supercell_prcomp: compute PCA for super-cell data (sample-weighted data)

In SuperCell: Simplification of scRNA-Seq Data by Merging Together Similar Cells

compute PCA for super-cell data (sample-weighted data)

Description

compute PCA for super-cell data (sample-weighted data)

Usage

supercell_prcomp(
  X,
  genes.use = NULL,
  genes.exclude = NULL,
  supercell_size = NULL,
  k = 20,
  do.scale = TRUE,
  do.center = TRUE,
  fast.pca = TRUE,
  seed = 12345
)

Arguments

X	super-cell transposed gene expression matrix (! where rows represent super-cells and cols represent genes)
genes.use	genes to use for dimensionality reduction
genes.exclude	genes to exclude from dimensionaloty reduction
supercell_size	a vector with supercell sizes (ordered the same way as in X)
k	number of components to compute
do.scale	scale data before PCA
do.center	center data before PCA
fast.pca	whether to run fast PCA (works for datasets with |super-cells| > 50)
seed	a seed to use for set.seed

Value

the same object as prcomp result

SuperCell documentation built on Oct. 25, 2024, 5:07 p.m.