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

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0.3.7 by S. Thomas Kelly, 4 months 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.

Suggested by wpa.

See at CRAN