Select Top Differentially Expressed Features

Source: R/de_features.R

Applies moderated t-statistics via limma across one or more cohorts, then aggregates the resulting evidence into a ranked list of candidate features. The top entries can be used to seed downstream optimization or ratio construction workflows.

select_de_features(
  x_list,
  y_list,
  contrast = NULL,
  n_features = 50L,
  combination_method = c("OSP", "Stouffer", "Fisher", "maxP"),
  assay = NULL
)

Arguments

x_list

A matrix-like object, SummarizedExperiment, or list of such objects. Rows represent samples and columns represent features. When a list is supplied each element is treated as an independent cohort.

y_list

A binary response aligned with x_list. Must be a factor with levels c("No", "Yes"). Provide a list when x_list is a list.

contrast

Optional contrast string (or list of strings) passed to limma::makeContrasts(). Defaults to "Yes-No" to align with ensure_binary_response().

n_features

Number of features to return after ranking (default 50).

combination_method

Method for combining cohort-specific z-scores. One of "OSP", "Stouffer", "Fisher", or "maxP".

assay

For SummarizedExperiment inputs, the assay name or index to extract prior to modelling.

Value

Character vector of feature identifiers ordered by significance.