SetupLinearModel: Set up design matrices and response given a Seurat object

In yanwu2014/perturbLM: A lightweight R package that uses linear models to analyze the effects of chemical/genetic perturbations, conditions, and disease states on single gene expression.

Set up design matrices and response given a Seurat object

Description

Set up design matrices and response given a Seurat object

Usage

SetupLinearModel(
  obj,
  pert.col,
  batch.col = NULL,
  size.factor.col = NULL,
  mito.col = NULL,
  response.col = NULL,
  features.use = NULL,
  test.prop = 0.2,
  seed = 12345
)

Arguments

obj	Seurat object
pert.col	Metadata column containing perturbation info (required)
batch.col	Metadata column containing batch info (default: NULL)
size.factor.col	Metadata column containing library size info (default: NULL)
mito.col	Metadata column containing mitochondrial fraction info (default: NULL)
response.col	Metadata column containing the desired response. If NULL, the normalized data in the Seurat object will be used as the response.
features.use	If response.col is NULL, a subset of features to use for the response
test.prop	Proportion of cells held out for model evaluation

Value

List of x (perturbation + covariate design matrix) y (response vector or matrix), and family (response family)

yanwu2014/perturbLM documentation built on Aug. 24, 2023, 2:28 p.m.