PCAFast: Run Principal Component Analysis on gene expression using...

In nukappa/seurat_v2: Seurat : R toolkit for single cell genomics

Description

Run Fast PCA dimensionality reduction

Usage

PCAFast(object, pc.genes = NULL, do.print = TRUE, pcs.print = 5,
  pcs.compute = 20, genes.print = 30, ...)

Arguments

object	Seurat object
pc.genes	Genes to use as input for PCA. Default is [e-mail]
do.print	Print the top genes associated with high/low loadings for the PCs
pcs.print	Number of PCs to print genes for
pcs.compute	Total Number of PCs to compute and store
genes.print	Number of genes to print for each PC
...	Additional arguments to be passed to prcomp

Value

Returns Seurat object with an PCA embedding ([e-mail]) and gene projection matrix (object@pca.x). The PCA object itself is stored in [e-mail][[1]]

nukappa/seurat_v2 documentation built on May 24, 2019, 9:57 a.m.