perform_de: Perform Differential Gene Expression on a...

In combiz/scFlow: A Single-Cell/Nuclei Analysis Toolkit

Perform Differential Gene Expression on a SingleCellExperiment

Description

Perform Differential Gene Expression on a SingleCellExperiment

Usage

perform_de(
  sce,
  de_method = "MASTZLM",
  mast_method = "glm",
  min_counts = 1,
  min_cells_pc = 0.1,
  rescale_numerics = TRUE,
  dependent_var = "group",
  ref_class = "Control",
  confounding_vars = c("individual", "cngeneson", "sex", "age", "PMI", "RIN", "seqdate",
    "pc_mito"),
  random_effects_var = NULL,
  interaction_vars = NULL,
  unique_id_var = "individual",
  species = getOption("scflow_species", default = "human"),
  parallel = TRUE,
  ...
)

Arguments

sce	a SingleCellExperiment object
de_method	The differential gene expression method.
mast_method	If de_method is "MASTZLM" then mast_method should be provided. Possible values are "glm", "glmer", "bayesglm". Default is "glm". For "glmer" and "random_effects_var" should be provided.
min_counts	minimum number of counts
min_cells_pc	percentage of cells with min_counts for gene selection
rescale_numerics	rescaling numerics may improve model
dependent_var	the name of the colData variable for contrasts
ref_class	the class of dependent_var used as reference
confounding_vars	the independent variables of the model
random_effects_var	variable(s) to model as random effects
interaction_vars	two or more variables to model as interacting
unique_id_var	the colData variable identifying unique samples
species	human or mouse
parallel	enable parallel processing
...	advanced options

Value

results_l a list of DE table results

See Also

Other differential gene expression: .filter_sce_genes_for_de(), .generate_model_from_vars(), .perform_de_with_mast(), .preprocess_sce_for_de(), pseudobulk_sce(), report_de(), volcano_plot()

combiz/scFlow documentation built on Feb. 25, 2024, 10:25 a.m.