calculate_probability: Calculate gene set expression and infer probabilities with...

In SlimR: Marker-Based Package for Single-Cell and Spatial-Transcriptomic Annotation

Calculate gene set expression and infer probabilities with control datasets (Use in package)

Description

Calculate gene set expression and infer probabilities with control datasets (Use in package)

Usage

calculate_probability(
  object,
  features,
  assay = NULL,
  cluster_col = NULL,
  min_expression = 0.1,
  specificity_weight = 3
)

Arguments

object	Enter a Seurat object.
features	Enter one or a set of markers.
assay	Enter the assay used by the Seurat object, such as "RNA". Default parameters use "assay = NULL".
cluster_col	Enter the meta.data column in the Seurat object to be annotated, such as "seurat_cluster". Default parameters use "cluster_col = NULL".
min_expression	The min_expression parameter defines a threshold value to determine whether a cell's expression of a feature is considered "expressed" or not. It is used to filter out low-expression cells that may contribute noise to the analysis. Default parameters use "min_expression = 0.1".
specificity_weight	The specificity_weight parameter controls how much the expression variability (standard deviation) of a feature within a cluster contributes to its "specificity score." It amplifies or suppresses the impact of variability in the final score calculation.Default parameters use "specificity_weight = 3".

Value

Average expression of genes in the input "Seurat" object given "cluster_col" and given "features".

See Also

Other Use_in_packages: calculate_expression()

SlimR documentation built on Aug. 19, 2025, 1:13 a.m.