R Implementation of Leiden Clustering Algorithm

Implements the 'Python leidenalg' module to be called in R. Enables clustering using the leiden algorithm for partition a graph into communities. See the 'Python' repository for more details: < https://github.com/vtraag/leidenalg> Traag et al (2018) From Louvain to Leiden: guaranteeing well-connected communities. .


leiden 0.1.0

  • Implements the Leiden algorithm in R by calling the leidenalg python library. Runs ModularityVertexPartition with defaults.

leiden 0.1.1

  • Removes dependancy on igraph R package and avoids writing to disk (compatible with CRAN). Passes adjacency matrix directly to python as a numpy array.

leiden 0.2.0

  • Adds passing arguments to the Python implementation: the partition_type and resolution_parameter. Runs the RBConfigurationVertexPartition by default (which is equivalent to ModularityVertexPartition with a resolution_parameter of 1).

leiden 0.2.1

  • Enable passing arguments to Python functions: initial_membership, weights, and node_sizes.

leiden 0.2.2

  • Changes to ensure compatibility with CRAN. Updates to vignettes and documentation.

leiden 0.2.3

  • Adds passing weighted adjacency matrices to derive weight parameters

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.


0.3.7 by S. Thomas Kelly, a month ago


Browse source code at https://github.com/cran/leiden

Authors: S. Thomas Kelly [aut, cre, trl] , Vincent A. Traag [com]

Documentation:   PDF Manual  

GPL-3 | file LICENSE license

Imports methods, reticulate, Matrix, igraph

Suggests bipartite, covr, data.table, devtools, graphsim, knitr, multiplex, multinet, markdown, network, RColorBrewer, rmarkdown, spelling, testthat, tibble

Imported by Seurat.

See at CRAN