Function to prepare data for Linear Discriminant Analysis.

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

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.