Last data update: 2014.03.03

R: Plot of a ExpressionSet object
plot-methodsR Documentation

Plot of a ExpressionSet object

Description

Creating quality control plots of a ExpressionSet object

Usage

## S4 method for signature 'ExpressionSet,missing'
plot(x, what = c("density", "boxplot", "pair", "MAplot", "sampleRelation", "outlier", "cv"), main, ...)

Arguments

x

a ExpressionSet object returned by lumiQ

what

one of the six kinds of QC plots

main

the title of the QC plot

...

additional parameters for the corresponding QC plots

Details

The parameter "what" of plot function controls the type of QC plots, which includes:

  • density: the density plot of the chips, see hist-methods

  • boxplot: box plot of the chip intensities, see boxplot-methods

  • pair: the correlation among chips, plot as a hierarchical tree, see pairs-methods

  • MAplot: the MAplot between chips, see MAplot-methods

  • sampleRelation: plot the sample relations. See plotSampleRelation

  • outlier: detect the outliers based on the sample distance to the center. See detectOutlier

  • cv: the density plot of the coefficients of variance of the chips. See estimateLumiCV

See Also

LumiBatch-class, hist-methods, boxplot-methods, MAplot-methods, pairs-methods, plotSampleRelation, estimateLumiCV, detectOutlier

Examples


## load example data
data(example.lumi)

## Quality control estimation
lumi.Q <- lumiQ(example.lumi)

## summary
summary(lumi.Q)

## plot the density
plot(lumi.Q, what='density')

## plot the pairwise sample correlation
plot(lumi.Q, what='pair')

## plot the pairwise MAplot
plot(lumi.Q, what='MAplot')

## sample relations
plot(lumi.Q, what='sampleRelation', method='mds', color=c('100US', '95US:5P', '100US', '95US:5P'))

## detect outlier based on the distance to the mean profile
plot(lumi.Q, what='outlier')

## Density plot of coefficient of variance
plot(lumi.Q, what='cv')

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(lumi)
Loading required package: Biobase
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

Welcome to Bioconductor

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

Setting options('download.file.method.GEOquery'='auto')
Setting options('GEOquery.inmemory.gpl'=FALSE)
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/lumi/plot-methods.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plot-methods
> ### Title: Plot of a ExpressionSet object
> ### Aliases: plot-methods plot.ExpressionSet plot,ExpressionSet-method
> ###   plot,ExpressionSet,missing-method
> ### Keywords: methods hplot
> 
> ### ** Examples
> 
> 
> ## load example data
> data(example.lumi)
> 
> ## Quality control estimation
> lumi.Q <- lumiQ(example.lumi)
Perform Quality Control assessment of the LumiBatch object ...
> 
> ## summary
> summary(lumi.Q)
Summary of data information:
Illumina Inc. BeadStudio version 1.4.0.1
		Normalization = none
		Array Content = 11188230_100CP_MAGE-ML.XML
		Error Model = none
		DateTime = 2/3/2005 3:21 PM
		Local Settings = en-US
		

Major Operation History:
            submitted            finished
1 2007-04-22 00:08:36 2007-04-22 00:10:36
2 2007-04-22 00:10:36 2007-04-22 00:10:38
3 2007-04-22 00:13:06 2007-04-22 00:13:10
4 2007-04-22 00:59:20 2007-04-22 00:59:36
5 2016-07-06 21:31:10 2016-07-06 21:31:10
                                             command lumiVersion
1           lumiR("../data/Barnes_gene_profile.txt")       1.1.6
2                             lumiQ(x.lumi = x.lumi)       1.1.6
3 addNuId2lumi(x.lumi = x.lumi, lib = "lumiHumanV1")       1.1.6
4            Subsetting 8000 features and 4 samples.       1.1.6
5                       lumiQ(x.lumi = example.lumi)      2.24.0

Object Information:
LumiBatch (storageMode: lockedEnvironment)
assayData: 8000 features, 4 samples 
  element names: beadNum, detection, exprs, se.exprs 
protocolData: none
phenoData
  sampleNames: A01 A02 B01 B02
  varLabels: sampleID label
  varMetadata: labelDescription
featureData
  featureNames: oZsQEQXp9ccVIlwoQo 9qedFRd_5Cul.ueZeQ ...
    33KnLHy.RFaieogAF4 (8000 total)
  fvarLabels: TargetID
  fvarMetadata: labelDescription
experimentData: use 'experimentData(object)'
Annotation: lumiHumanAll.db 
Control Data: Available
QC information: Please run summary(x, 'QC') for details!
> 
> ## plot the density
> plot(lumi.Q, what='density')
> 
> ## plot the pairwise sample correlation
> plot(lumi.Q, what='pair')
> 
> ## plot the pairwise MAplot
> plot(lumi.Q, what='MAplot')
> 
> ## sample relations
> plot(lumi.Q, what='sampleRelation', method='mds', color=c('100US', '95US:5P', '100US', '95US:5P'))
> 
> ## detect outlier based on the distance to the mean profile
> plot(lumi.Q, what='outlier')
> 
> ## Density plot of coefficient of variance
> plot(lumi.Q, what='cv')
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>