runPhenograph: RphenoGraph clustering

In JhuangLab/CytoTree: A Toolkit for Flow And Mass Cytometry Data

Description

A simple R implementation of the phenograph [PhenoGraph](http://www.cell.com/cell/abstract/S0092-8674(15)00637-6) algorithm, which is a clustering method designed for high-dimensional single-cell data analysis. It works by creating a graph ("network") representing phenotypic similarities between cells by calculating the Jaccard coefficient between nearest-neighbor sets, and then identifying communities using the well known [Louvain method](https://sites.google.com/site/findcommunities/) in this graph.

Usage

runPhenograph(object, knn = 30, scale = FALSE, verbose = FALSE, ...)

Arguments

object	a CYT object.
knn	numeric. Number of nearest neighbours, default is 30.
scale	logical. Whether to scale the expression matrix
verbose	logical. Whether to print calculation progress.
...	Parameters passing to igraph function

Value

A CYT object with cluster

Examples

cyt.file <- system.file("extdata/cyt.rds", package = "CytoTree")
cyt <- readRDS(file = cyt.file)

cyt <- runPhenograph(cyt, knn = 30, verbose = TRUE)

JhuangLab/CytoTree documentation built on Nov. 16, 2020, 7:23 a.m.