reduce_dims_scExp: Reduce dimensions (PCA, TSNE, UMAP)

In vallotlab/ChromSCape: Analysis of single-cell epigenomics datasets with a Shiny App

Reduce dimensions (PCA, TSNE, UMAP)

Description

Reduce dimensions (PCA, TSNE, UMAP)

Usage

reduce_dims_scExp(
  scExp,
  dimension_reductions = c("PCA", "UMAP"),
  n = 10,
  batch_correction = FALSE,
  batch_list = NULL,
  remove_PC = NULL,
  verbose = TRUE
)

Arguments

scExp	A SingleCellExperiment object.
dimension_reductions	A character vector of methods to apply. (c('PCA','TSNE','UMAP'))
n	Numbers of dimensions to keep for PCA. (50)
batch_correction	Do batch correction ? (FALSE)
batch_list	List of characters. Names are batch names, characters are sample names.
remove_PC	A vector of string indicating which principal components to remove before downstream analysis as probably correlated to library size. Should be under the form : 'Component_1', 'Component_2', ... Recommended when using 'TFIDF' normalization method. (NULL)
verbose	Print messages ?(TRUE)

Value

A SingleCellExperiment object containing feature spaces. See ?reduceDims().

Examples

raw <- create_scDataset_raw()
scExp = create_scExp(raw$mat, raw$annot)
scExp =  normalize_scExp(scExp, "CPM")
scExp = reduce_dims_scExp(scExp,dimension_reductions=c("PCA","UMAP"))

vallotlab/ChromSCape documentation built on Oct. 15, 2023, 1:47 p.m.