Class mergeExpressionSet, a class for merged microarray data, and methods for processing them

Description

This is class representation for merged Microarray Data.

Details

The mergeExpressionSet class is conceived as an extension of the ExpressionSet class provided in Biobase for the storage of expression array data. A mergeExpressionSet object is primarily a list of ExpressionSet objects, along with an incidence matrix indicating which genes appear in which studies. A mergeExpressionSet object with a single study reverts to the ExpressionSet class. A number of accessor functions are defiined for this class, as well as a few convenient analysis and plotting functions.

Slots

We assume there are K studies, representing a total of M unique genes.

data

A list of ExpressionSet objects.

geneStudy

Binary incidence matrix with M rows and K columns. Each column represents a study, and each row represents a gene. If study "s" contains gene "g", then geneStudy[g,s]=1, otherwise geneStudy[g,s]=0.

notes

Object of class "character" This slot is available for storage of descriptive information.

Methods

Derived from ExpressionSet:

exprs(mergeExpressionSet)

An accessor function for the data slot.

exprs<- (mergeExpressionSet)

A replace function for the data slot

notes (mergeExpressionSet)

An accessor function for the notes slot.

notes<- (mergeExpressionSet)

A replace function for the notes slot.

geneNames (mergeExpressionSet)

Accessor function for union of gene ids in all studies.

geneNames<- (mergeExpressionSet)

A replace function for gene ids.

Class-specific methods:

geneStudy (mergeExpressionSet)

Accessor function for the geneStudy slot.

phenoData (mergeExpressionSet)

Accessor function for phenodata in ExpressionSet's. Returns a list, one phenodata matrix per study.

phenoData<- (mergeExpressionSet)

A replace function for phenodata in ExpressionSet's. Returns a list, one phenodata matrix per study.

intersection (mergeExpressionSet)

Represent data for genes common to all studies as a single ExpressionSet object.

modelOutcome (mergeExpressionSet)

Calculate regression coefficients for each study/gene.

intCor (mergeExpressionSet)

Calculate the integrative correlation coefficients for mergeExpressionSet data.

intcorDens (mergeExpressionSet)

Plot the distribution of the integrative correlation coefficients and the null distribution obtained by permutation here we use the approximate method to calculate the integrative correlation.

Standard generic methods:

length (mergeExpressionSet)

Function returning the number of studies in the mergeExpressionSet.

names (mergeExpressionSet)

Function returning study names.

names<- (mergeExpressionSet)

A replace function for study names.

[ (mergeExpressionSet)

A subset operator. Returns a mergeExpressionSet containing a subset of the studies. A mergeExpressionSet with only one study is returned as a single ExpressionSet.

summary (mergeExpressionSet)

Obtain the basic information for 'mergeExpressionSet'.

plot (mergeExpressionSet)

Draw scatterplots to compare integrative correlations for genes, here we use the approximate method to calculate the integrative correlation.

See Also

mergeExprs, intCor, modelOutcome, intcorDens, ExpressionSet

Examples

  if(require(Biobase) & require(MASS)){
  data(mergeData)
  merged  <-mergeExprs(sample1,sample2,sample3)

  merged[1:2]
  i<-c(1,3)
  merged[i]

  exprs(merged)

  names(merged)<-c("study1","study2","study3")

  length(merged)

  summary(merged)

  plot(merged)

  plot(merged[1:2])

  intcorDens(merged)

  inter  <- intersection(merged)
  }

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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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(MergeMaid)
Loading required package: survival
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")'.

Loading required package: MASS
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/MergeMaid/class.mergeExpressionSet.Rd_%03d_medium.png", width=480, height=480)
> ### Name: mergeExpressionSet
> ### Title: Class mergeExpressionSet, a class for merged microarray data,
> ###   and methods for processing them
> ### Aliases: mergeExpressionSet-class mergeExpressionSet geneNames
> ###   geneNames<- geneStudy geneStudy<- subsetmES
> ###   geneStudy,mergeExpressionSet-method names,mergeExpressionSet-method
> ###   length,mergeExpressionSet-method summary,mergeExpressionSet-method
> ###   show,mergeExpressionSet-method exprs<-,mergeExpressionSet,ANY-method
> ###   exprs,mergeExpressionSet-method geneNames<-,mergeExpressionSet-method
> ###   geneNames,mergeExpressionSet-method
> ###   notes<-,mergeExpressionSet,ANY-method notes,mergeExpressionSet-method
> ###   phenoData<-,mergeExpressionSet,ANY-method
> ###   phenoData,mergeExpressionSet-method names<-,mergeExpressionSet-method
> ###   geneStudy<-,mergeExpressionSet-method [,mergeExpressionSet-method
> ###   plot,mergeExpressionSet-method intcorDens,mergeExpressionSet-method
> ###   intCor,mergeExpressionSet-method
> ###   intersection,mergeExpressionSet-method
> ###   modelOutcome,mergeExpressionSet-method isna maxintcor
> ### Keywords: classes
> 
> ### ** Examples
> 
>   if(require(Biobase) & require(MASS)){
+   data(mergeData)
+   merged  <-mergeExprs(sample1,sample2,sample3)
+ 
+   merged[1:2]
+   i<-c(1,3)
+   merged[i]
+ 
+   exprs(merged)
+ 
+   names(merged)<-c("study1","study2","study3")
+ 
+   length(merged)
+ 
+   summary(merged)
+ 
+   plot(merged)
+ 
+   plot(merged[1:2])
+ 
+   intcorDens(merged)
+ 
+   inter  <- intersection(merged)
+   }
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>