Correlation of Correlations

Description

Given a mergeExpressionSet, this function calculates the study specific correlation matrices, and, for each gene, the correlation of correlations.

Usage

   intCor(x,method= c("pearson", "spearman"),exact,...)

Arguments

Details

Integrative correlation coefficients are calcualted as follows. The first step is to identify the n genes common to all studies. Within each study, we calculate the correlation coefficient between gene g, and every other common gene. This gives a vector of length n-1. For a pair of studies, S1 and S2, we calculate the correlation of correlations for gene g. When there are more than 2 studies under consideration, all pairwise correlation of correlations are calculated and averaged.

Value

The output is an object of class mergeCor.

See Also

mergeCor-class,intcorDens

Examples

if(require(Biobase) & require(MASS)){
  data(mergeData)
  merged  <-mergeExprs(sample1,sample2,sample3)
  corcor  <-intCor(merged,method="spearman")
  
  plot(merged)
  hist(corcor)

  corcor  <-intCor(merged,method="pearson",exact=FALSE)
  corcor  <-intCor(merged[1:2])
  corcor  <-intCor(merged,exact=TRUE)

  vv<-c(1,3)
  corcor1  <-intCor(merged[vv])
  plot(merged,xlab="study A",ylab="study B",main="CORRELATION OF CORRELATION",col=3,pch=4)
  hist(corcor1,xlab="CORRELATION OF CORRELATION")
 }  

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
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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/intCor.Rd_%03d_medium.png", width=480, height=480)
> ### Name: intCor
> ### Title: Correlation of Correlations
> ### Aliases: intCor
> ### Keywords: univar
> 
> ### ** Examples
> 
> 
> if(require(Biobase) & require(MASS)){
+   data(mergeData)
+   merged  <-mergeExprs(sample1,sample2,sample3)
+   corcor  <-intCor(merged,method="spearman")
+   
+   plot(merged)
+   hist(corcor)
+ 
+   corcor  <-intCor(merged,method="pearson",exact=FALSE)
+   corcor  <-intCor(merged[1:2])
+   corcor  <-intCor(merged,exact=TRUE)
+ 
+   vv<-c(1,3)
+   corcor1  <-intCor(merged[vv])
+   plot(merged,xlab="study A",ylab="study B",main="CORRELATION OF CORRELATION",col=3,pch=4)
+   hist(corcor1,xlab="CORRELATION OF CORRELATION")
+  }  
NULL
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>