find_cbf_modules: find_cbf_modules

In csbl-usp/fcoex: FCBF-based Co-Expression Networks for Single Cells

Description

find_cbf_modules uses Symmetrical Uncertainty as a correlation measure and the FCBF algorithm to 1 - Filter the gene list by correlations to a class (Step 1) and 2 - Determine soft thresholds for coexpression to genes predominantly correlated to a class.

Usage

find_cbf_modules(
  fc,
  n_genes_selected_in_first_step = NULL,
  FCBF_threshold = 0.1,
  verbose = TRUE,
  is_parallel = FALSE
)

## S4 method for signature 'fcoex'
find_cbf_modules(
  fc,
  n_genes_selected_in_first_step = NULL,
  FCBF_threshold = 0.1,
  verbose = TRUE,
  is_parallel = FALSE
)

Arguments

fc	A fcoex object containing a discretized expression table
n_genes_selected_in_first_step	Sets the number of genes to be selected in the first part of the algorithm. If left unchanged, it defaults to NULL and the minimum_su parameter is used. Caution: it overrides the minimum_su parameter altogether.
FCBF_threshold	A threshold for the minimum correlation (as determined by symettrical uncertainty) between each variable and the class used for wrapped FCBF function. Defaults to 0.1.
verbose	Adds verbosity. Defaults to TRUE
is_parallel	Uses package parallel to paralleliza calculations. Defaults to FALSE.

Value

Returns a list with the CBF modules found or a adjacency matrix of the graph

Examples

library(SingleCellExperiment)
data("mini_pbmc3k")
targets <- colData(mini_pbmc3k)$clusters
exprs <- as.data.frame(assay(mini_pbmc3k, "logcounts"))
fc <- new_fcoex(exprs, targets)
fc <- discretize(fc)
fc <- find_cbf_modules(fc)

csbl-usp/fcoex documentation built on Sept. 15, 2021, 7:42 a.m.