optimcluster: This function decides the number of optimum cell clusters for...

In sam-uofl/SwarnSeq: Detection of Differentially Expressed Genes from Single Cell RNA-seq Data

Description

This function decides the number of optimum cell clusters for the given experimental scRNA-seq data.

Usage

optimcluster(CountData, n, seed, Threshold, plot = TRUE)

Arguments

CountData	Observed count data matrix for genes, rows represent genes, columns represent cells.
n	Maximum value for number of cell clusters.
seed	value for random cluster generation.
Threshold	Threshold value for deciding the optimum number of cell clusters.
plot	Logical variabe taking value either TRUE or FALSE, default is FALSE.

Value

A list containing the clustering index, delta and the optimum cluster number.

Author(s)

Samarendra Das

Examples

##Load the test count data given for SwarnSeq.
counts <- matrix(rnbinom(2000, size=0.2, mu=3.4), 50)

results <- optimcluster(CountData=counts, n = 10, seed = 108, Threshold = 0.3, plot = FALSE)

sam-uofl/SwarnSeq documentation built on Sept. 6, 2020, 12:09 a.m.