mixedmodel_de: Run mixed model differential expression

In neurorestore/Libra: Differential expression utilizing biological replicates in single-cell data

Run mixed model differential expression

Description

Run differential expression, accounting for biological replicates in single cell data. Options include pseudobulk or mixed model approaches

Usage

mixedmodel_de(
  input,
  meta = NULL,
  replicate_col = "replicate",
  cell_type_col = "cell_type",
  label_col = "label",
  latent_vars = NULL,
  min_cells = 3,
  min_features = 0,
  de_family = "mixedmodel",
  de_method = "negbinom",
  de_type = "LRT",
  n_threads = 2,
  show_progress = T
)

Arguments

input	a single-cell matrix to be converted, with features (genes) in rows and cells in columns. Alternatively, a Seurat, monocle3, or or SingleCellExperiment object can be directly input.
meta	the accompanying meta data whereby the rownames match the column names of input.
replicate_col	the vector in meta containing the replicate information. Defaults to replicate.
cell_type_col	the vector in meta containing the cell type information. Defaults to cell_type.
label_col	the vector in meta containing the experimental label. Defaults to label.
min_cells	the minimum number of cells in a cell type to retain it. Defaults to 3.
min_features	the minimum number of expressing cells (or replicates) for a gene to retain it. Defaults to 0.
de_method	the mixed model type to use. Defaults to negbinom.
de_type	the specific mixed model test to use. Defaults to LRT.
n_threads	number of threads to use for parallelization.
show_progress	show a progress bar. Defaults to T
min_reps	the minimum number of replicates in a cell type to retain it. Defaults to 2.

Value

a data frame containing differential expression results.

neurorestore/Libra documentation built on Aug. 31, 2024, 8:53 p.m.