dyebias.rgplot {dyebias}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

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.

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, submitted

See Also

dyebias.estimate.iGSDBs, dyebias.apply.correction, dyebias.rgplot, dyebias.maplot, dyebias.boxplot, dyebias.trendplot

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)

[Package dyebias version 1.2.1 Index]