Pseudobulk Differential Expression Analysis (Deprecated)

get.dea() has been renamed to get.pbDE() for clarity. This function is provided for backward compatibility and will be removed in a future version.

Usage

get.dea(
  .tdr.obj,
  .design,
  .contrasts = NULL,
  .block = NULL,
  .geneset.ls = NULL,
  .id.idx = NULL,
  .id = NULL,
  .id.from = NULL,
  .verbose = TRUE,
  .label.confidence = 0.5
)

Arguments

.design

Design matrix specifying experimental design (design mode only). Rows = samples, columns = coefficients.

.contrasts

Optional contrast matrix for specific comparisons (design mode only). Create with limma::makeContrasts(). If NULL, tests all .design coefficients.

.block

Optional character: column name in .tdr.obj$metadata for blocking factor (design mode only, e.g., "Donor"). Accounts for within-block correlation.

.geneset.ls

Optional named list of character vectors defining gene sets for GSVA enrichment analysis. Only for RNA data. Example: list("Tcell" = c("CD3D", "CD3E"), "Bcell" = c("CD19", "MS4A1")).

.id.idx

Optional integer vector specifying landmark indices. In design mode, restricts analysis to cells confidently assigned to these landmarks. In marker mode, defines group 1 landmark indices.

.id

Optional character vector of cluster/celltype IDs. In design mode, restricts analysis to cells matching these IDs. In marker mode, defines group 1 (test group).

.id.from

Character: "clustering" or "celltyping". Source of IDs in .id and .id2. Default NULL (resolved to "clustering" when needed).

.verbose

Logical: print progress messages? Default TRUE.

.label.confidence

Numeric scalar in [0,1] controlling the minimum posterior confidence required to assign a cell to a set of target landmarks (used when .id.idx or .id2.idx is provided). Default 0.5.

Value

A list containing DE analysis results (legacy format). Use get.pbDE() instead which stores results in .tdr.obj$pbDE and returns the modified object.

See also

get.pbDE