% Generated by roxygen2: do not edit by hand

% Please edit documentation in R/scAI_model.R

\name{runLeiden}

\alias{runLeiden}

\title{Run Leiden clustering algorithm

This code is modified from Tom Kelly (https://github.com/TomKellyGenetics/leiden), where we added more parameters (seed.use and n.iter) to run the Python version. In addition, we also take care of the singleton issue after running leiden algorithm.}

\usage{

runLeiden(SNN = matrix(), resolution = 1,

  partition_type = c("RBConfigurationVertexPartition",

  "ModularityVertexPartition", "RBERVertexPartition", "CPMVertexPartition",

  "MutableVertexPartition", "SignificanceVertexPartition",

  "SurpriseVertexPartition"), seed.use = 42L, n.iter = 10L,

  initial.membership = NULL, weights = NULL, node.sizes = NULL)

}

\arguments{

\item{SNN}{An adjacency matrix compatible with \code{\link[igraph]{igraph}} object.}

\item{resolution}{A parameter controlling the coarseness of the clusters}

\item{partition_type}{Type of partition to use. Defaults to RBConfigurationVertexPartition. Options include: ModularityVertexPartition, RBERVertexPartition, CPMVertexPartition, MutableVertexPartition, SignificanceVertexPartition, SurpriseVertexPartition (see the Leiden python module documentation for more details)}

\item{seed.use}{set seed}

\item{n.iter}{number of iteration}

\item{initial.membership}{arameters to pass to the Python leidenalg function defaults initial_membership=None}

\item{weights}{defaults weights=None}

\item{node.sizes}{Parameters to pass to the Python leidenalg function}

}

\value{

A parition of clusters as a vector of integers

}

\description{

Implements the Leiden clustering algorithm in R using reticulate to run the Python version. Requires the python "leidenalg" and "igraph" modules to be installed. Returns a vector of partition indices.

}

\keyword{graph}

\keyword{igraph}

\keyword{mvtnorm}

\keyword{network}

\keyword{simulation}