get_variable_genes_by_fitting_GLM_model: Identified variable genes by fitting the GLM model using mean...

In supatt-lab/SingCellaR: SingCellaR: an integrative analysis tool for single-cell RNA sequencing (scRNA-seq) data

Identified variable genes by fitting the GLM model using mean vs coefficient of variation

Description

Identified variable genes by fitting the GLM model using mean vs coefficient of variation

Usage

get_variable_genes_by_fitting_GLM_model(
  object,
  mean_expr_cutoff = 0.1,
  disp_zscore_cutoff = 0.1,
  quantile_genes_expr_for_fitting = 0.2,
  quantile_genes_cv2_for_fitting = 0.8
)

Arguments

object	The SingCellaR object.
mean_expr_cutoff	The mean expression cutoff.
disp_zscore_cutoff	The dispersion of z-score cutoff.
quantile_genes_expr_for_fitting	The quantile gene expression used for fitting the model.
quantile_genes_cv2_for_fitting	The quantile coefficient of variation used for fitting the model.

supatt-lab/SingCellaR documentation built on Aug. 24, 2023, 5:49 p.m.