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Last data update: 2014.03.03

R: Multidimensional Scaling Plots

MDSplot

R Documentation

Multidimensional Scaling Plots

Description

Visualization of data similarity using non-metric multidimensional scaling.

Usage

MDSplot(x, mask, flip = integer(0), rotation = 0, cex = 2, col = x$sampleColour, panellabel, pointlabel)

Arguments

`x`	an `ExpressionSet` containing a matrix of expression values with rows representing features and columns samples
`mask`	a logical vector specifying the masking of data points; if missing all points are drawn
`flip`	an integer vector containing indices of columns of the distance matrix whose sign should be flipped
`rotation`	numeric, angle in radians by which the plot should be rotated
`cex`	numeric, the value giving the amount by which text and symbols should be scaled relative to the current setting
`col`	character vector specifing the colors of points
`panellabel`	character, the label of the figure panel
`pointlabel`	character vector containing labels corresponding to samples; if specified labels are drawn instead of points

Value

The result of the function is a plot.

Author(s)

Wolfgang Huber, 2013

Examples

## data preparation
data(x)
y = x[, with(pData(x), Embryonic.day=="E3.25")]

## some helper functions
zero2one = function(x) (x-min(x))/diff(range(x))
rgb2col = function(x) {x=x/255; rgb(x[,1], x[,2], x[,3])}

## define colours for plotting
colours = character(nrow(pData(y)))
colours[y$genotype=="FGF4-KO"] = brewer.pal(10, "Paired")[c(7)]
colours[y$genotype=="WT"] = brewer.pal(12, "Paired")[c(9)]

## select 100 most variable genes for plotting
selMDS = order(rowVars(exprs(y)), decreasing=TRUE)[seq_len(100)]
MDSplot(y[selMDS,], col=colours)

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(Hiiragi2013)
Loading required package: affy
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Loading required package: Biobase
Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Loading required package: boot
Loading required package: clue
Loading required package: cluster
Loading required package: genefilter
Loading required package: geneplotter
Loading required package: lattice

Attaching package: 'lattice'

The following object is masked from 'package:boot':

    melanoma

Loading required package: annotate
Loading required package: AnnotationDbi
Loading required package: stats4
Loading required package: IRanges
Loading required package: S4Vectors

Attaching package: 'S4Vectors'

The following objects are masked from 'package:base':

    colMeans, colSums, expand.grid, rowMeans, rowSums

Loading required package: XML
Loading required package: gplots

Attaching package: 'gplots'

The following object is masked from 'package:IRanges':

    space

The following object is masked from 'package:S4Vectors':

    space

The following object is masked from 'package:stats':

    lowess

Loading required package: gtools

Attaching package: 'gtools'

The following objects are masked from 'package:boot':

    inv.logit, logit

Loading required package: KEGGREST
Loading required package: MASS

Attaching package: 'MASS'

The following object is masked from 'package:AnnotationDbi':

    select

The following object is masked from 'package:genefilter':

    area

Loading required package: mouse4302.db
Loading required package: org.Mm.eg.db


Loading required package: RColorBrewer
Loading required package: xtable
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/Hiiragi2013/MDSplot.Rd_%03d_medium.png", width=480, height=480)
> ### Name: MDSplot
> ### Title: Multidimensional Scaling Plots
> ### Aliases: MDSplot
> 
> ### ** Examples
> 
> ## data preparation
> data(x)
> y = x[, with(pData(x), Embryonic.day=="E3.25")]
> 
> ## some helper functions
> zero2one = function(x) (x-min(x))/diff(range(x))
> rgb2col = function(x) {x=x/255; rgb(x[,1], x[,2], x[,3])}
> 
> ## define colours for plotting
> colours = character(nrow(pData(y)))
> colours[y$genotype=="FGF4-KO"] = brewer.pal(10, "Paired")[c(7)]
> colours[y$genotype=="WT"] = brewer.pal(12, "Paired")[c(9)]
> 
> ## select 100 most variable genes for plotting
> selMDS = order(rowVars(exprs(y)), decreasing=TRUE)[seq_len(100)]
> MDSplot(y[selMDS,], col=colours)
initial  value 23.999806 
iter   5 value 19.519819
iter  10 value 18.348476
final  value 17.655268 
converged
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>