RunICA: Run Independent Component Analysis on gene expression

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

Description

Run fastica algorithm from the ica package for ICA dimensionality reduction. For details about stored ICA calculation parameters, see PrintICAParams.

Usage

RunICA(object, ic.genes = NULL, ics.compute = 50, use.imputed = FALSE,
  rev.ica = FALSE, print.results = TRUE, ics.print = 1:5,
  genes.print = 50, ica.function = "icafast", seed.use = 1,
  reduction.name = "ica", reduction.key = "IC", ...)

Arguments

object	Seurat object
ic.genes	Genes to use as input for ICA. Default is [e-mail]
ics.compute	Number of ICs to compute
use.imputed	Run ICA on imputed values (FALSE by default)
rev.ica	By default, computes the dimensional reduction on the cell x gene matrix. Setting to true will compute it on the transpose (gene x cell matrix).
print.results	Print the top genes associated with each dimension
ics.print	ICs to print genes for
genes.print	Number of genes to print for each IC
ica.function	ICA function from ica package to run (options: icafast, icaimax, icajade)
seed.use	Random seed to use for fastica
reduction.name	dimensional reduction name, specifies the position in the object$dr list. ica by default
reduction.key	dimensional reduction key, specifies the string before the number for the dimension names. IC by default
...	Additional arguments to be passed to fastica

Value

Returns Seurat object with an ICA calculation stored in object@dr$ica

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