/Giotto: Spatial Single-Cell Transcriptomics Toolbox

doLeidenCluster

R Documentation

doLeidenCluster

Description

cluster cells using a NN-network and the Leiden community detection algorithm

Usage

doLeidenCluster(
  gobject,
  name = "leiden_clus",
  nn_network_to_use = "sNN",
  network_name = "sNN.pca",
  python_path = NULL,
  resolution = 1,
  weight_col = "weight",
  partition_type = c("RBConfigurationVertexPartition", "ModularityVertexPartition"),
  init_membership = NULL,
  n_iterations = 1000,
  return_gobject = TRUE,
  set_seed = T,
  seed_number = 1234
)

Arguments

`gobject`	giotto object
`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`	specify specific path to python if required
`resolution`	resolution
`weight_col`	weight column to use for edges
`partition_type`	The type of partition to use for optimisation.
`init_membership`	initial membership of cells for the partition
`n_iterations`	number of interations to run the Leiden algorithm. If the number of iterations is negative, the Leiden algorithm is run until an iteration in which there was no improvement.
`return_gobject`	boolean: return giotto object (default = TRUE)
`set_seed`	set seed
`seed_number`	number for seed

Details

This function is a wrapper for the Leiden algorithm implemented in python, which can detect communities in graphs of millions of nodes (cells), as long as they can fit in memory. See the https://github.com/vtraag/leidenalgleidenalg github page or the https://leidenalg.readthedocs.io/en/stable/index.htmlreadthedocs page for more information.

Partition types available and information:

RBConfigurationVertexPartition: Implements Reichardt and Bornholdt’s Potts model with a configuration null model. This quality function is well-defined only for positive edge weights. This quality function uses a linear resolution parameter.
ModularityVertexPartition: Implements modularity. This quality function is well-defined only for positive edge weights. It does not use the resolution parameter

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