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.