Run Independent Component Analysis on gene expression
Source:R/generics.R, R/dimensional_reduction.R
RunICA.RdRun fastica algorithm from the ica package for ICA dimensionality reduction.
For details about stored ICA calculation parameters, see
PrintICAParams.
Usage
RunICA(object, ...)
# Default S3 method
RunICA(
object,
assay = NULL,
nics = 50,
rev.ica = FALSE,
ica.function = "icafast",
verbose = TRUE,
ndims.print = 1:5,
nfeatures.print = 30,
reduction.name = "ica",
reduction.key = "ica_",
seed.use = 42,
...
)
# S3 method for class 'Assay'
RunICA(
object,
assay = NULL,
features = NULL,
nics = 50,
rev.ica = FALSE,
ica.function = "icafast",
verbose = TRUE,
ndims.print = 1:5,
nfeatures.print = 30,
reduction.name = "ica",
reduction.key = "ica_",
seed.use = 42,
...
)
# S3 method for class 'StdAssay'
RunICA(
object,
assay = NULL,
features = NULL,
layer = "scale.data",
nics = 50,
rev.ica = FALSE,
ica.function = "icafast",
verbose = TRUE,
ndims.print = 1:5,
nfeatures.print = 30,
reduction.name = "ica",
reduction.key = "ica_",
seed.use = 42,
...
)
# S3 method for class 'Seurat'
RunICA(
object,
assay = NULL,
features = NULL,
nics = 50,
rev.ica = FALSE,
ica.function = "icafast",
verbose = TRUE,
ndims.print = 1:5,
nfeatures.print = 30,
reduction.name = "ica",
reduction.key = "IC_",
seed.use = 42,
...
)Arguments
- object
Seurat object
- ...
Additional arguments to be passed to fastica
- assay
Name of Assay ICA is being run on
- nics
Number of ICs to compute
- rev.ica
By default, computes the dimensional reduction on the cell x feature matrix. Setting to true will compute it on the transpose (feature x cell matrix).
- ica.function
ICA function from ica package to run (options: icafast, icaimax, icajade)
- verbose
Print the top genes associated with high/low loadings for the ICs
- ndims.print
ICs to print genes for
- nfeatures.print
Number of genes to print for each IC
- reduction.name
dimensional reduction name
- reduction.key
dimensional reduction key, specifies the string before the number for the dimension names.
- seed.use
Set a random seed. Setting NULL will not set a seed.
- features
Features to compute ICA on
- layer
The layer in `assay` to use when running independant component analysis.