extract_dataset_features: Extract Dataset Characteristics for Adaptive Parameter...

In SlimR: Adaptive Machine Learning-Powered, Context-Matching Tool for Single-Cell and Spatial Transcriptomics Annotation

Extract Dataset Characteristics for Adaptive Parameter Calculation (Use in package)

Description

Computes various statistical features from single-cell data that are used as input for the parameter prediction model.

Usage

extract_dataset_features(
  seurat_obj,
  features,
  assay = NULL,
  cluster_col = NULL
)

Arguments

seurat_obj	Seurat object
features	Features to analyze
assay	Assay name
cluster_col	Cluster column name

Value

List of dataset characteristics including expression statistics, variability measures, and cluster properties

See Also

Other Section_1_Functions_Use_in_Package: calculate_cluster_variability(), calculate_expression(), calculate_expression_skewness(), calculate_probability(), compute_adaptive_parameters(), estimate_batch_effect()

SlimR documentation built on Feb. 5, 2026, 5:08 p.m.