Consensus: Consensus Clustering

In suke18/FEAST: FEAture SelcTion (FEAST) for Single-cell clustering

Description

Consensus Clustering

Usage

Consensus(Y, num_pcs = 10, top_pctg = 0.33, k = 2, thred = 0.9, nProc = 1)

Arguments

Y	A expression matrix. It is recommended to use the raw count matrix. Users can input normalized matrix directly.
num_pcs	The number of top pcs that will be investigated on through consensus clustering.
top_pctg	Top percentage of features for dimension reduction
k	The number of input clusters (best guess).
thred	For the final GMM clustering, the probability of a cell belonging to a certain cluster.
nProc	number of cores for BiocParallel enviroment.

Value

the clustering labels and the featured genes.

Examples

data(Yan)
set.seed(123)
rixs = sample(nrow(Y), 500)
cixs = sample(ncol(Y), 40)
Y = Y[rixs, cixs]
con = Consensus(Y, k=5)

suke18/FEAST documentation built on Sept. 14, 2021, 12:22 a.m.