PrepLDA: Function to prepare data for Linear Discriminant Analysis.

In satijalab/seurat: Tools for Single Cell Genomics

Function to prepare data for Linear Discriminant Analysis.

Description

This function performs unsupervised PCA on each mixscape class separately and projects each subspace onto all cells in the data.

Usage

PrepLDA(
  object,
  de.assay = "RNA",
  pc.assay = "PRTB",
  labels = "gene",
  nt.label = "NT",
  npcs = 10,
  verbose = TRUE,
  logfc.threshold = 0.25
)

Arguments

object	An object of class Seurat.
de.assay	Assay to use for selection of DE genes.
pc.assay	Assay to use for running Principle components analysis.
labels	Meta data column with target gene class labels.
nt.label	Name of non-targeting cell class.
npcs	Number of principle components to use.
verbose	Print progress bar.
logfc.threshold	Limit testing to genes which show, on average, at least X-fold difference (log-scale) between the two groups of cells. Default is 0.25. Increasing logfc.threshold speeds up the function, but can miss weaker signals.

Value

Returns a list of the first 10 PCs from each projection.

satijalab/seurat documentation built on May 11, 2024, 4:04 a.m.