runPhenograph {CytoTree} | R Documentation

## RphenoGraph clustering

### 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)

[Package CytoTree version 1.0.3 Index]