SharedBasalComponents: Identify shared basal components

In WWXkenmo/ICAnet: What the Package Does (One Line, Title Case)

Identify shared basal components

Description

Identify shared basal components through using whiten matrices derived from latent semantic indexing

Usage

SharedBasalComponents(
  data_list,
  var.names,
  reduct.dim,
  center = TRUE,
  method = "irlba",
  fastICA = FALSE,
  corr = "spearman",
  W.top = 2
)

Arguments

data_list	a list Seurat objects
var.names	the features genes, e.g highly variable features learned from FindVariableFeatures
reduct.dim	the reducted dimensions, default: 30
method	truncted SVD solver. "irlba" or "rARPACK"
fastICA	boolean variable,if TRUE, using FastICA, otherwise use JADE to perform ICA.
corr	the correlation method which determine the correlation between different pair of source components (default: spearman)
W.top	the threshold to determine the activated genes, the genes which has absolute attributes value large than threshold*standard derivation from mean are the activated genes (default: 2.5)

Value

a list object which containing merged seurat object and basal components

Examples

## Not run: 
list <- SharedBasalComponents(PBMC_list,features,30)
objs <- list$mergedObject
basalcomp <- list$basalcomp

## End(Not run)

WWXkenmo/ICAnet documentation built on April 11, 2022, 5:44 a.m.