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Last data update: 2014.03.03

R: plotmclust

plotmclust

R Documentation

plotmclust

Description

Plot the model-based clustering results

Usage

plotmclust(mclustobj, x = 1, y = 2, MSTorder = NULL, show_tree = T,
  show_cell_names = T, cell_name_size = 3, markerexpr = NULL)

Arguments

`mclustobj`	The exact output of `exprmclust` function.
`x`	The column of data after dimension reduction to be plotted on the horizontal axis.
`y`	The column of data after dimension reduction to be plotted on the vertical axis.
`MSTorder`	The arbitrary order of cluster to be shown on the plot.
`show_tree`	Whether to show the links between cells connected in the minimum spanning tree.
`show_cell_names`	Whether to draw the name of each cell in the plot.
`cell_name_size`	The size of cell name labels if show_cell_names is TRUE.
`markerexpr`	The gene expression used to define the size of nodes.

Details

This function will plot the gene expression data after dimension reduction and show the clustering results.

Value

A ggplot2 object.

Author(s)

Zhicheng Ji, Hongkai Ji <zji4@zji4.edu>

Examples

data(lpsdata)
procdata <- preprocess(lpsdata)
lpsmclust <- exprmclust(procdata)
plotmclust(lpsmclust)

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(TSCAN)
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/TSCAN/plotmclust.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plotmclust
> ### Title: plotmclust
> ### Aliases: plotmclust
> 
> ### ** Examples
> 
> data(lpsdata)
> procdata <- preprocess(lpsdata)
> lpsmclust <- exprmclust(procdata)
> plotmclust(lpsmclust)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>