Run ambient RNA decontamination with decontX

Usage

RunDecontX(
  srt,
  assay = "RNA",
  group.by = NULL,
  batch = NULL,
  background = NULL,
  background_assay = NULL,
  bg_batch = NULL,
  assay_name = "decontXcounts",
  store_assay = TRUE,
  round_counts = FALSE,
  data_type = NULL,
  seed = 11,
  ...,
  verbose = TRUE
)

Arguments

srt: A Seurat object.
assay: The name of the assay to be used for decontamination. Default is "RNA".
group.by: Cell cluster labels passed to decontX::decontX(). Can be NULL, a meta.data column name, or a vector aligned to cells. Default is NULL.
batch: Batch labels passed to decontX::decontX(). Can be NULL, a meta.data column name, or a vector aligned to cells. Default is NULL.
background: Optional background / empty-droplet input passed to decontX::decontX(). Can be a Seurat object, SingleCellExperiment, or count matrix. Default is NULL.
background_assay: Assay name used when background is a Seurat object or SingleCellExperiment. Default is NULL, which falls back to assay for Seurat background and "counts" for SingleCellExperiment background.
bg_batch: Batch labels for background passed to decontX::decontX(). Can be NULL, a metadata column name, or a vector aligned to the background droplets. Default is NULL.
assay_name: Name of the assay used to store decontaminated counts. Default is "decontXcounts".
store_assay: Whether to store decontaminated counts as a new assay. Default is TRUE.
round_counts: Whether to round decontaminated counts before creating the assay. Default is FALSE.
data_type: Optional precomputed result from CheckDataType() for the input assay. Primarily used internally to avoid repeated scans of the same count matrix across nested QC calls.
seed: Random seed for reproducibility. Default is 11.
...: Additional arguments passed to decontX::decontX().
verbose: Whether to print the message. Default is TRUE.

Value

Returns a Seurat object with decontX contamination estimates stored in the meta.data, and optional decontaminated counts stored in a new assay.

Examples

data(pancreas_sub)
pancreas_sub <- standard_scop(pancreas_sub)
pancreas_sub <- RunDecontX(
  pancreas_sub,
  group.by = "CellType"
)

FeatureStatPlot(
  pancreas_sub,
  stat.by = "decontX_contamination"
)

FeatureDimPlot(
  pancreas_sub,
  features = "decontX_contamination"
)