calculate_probability: 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)

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

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

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".