Evaluate feature selection against features label — evaluate_feature_selection

Compares the selection of features with different feature labels (e.g. result of a DE analysis) for each latent dimension.

Usage

evaluate_feature_selection_table(
  method_output,
  mo_data,
  col_names,
  latent_dimensions = NULL
)

method_output: Integration method output generated via the get_output() function.
mo_data: A MultiDataSet-class object.
col_names: Named character vector, giving for each dataset the name of the column in the features metadata table that contains the features label. If a dataset is not present in this vector, will be excluded from the resulting table.
latent_dimensions: Character vector, the latent dimensions to include in the resulting table. If NULL (default value), all latent dimensions will be represented.

A tibble, with for each dataset and latent dimension the number of selected and non-selected features per feature label.