sc_clustering.sc3: Perform Single Cell data clustering using SC3 clustering...

In pengminshi/MRtree: Multi-resolution Reconciled Tree

Perform Single Cell data clustering using SC3 clustering pipeline

Description

Perform Single Cell data clustering using SC3 clustering pipeline

Usage

sc_clustering.sc3(
  exprs,
  Ks,
  type = c("counts", "normcounts"),
  colData = NULL,
  rowData = NULL,
  estimate.k = FALSE,
  scale.factor = 10000,
  build.hierarchical.tree = FALSE,
  ...
)

Arguments

exprs	n.genes-by-n.cells expression matrix
Ks	vector of resolution, number of clusters
type	string, type of the expression matrix, choices are 'counts', 'normcounts' and 'logcounts', and default by 'counts'
colData	a dataframe containing cell informations
rowData	a dataframe containing gene informations
estimate.k	boolean, whether to estimate optimal number of clusters by sc3
scale.factor	scalar sets the scale factor for cell-level normalization
build.hierarchical.tree	boolean, whether to obtain HAC results using SC3
...	other parameters input to sc3 function

Value

a list containing

sce

an SingleCellExperiment object containing all the clustering results

hc.tree

hclust object resulted from hierarchical agglomerative clustering using obtained by SC3

pengminshi/MRtree documentation built on March 6, 2023, 4:20 p.m.