Prepare differential correlation-based module detection — diffcor_module

This function will calculate the differential correlation between the stored data set in the class and another background data set. To do so, it uses a Fisher transformation of the correlation coefficients and calculates a Z score based on the delta. The function will automatically subset into shared features between the two data sets.

Usage

diffcor_module_processing(
  object,
  background_mat,
  cor_method = c("pearson", "spearman"),
  .verbose = TRUE
)

Arguments

object: The class, see BulkCoExp(). Ideally, you should run preprocess_bulk_coexp() before applying this function.
background_mat: Numerical matrix. The background data set.
cor_method: String. Option of c("pearson", "spearman").
.verbose: Boolean. Controls verbosity of the function.

Value

The class with added data to the properties for subsequent usage.