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Iterate through Leiden resolutions for graph-based community detection.

cor_module_graph_check_res.Rd

This function will identify gene modules based on affinity graphs from the single correlation or differential correlation methods. Briefly, in the case of single correlation, the graph is generated based on the absolute correlation coefficients that are subjected to a Gaussian affinity kernel. This reduces spurious correlations and leaves a sparsely connected graph. In the case of differential correlations, the graph is generated based on significant differential correlations if one of the two correlations reached the defined minimum thresholds.
Subsequently, Leiden community detection is applied on the respective graph through a range of resolutions that the user can define. The function then returns meta information about the resolutions (which can also be plotted) to identify the best suitable resolution parameter to identify co-expression modules.

Usage

cor_module_graph_check_res(
  object,
  resolution_params = params_graph_resolution(),
  graph_params = params_cor_graph(),
  random_seed = 123L,
  min_genes = 10L,
  parallel = TRUE,
  max_workers = NULL,
  .verbose = TRUE
)

Arguments

object

The class, see BulkCoExp().

resolution_params

List. Parameters for the resolution search, see params_graph_resolution(). Contains:

  • min_res - Float. Minimum resolution to test.

  • max_res - Float. Maximum resolution to test.

  • number_res - Integer. Number of resolutions to test between the max_res and min_res.

graph_params

List. Parameters for the generation of the (differential) correlation graph, see params_cor_graph(). Contains:

  • Epsilon - Defines the epsilon parameter for the radial basis function. Defaults to 1, but should be ideally optimised.

  • min_cor - Float. Minimum absolute correlation that needs to be observed in either data set. Only relevant for differential correlation-based graphs.

  • fdr_threshold - Float. Maximum FDR for the differential correlation p-value.

  • verbose - Boolean. Controls verbosity of the graph generation.

random_seed

Integer. Random seed.

min_genes

Integer. Minimum number of genes that should be in a community.

parallel

Boolean. Parallelise the Leiden clustering.

max_workers

Optional Integer. Number of cores to use if parallel is set to TRUE. If set to NULL it will automatically detect the number of cores.

.verbose

Controls the verbosity of the function.

Value

The class with added data to the properties.