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Last data update: 2014.03.03

R: Produce scatterplots of the hybridization, with strongest dye...

dyebias.rgplot

R Documentation

Produce scatterplots of the hybridization, with strongest dye biases highlighted.

Description

Plots the log_2(R) vs. log_2(G) (or alternatively M vs. A) signal of one slide, highlighting the reporters with the strongest red and green dye bias. Two lines indicate two-fold change. See also Margaritis et al. (2009), Fig. 1

Usage


dyebias.rgplot(data, slide, iGSDBs, dyebias.percentile=5,
               application.subset=TRUE, output=NULL, xlim =
               c(log2(50),log2(50000)), ylim = c(log2(50),log2(50000)),
               xticks = c(100,1000,10000,10000), yticks =
               c(100,1000,10000,10000), pch = 19, cex = 0.3, cex.lab =
               1.4, ...)

dyebias.maplot(data, slide, iGSDBs, dyebias.percentile=5,
               application.subset=TRUE, output=NULL, xlim = c(6,16),
               ylim = c(-2,2), pch = 19, cex = 0.3, cex.lab = 1.4, ...)

Arguments

`data`	The `marrayNorm` object to plot one slide of.
`slide`	The index of the slide to plot; must be > 1, and < `maNsamples(data)`
`iGSDBs`	A data frame with intrinsic gene-specific dye biases, the same as that used in `dyebias.apply.correction`, probably returned by `dyebias.estimate.iGSDBs`; see there for documentation.
`dyebias.percentile`	The percentile of intrinsic gene specific dye biases (iGSDBs) for which to highlight the reporters.
`application.subset`	The set of reporters that was eligible for dye bias correction; same argument as for `dyebias.apply.correction`.
`output`	Specifies the output. If `NULL`, the existing output device is used; if `output` is one of `"X11", "windows", "quartz"`, a new X11 (Unix)/windows (Windows)/quartz (Mac) device is created. If `output` is a string ending in one of `".pdf", ".png", ".eps", ".ps"` is given, a file of that name and type is created and closed afterwards.
`xlim,ylim, xticks, yticks,pch,cex,cex.lab`	Graphical parameters; see `par()`
`...`	Other arguments (such as `main` etc.) are passed on to `plot()`.

Value

None.

Note

The highlighted spots are all spots with an iGSDB that lies in the top- or bottom- dyebias.percentile of iGSDBS. That is, not just the estimator genes are highlighted.

Author(s)

Philip Lijnzaad p.lijnzaad@umcutrecht.nl

References

Margaritis, T., Lijnzaad, P., van Leenen, D., Bouwmeester, D., Kemmeren, P., van Hooff, S.R and Holstege, F.C.P. (2009). Adaptable gene-specific dye bias correction for two-channel DNA microarrays. Molecular Systems Biology, 5:266, 2009. doi: 10.1038/msb.2009.21.

Examples


                                       

  ## show both an RG-plot and an MA-plot of the uncorrected data and the
  ## corrected data next to each other. 

  slide <- 3                               # or any other other, of course

  layout(matrix(1:4, nrow=2,ncol=2, byrow=TRUE))

  dyebias.rgplot(data=data.norm,
                 slide=slide,
                 iGSDBs=iGSDBs.estimated,   # from dyebias.estimate.iGSDBs
                 main=sprintf("RG-plot, uncorrected, slide %d", slide),
                 output=NULL)

  dyebias.rgplot(data=correction$data.corrected,
                 slide=slide,
                 iGSDBs=iGSDBs.estimated,
                 main=sprintf("RG-plot, corrected, slide %d", slide),
                 output=NULL)


  dyebias.maplot(data=data.norm,
                 slide=slide,
                 iGSDBs=iGSDBs.estimated,
                 main=sprintf("MA-plot, uncorrected, slide %d",slide),
                 output=NULL)

  dyebias.maplot(data=correction$data.corrected,
                 slide=slide,
                 iGSDBs=iGSDBs.estimated,
                 main=sprintf("MA-plot, corrected, slide %d",slide),
                 output=NULL)

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.
You are welcome to redistribute it under certain conditions.
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(dyebias)
Loading required package: marray
Loading required package: limma
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 object is masked from 'package:limma':

    plotMA

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")'.

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/dyebias/dyebias.rgplot.Rd_%03d_medium.png", width=480, height=480)
> ### Name: dyebias.rgplot
> ### Title: Produce scatterplots of the hybridization, with strongest dye
> ###   biases highlighted.
> ### Aliases: dyebias.rgplot dyebias.maplot
> ### Keywords: hplot misc
> 
> ### ** Examples
> 
> 
>   ## Don't show: 
>      options(stringsAsFactors = FALSE)
> 
>      library(dyebias)
>      library(dyebiasexamples)
Loading required package: GEOquery
Setting options('download.file.method.GEOquery'='auto')
Setting options('GEOquery.inmemory.gpl'=FALSE)
>      data(data.raw)
>      data(data.norm)
> 
>      ### obtain estimate for the iGSDBs:
>      iGSDBs.estimated <- dyebias.estimate.iGSDBs(data.norm,
+                                               is.balanced=TRUE,
+                                               verbose=FALSE)
> 
> 
>   ### choose the estimators and which spots to correct:
>   estimator.subset <- dyebias.umcu.proper.estimators(maInfo(maGnames(data.norm)))
> 
>   application.subset <- maW(data.norm) == 1 & dyebias.application.subset(data.raw=data.raw, use.background=TRUE)
> 
>   ### do the correction:
>   correction <- dyebias.apply.correction(data.norm=data.norm,
+                                          iGSDBs = iGSDBs.estimated,
+                                          estimator.subset=estimator.subset,
+                                          application.subset = application.subset,
+                                          verbose=FALSE)
> 
>   
> ## End(Don't show)                                     
> 
>   ## show both an RG-plot and an MA-plot of the uncorrected data and the
>   ## corrected data next to each other. 
> 
>   slide <- 3                               # or any other other, of course
> 
>   layout(matrix(1:4, nrow=2,ncol=2, byrow=TRUE))
> 
>   dyebias.rgplot(data=data.norm,
+                  slide=slide,
+                  iGSDBs=iGSDBs.estimated,   # from dyebias.estimate.iGSDBs
+                  main=sprintf("RG-plot, uncorrected, slide %d", slide),
+                  output=NULL)
> 
>   dyebias.rgplot(data=correction$data.corrected,
+                  slide=slide,
+                  iGSDBs=iGSDBs.estimated,
+                  main=sprintf("RG-plot, corrected, slide %d", slide),
+                  output=NULL)
> 
> 
>   dyebias.maplot(data=data.norm,
+                  slide=slide,
+                  iGSDBs=iGSDBs.estimated,
+                  main=sprintf("MA-plot, uncorrected, slide %d",slide),
+                  output=NULL)
> 
>   dyebias.maplot(data=correction$data.corrected,
+                  slide=slide,
+                  iGSDBs=iGSDBs.estimated,
+                  main=sprintf("MA-plot, corrected, slide %d",slide),
+                  output=NULL)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>