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Last data update: 2014.03.03

R: Normalization applied to ExpressionSets

normalize.ExpressionSet

R Documentation

Normalization applied to ExpressionSets

Description

Allows the user to apply normalization routines to ExpressionSets.

Usage

  normalize.ExpressionSet.quantiles(eset, transfn=c("none","log","antilog"))
  normalize.ExpressionSet.loess(eset, transfn=c("none","log","antilog"),...)
  normalize.ExpressionSet.contrasts(eset, span = 2/3,
      choose.subset=TRUE, subset.size=5000, verbose=TRUE, family="symmetric",
      transfn=c("none","log","antilog")) 
  normalize.ExpressionSet.qspline(eset, transfn=c("none","log","antilog"),...)
  normalize.ExpressionSet.invariantset(eset,prd.td=c(0.003, 0.007),
      verbose=FALSE, transfn=c("none","log","antilog"),
      baseline.type=c("mean","median","pseudo-mean","pseudo-median")) 
  normalize.ExpressionSet.scaling(eset, trim=0.02, baseline=-1,
      transfn=c("none","log","antilog"))

Arguments

`eset`	An `ExpressionSet`
`span`	parameter to be passed to the function `loess`.
`choose.subset`	use a subset of values to establish the normalization relationship
`subset.size`	number to use for subset
`verbose`	verbosity flag
`family`	parameter to be passed to the function `loess`.
`prd.td`	cutoff parameter (details in the bibliographic reference)
`trim`	How much to trim from the top and bottom before computing the mean when using the scaling normalization
`baseline`	Index of array to use as baseline, negative values (-1,-2,-3,-4) control different baseline selection methods
`transfn`	Transform the ExpressionSet before normalizing. Useful when dealing with expression values that are log-scale
`baseline.type`	A method of selecting the baseline array
`...`	Additional parameters that may be passed to the normalization routine

Details

This function carries out normalization of expression values. In general you should either normalize at the probe level or at the expression value level, not both.

Typing normalize.ExpressionSet.methods should give you a list of methods that you may use. note that you can also use the normalize function on ExpressionSets. Use method to select the normalization method.

Value

A normalized ExpressionSet.

Author(s)

Ben Bolstad, bmb@bmbolstad.com

References

Bolstad, BM (2004) Low Level Analysis of High-density Oligonucleotide Array Data: Background, Normalization and Summarization. PhD Dissertation. University of California, Berkeley.

Examples

if (require(affydata)) {
  data(Dilution)
  eset <- rma(Dilution, normalize=FALSE, background=FALSE)
  normalize(eset)
}

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.
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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(affyPLM)
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: affy
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: gcrma
Loading required package: preprocessCore
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/affyPLM/normalize.exprSet.Rd_%03d_medium.png", width=480, height=480)
> ### Name: normalize.ExpressionSet
> ### Title: Normalization applied to ExpressionSets
> ### Aliases: normalize.ExpressionSet.quantiles
> ###   normalize.ExpressionSet.loess normalize.ExpressionSet.contrasts
> ###   normalize.ExpressionSet.qspline normalize.ExpressionSet.invariantset
> ###   normalize.ExpressionSet.scaling normalize.ExpressionSet.methods
> ### Keywords: manip
> 
> ### ** Examples
> 
> if (require(affydata)) {
+   data(Dilution)
+   eset <- rma(Dilution, normalize=FALSE, background=FALSE)
+   normalize(eset)
+ }
Loading required package: affydata
     Package    LibPath                            Item      
[1,] "affydata" "/home/ddbj/local/lib64/R/library" "Dilution"
     Title                        
[1,] "AffyBatch instance Dilution"

Calculating Expression
ExpressionSet (storageMode: lockedEnvironment)
assayData: 12625 features, 4 samples 
  element names: exprs 
protocolData: none
phenoData
  sampleNames: 20A 20B 10A 10B
  varLabels: liver sn19 scanner
  varMetadata: labelDescription
featureData: none
experimentData: use 'experimentData(object)'
Annotation: hgu95av2 
Warning messages:
1: replacing previous import 'AnnotationDbi::tail' by 'utils::tail' when loading 'hgu95av2cdf' 
2: replacing previous import 'AnnotationDbi::head' by 'utils::head' when loading 'hgu95av2cdf' 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>