Differential Expression with Optional Cell Pooling

It can run Seurat DE directly or first aggregate cells into metacells using CellDEEP pooling.

FindMarker.CellDEEP(
  object,
  ident.1 = NULL,
  ident.2 = NULL,
  group.by = "group_id",
  sample_id = NULL,
  group_id = NULL,
  cluster_id = NULL,
  prepare = TRUE,
  test.use = "wilcox",
  Pool = TRUE,
  readcounts = "sum",
  n_cells = 10,
  assay = "RNA",
  min_cells_per_subgroup = 25,
  cell_selection = "kmean",
  name.only = TRUE,
  logfc.threshold = 0.25,
  min.pct = 0.01,
  p_cutoff = 0.05,
  full_list = FALSE,
  ...
)

Arguments

object

A Seurat object.

ident.1

Character. First identity group to compare.

ident.2

Character. Second identity group to compare.

group.by

Character. Metadata column used for grouping (default "group_id").

sample_id

Character. Input metadata column for sample IDs.

group_id

Character. Input metadata column for group IDs.

cluster_id

Character. Input metadata column for cluster IDs.

prepare

Logical. If TRUE, run prepare_data first.

test.use

Character. DE test to use.

Pool

Logical. If TRUE, perform CellDEEP pooling before DE (default TRUE).

readcounts

Character. Pool aggregation method: "sum", "mean", or "10X".

n_cells

Integer. Target number of cells per pool.

assay

Character. Assay to use (default "RNA").

min_cells_per_subgroup

Integer. Minimum cells in each sample-cluster subgroup required for pooling.

cell_selection

Character. Pooling strategy: "kmean" or "random".

name.only

Logical. If TRUE, return gene names only.

logfc.threshold

Numeric. Minimum log fold-change.

min.pct

Numeric. Minimum detection rate.

p_cutoff

Numeric. Adjusted p-value threshold.

full_list

Logical. If TRUE, return all genes regardless of p-value.

...

Additional arguments passed to Seurat::FindMarkers.

Value

A vector of gene names or a DE data.frame.