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OsloM Community Finding

Source: R/netclu_oslom.R
netclu_oslom.Rd

This function finds communities in a (un)weighted (un)directed network based on the OsloM algorithm (http://oslom.org/, version 2.4).

Usage

netclu_oslom(
  net,
  weight = TRUE,
  cut_weight = 0,
  index = names(net)[3],
  seed = NULL,
  reassign = "no",
  r = 10,
  hr = 50,
  t = 0.1,
  cp = 0.5,
  directed = FALSE,
  bipartite = FALSE,
  site_col = 1,
  species_col = 2,
  return_node_type = "both",
  binpath = "tempdir",
  check_install = TRUE,
  path_temp = "oslom_temp",
  delete_temp = TRUE
)

Arguments

net

The output object from similarity() or dissimilarity_to_similarity(). If a data.frame is used, the first two columns represent pairs of sites (or any pair of nodes), and the next column(s) are the similarity indices.

weight

A boolean indicating if the weights should be considered if there are more than two columns.

cut_weight

A minimal weight value. If weight is TRUE, the links between sites with a weight strictly lower than this value will not be considered (0 by default).

index

Name or number of the column to use as weight. By default, the third column name of net is used.

seed

For the random number generator (NULL for random by default).

reassign

A character indicating if the nodes belonging to several community should be reassigned and what method should be used (see Note).

r

The number of runs for the first hierarchical level (10 by default).

hr

The number of runs for the higher hierarchical level (50 by default, 0 if you are not interested in hierarchies).

t

The p-value, the default value is 0.10. Increase this value if you want more modules.

cp

Kind of resolution parameter used to decide between taking some modules or their union (default value is 0.5; a bigger value leads to bigger clusters).

directed

A boolean indicating if the network is directed (from column 1 to column 2).

bipartite

A boolean indicating if the network is bipartite (see Details).

site_col

Name or number for the column of site nodes (i.e. primary nodes).

species_col

Name or number for the column of species nodes (i.e. feature nodes).

return_node_type

A character indicating what types of nodes (site, species, or both) should be returned in the output (return_node_type = "both" by default).

binpath

A character indicating the path to the bin folder (see install_binaries and Details).

check_install

A boolean indicating if the function should check that the OSLOM has been properly installed (see install_binaries and Details).

path_temp

A character indicating the path to the temporary folder (see Details).

delete_temp

A boolean indicating if the temporary folder should be removed (see Details).

Value

A list of class bioregion.clusters with five slots:

  1. name: A character containing the name of the algorithm.

  2. args: A list of input arguments as provided by the user.

  3. inputs: A list of characteristics of the clustering process.

  4. algorithm: A list of all objects associated with the clustering procedure, such as original cluster objects (only if algorithm_in_output = TRUE).

  5. clusters: A data.frame containing the clustering results.

In the algorithm slot, users can find the following elements:

  • cmd: The command line used to run OSLOM.

  • version: The OSLOM version.

  • web: The OSLOM's web site.

Details

OSLOM is a network community detection algorithm proposed in Lancichinetti et al. (2011) that finds statistically significant (overlapping) communities in (un)weighted and (un)directed networks.

This function is based on the 2.4 C++ version of OSLOM (http://www.oslom.org/software.htm). This function needs files to run. They can be installed with install_binaries.

If you changed the default path to the bin folder while running install_binaries, PLEASE MAKE SURE to set binpath accordingly.

If you did not use install_binaries to change the permissions and test the binary files, PLEASE MAKE SURE to set check_install accordingly.

The C++ version of OSLOM generates temporary folders and/or files that are stored in the path_temp folder (folder "oslom_temp" with a unique timestamp located in the bin folder in binpath by default). This temporary folder is removed by default (delete_temp = TRUE).

Note

Although this algorithm was not primarily designed to deal with bipartite networks, it is possible to consider the bipartite network as unipartite network (bipartite = TRUE). Do not forget to indicate which of the first two columns is dedicated to the site nodes (i.e. primary nodes) and species nodes (i.e. feature nodes) using the arguments site_col and species_col. The type of nodes returned in the output can be chosen with the argument return_node_type equal to both to keep both types of nodes, sites to preserve only the sites nodes, and species to preserve only the species nodes.

Since OSLOM potentially returns overlapping communities, we propose two methods to reassign the 'overlapping' nodes: randomly (reassign = "random") or based on the closest candidate community (reassign = "simil") (only for weighted networks, in this case the closest candidate community is determined with the average similarity). By default, reassign = "no" and all the information will be provided. The number of partitions will depend on the number of overlapping modules (up to three). The suffix _semel, _bis, and _ter are added to the column names. The first partition (_semel) assigns a module to each node. A value of NA in the second (_bis) and third (_ter) columns indicates that no overlapping module was found for this node (i.e. non-overlapping nodes).

References

Lancichinetti A, Radicchi F, Ramasco JJ & Fortunato S (2011) Finding statistically significant communities in networks. PLOS ONE 6, e18961.

See also

For more details illustrated with a practical example, see the vignette: https://biorgeo.github.io/bioregion/articles/a4_3_network_clustering.html.

Associated functions: netclu_greedy netclu_infomap netclu_louvain

Author

Maxime Lenormand (maxime.lenormand@inrae.fr)
Pierre Denelle (pierre.denelle@gmail.com)
Boris Leroy (leroy.boris@gmail.com)

Examples

comat <- matrix(sample(1000, 50), 5, 10)
rownames(comat) <- paste0("Site", 1:5)
colnames(comat) <- paste0("Species", 1:10)

net <- similarity(comat, metric = "Simpson")
com <- netclu_oslom(net)
#> OSLOM is not installed... Please have a look at https://bioRgeo.github.io/bioregion/articles/a1_install_binary_files.html for more details.
#> It should be located in /tmp/RtmpthrJxx/bin/OSLOM/