Assess marker purity across clusters or cell subsets

Quantifies marker purity by evaluating expression specificity within clusters or user-defined cell subsets.

Usage

markerPurity(
  data,
  assay = "RNA",
  layer = "counts",
  desired_markers = NULL,
  cluster_labels = NULL,
  desired_clusters = NULL,
  desired_cells = NULL,
  log1p = TRUE,
  remove_quiescent_cells = TRUE,
  high_quantile = 0.25,
  low_quantile = 0.25,
  noise_feature_thresh = 4,
  num_threads = -1,
  seed = 121,
  verbose = TRUE
)

Arguments

data: Either a Seurat object or a numeric matrix with features (genes) as rows and cells as columns.
assay: Assay name used for marker purity assessment.
layer: Data layer used for assessment.
desired_markers: Character vector of markers to assess.
cluster_labels: Character vector. Required if `desired_clusters` is specified. Either the name of the column in data@meta.data containing cluster labels, or a character vector of cluster labels with length equal to the number of columns (cells) in the `data` argument.
desired_clusters: Character vector of clusters to assess. Required if `desired_cells` is not specified. If not provided, marker purity will be assessed solely within `desired_cells`.
desired_cells: Named list of character vectors specifying the names of the desired cells. Required if `desired_clusters` is not specified.
log1p: Logical; whether to apply log1p transformation to the input data. It is recommended to set this argument to TRUE (default) if the data is not already on a log scale.
remove_quiescent_cells: Logical; whether to remove quiescent cells.
high_quantile: Quantile for defining high EWCSR values.
low_quantile: Quantile for defining low EWCSR values.
noise_feature_thresh: Threshold for filtering noise features.
num_threads: Number of threads to use.
seed: Random seed.
verbose: Logical; whether to display progress messages.

Value

An object of class MarkerPurity.

Details

Marker purity is assessed using EWCSR-based filtering and supports both Seurat objects and matrix-based inputs.

Examples

if (FALSE) { # \dontrun{
mp <- markerPurity(data = my_seurat_obj, cluster_labels = "seurat_clusters")
} # }