ProjectPCA: Project Principal Components Analysis onto full dataset

In mayer-lab/SeuratForMayer2018: Seurat : R Toolkit for Single Cell Genomics

Description

Takes a pre-computed PCA (typically calculated on a subset of genes) and projects this onto the entire dataset (all genes). Note that the cell loadings remains unchanged, but now there are gene loading scores for all genes.

Usage

ProjectPCA(object, do.print = TRUE, pcs.print = 1:5, pcs.store = 30,
  genes.print = 30, replace.pc = FALSE, do.center = FALSE)

Arguments

object	Seurat object
do.print	Print top genes associated with the projected PCs
pcs.print	Number of PCs to print genes for
pcs.store	Number of PCs to store (default is 30)
genes.print	Number of genes with highest/lowest loadings to print for each PC
replace.pc	Replace the existing PCA (overwite object@dr$[e-mail]), not done by default.
do.center	Center the dataset prior to projection (should be set to TRUE)

Value

Returns Seurat object with the projected PCA values in object@dr$[e-mail]

mayer-lab/SeuratForMayer2018 documentation built on May 25, 2019, 9:34 p.m.