find_cbf_modules {fcoex} | R Documentation

## find_cbf_modules

### 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)

[Package fcoex version 1.6.0 Index]