Merge gene expression data sets

Description

Merges gene expression data from different studies.

Usage

   mergeExprs(...)

Arguments

Details

The mergeExpressionSet object is the standard input for all functions in the MergeMaid package. Use the mergeExprs function when creating mergeExpressionSet objects to ensure that all necessary information is available for further analysis.

Value

The output is a mergeExpressionSet.

See Also

mergeExpressionSet-class

Examples

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

  rr<-rnorm(200*22,0,1)
  mm<-matrix(rr,200,22)
  rownames(mm)<-sample2[[3]]
  merge.m<-mergeExprs(sample1,mm,sample2)
  intcor.m<-intCor(merge.m)
  plot(merge.m)

  rr<-rnorm(200*50,0,1)
  mm2<-matrix(rr,200,50)
  ph.ll<-as.data.frame(rbinom(50,1,.5))
  ll<-list(mm2,ph.ll,sample2[[3]],"list 2")
  merge.t<-mergeExprs(sample1,mm,sample2,ll)
  intcor.t<-intCor(merge.t)
  plot(merge.t)

  merge.a<-mergeExprs(sample3,merge.m,ll)
  inter<-intersection(merge.a)
  summary(merge.a)
  }

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)

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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.
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> 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/mergeExprs.Rd_%03d_medium.png", width=480, height=480)
> ### Name: mergeExprs
> ### Title: Merge gene expression data sets
> ### Aliases: mergeExprs AverageDuplicates check mergeget
> ### Keywords: manip
> 
> ### ** Examples
> 
>   if(require(Biobase) & require(MASS)){
+   data(mergeData)
+   merged  <-mergeExprs(sample1,sample2,sample3)
+ 
+   rr<-rnorm(200*22,0,1)
+   mm<-matrix(rr,200,22)
+   rownames(mm)<-sample2[[3]]
+   merge.m<-mergeExprs(sample1,mm,sample2)
+   intcor.m<-intCor(merge.m)
+   plot(merge.m)
+ 
+   rr<-rnorm(200*50,0,1)
+   mm2<-matrix(rr,200,50)
+   ph.ll<-as.data.frame(rbinom(50,1,.5))
+   ll<-list(mm2,ph.ll,sample2[[3]],"list 2")
+   merge.t<-mergeExprs(sample1,mm,sample2,ll)
+   intcor.t<-intCor(merge.t)
+   plot(merge.t)
+ 
+   merge.a<-mergeExprs(sample3,merge.m,ll)
+   inter<-intersection(merge.a)
+   summary(merge.a)
+   }
$`Number of Genes in Each Study`
     [,1]      [,2]      [,3]  [,4]      [,5] 
[1,] "sample3" "sample1" "mm"  "sample2" "ll" 
[2,] "500"     "100"     "200" "200"     "200"

$`Number of Samples in Each Study`
     [,1]      [,2]      [,3] [,4]      [,5]
[1,] "sample3" "sample1" "mm" "sample2" "ll"
[2,] "70"      "100"     "22" "50"      "50"

$Notes
[1] "study 1" "study 2" "study 3" "study 4" "study 5"

> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>