Generate graph communities and their summarizing statistics

The results can subsequently be visualized with the function plotCommunitiesStats This function requires a filtered set of connections in the GRN object as generated by filterGRNAndConnectGenes. It then generates the TF-gene graph from the filtered connections, and clusters its vertices into communities using established community detection algorithms.

calculateCommunitiesStats(GRN, clustering = "louvain", forceRerun = FALSE, ...)

Arguments

GRN

Object of class GRN

clustering

Character. Default louvain. One of: louvain, leiden, leading_eigen, fast_greedy, optimal, walktrap. The community detection algorithm to be used. Please bear in mind the robustness and time consumption of the algorithms when opting for an alternative to the default.

forceRerun

TRUE or FALSE. Default FALSE. Force execution, even if the GRN object already contains the result. Overwrites the old results.

...

Additional parameters for the used clustering method, see the igraph::cluster_* methods for details on the specific parameters and what they do. For leiden clustering, for example, you may add a resolution_parameter to control the granularity of the community detection or n_iterations to modify the number of iterations.

Value

An updated GRN object, with a table that consists of the connections clustered into communities stored in the GRN@graph$TF_gene$clusterGraph slot as well as within the igraph object in GRN@graph$TF_gene$graph (retrievable via igraph using igraph::vertex.attributes(GRN@graph$TF_gene$graph)$community, for example.)

Examples

# See the Workflow vignette on the GRaNIE website for examples
GRN = loadExampleObject()
#> Downloading GRaNIE example object from https://git.embl.de/grp-zaugg/GRaNIE/-/raw/master/data/GRN.rds
#> Finished successfully. You may explore the example object. Start by typing the object name to the console to see a summaty. Happy GRaNIE'ing!
GRN = calculateCommunitiesStats(GRN, forceRerun = FALSE)
#> INFO [2024-04-04 17:35:15] Data already exists in object or the specified file already exists. Set forceRerun = TRUE to regenerate and overwrite.
#> INFO [2024-04-04 17:35:15]  Finished successfully. Execution time: 0 secs