Proportion Test

RunProportionTest performs a Monte-carlo permutation test to quantify the cell proportion differences between each condition.

Usage

RunProportionTest(
  srt,
  group.by,
  split.by,
  comparison = NULL,
  n_permutations = 1000,
  FDR_threshold = 0.05,
  log2FD_threshold = log2(1.5),
  include_all_cells = FALSE,
  verbose = TRUE
)

Arguments

srt

A Seurat object containing count data and metadata.

group.by

The name of the metadata column in srt containing cluster labels or cell type names.

split.by

The name of the metadata column in srt that contains sample identifiers.

comparison

Optional: specify comparisons to perform.

n_permutations

Number of permutations for the test.

FDR_threshold

FDR value cutoff for significance.

log2FD_threshold

Absolute value of log2FD cutoff for significance.

include_all_cells

Whether to include all cell types in the complete grid (default: FALSE).

verbose

Whether to print the message. Default is TRUE.

References

Miller et al. paper, scProportionTest

See also

ProportionTestPlot

Examples

data(pancreas_sub)
# Default behavior: only include cell types present in comparison groups
pancreas_sub <- RunProportionTest(
  pancreas_sub,
  group.by = "CellType",
  split.by = "Phase",
  comparison = list(c("G2M", "G1"))
)
#> ℹ [2025-11-13 12:29:58] Start proportion test
#> ℹ [2025-11-13 12:29:58] Running comparison: "G1" vs "G2M"
#> ℹ [2025-11-13 12:30:05] Running comparison: "G2M" vs "G1"
#> ✔ [2025-11-13 12:30:12] Proportion test completed

# Include all cell types from the dataset
pancreas_sub <- RunProportionTest(
  pancreas_sub,
  group.by = "CellType",
  split.by = "Phase",
  comparison = list(c("G2M", "G1")),
  include_all_cells = TRUE
)
#> ℹ [2025-11-13 12:30:12] Start proportion test
#> ℹ [2025-11-13 12:30:12] Running comparison: "G1" vs "G2M"
#> ℹ [2025-11-13 12:30:19] Running comparison: "G2M" vs "G1"
#> ✔ [2025-11-13 12:30:27] Proportion test completed

ProportionTestPlot(
  pancreas_sub
)