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Last data update: 2014.03.03

R: Function to plot correlation of different samples

corPlot

R Documentation

Function to plot correlation of different samples

Description

This function can be used to visualise the (rank) correlation in expression data between different samples or sample groups.

Usage

corPlot(eset, samples = NULL, grouping = NULL, ref = NULL,
   useSmoothScatter = TRUE, ...)

Arguments

`eset`	object of class `ExpressionSet` holding the array data, or a numeric matrix instead
`samples`	which samples' expression shall be correlated to each other; either a numeric vector of sample numbers in the `ExpressionSet` or a character vector that must be contained in the `sampleNames` of the `ExpressionSet`, default `NULL` means take all samples in the `ExpressionSet`
`grouping`	an optional factor vector defining if the correlation should be assessed between groups of samples, rather than individual samples. If two or more samples are assigned into the same group, the mean over these samples' expression values is taken before computing correlation. Default NULL means assess correlation between individual samples only.
`ref`	reference than only applies if argument `grouping` is given; see `relevel`
`useSmoothScatter`	logical; should the function `smoothScatter` be used?
`...`	additional arguments, not used yet

Value

The function only returns NULL (invisible). The function is called for its side-effect producing the pairs plot.

Author(s)

Joern Toedling

Examples

   data(sample.ExpressionSet)
   if (interactive()) 
   corPlot(sample.ExpressionSet,
    grouping=paste(sample.ExpressionSet$sex,
    sample.ExpressionSet$type, sep="."))

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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Platform: x86_64-pc-linux-gnu (64-bit)

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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(Ringo)
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: RColorBrewer
Loading required package: limma

Attaching package: 'limma'

The following object is masked from 'package:BiocGenerics':

    plotMA

Loading required package: Matrix
Loading required package: grid
Loading required package: lattice
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/Ringo/corrPlot.Rd_%03d_medium.png", width=480, height=480)
> ### Name: corPlot
> ### Title: Function to plot correlation of different samples
> ### Aliases: corrPlot corPlot
> ### Keywords: hplot
> 
> ### ** Examples
> 
>    data(sample.ExpressionSet)
> #   if (interactive()) 
>    corPlot(sample.ExpressionSet,
+     grouping=paste(sample.ExpressionSet$sex,
+     sample.ExpressionSet$type, sep="."))
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>