dyebias.application.subset: Return a subset of reporters that can be dye bias-corrected...

In dyebias: The GASSCO method for correcting for slide-dependent gene-specific dye bias

Description

Convenience function returning a subset of reporters that can be expected to be corrected reasonably well. Often, the logical AND of this set and that of maW(data.norm) == 1.0 is used. The resulting subset is passed as the application.subset-argument to dyebias.apply.correction.

Usage

dyebias.application.subset(data.raw=NULL, min.SNR=1.5,
                           use.background=FALSE, maxA=15)

Arguments

data.raw	A marrayRaw object whose normalized data is to be dye bias-corrected.
min.SNR	The minimum signal to noise ratio to require. It is loosely defined here as the foreground over the background signal. The background signal may not be real; see below.
use.background	Logical indicating whether or not to use the background signals maRb(data.raw) and maGb(data.raw). If the data.raw object does not have them, specify use.background=FALSE. This will use the smallest foreground of all reporters instead of the real backgrounds.
maxA	The maximum signal that is still allowed.

Details

This routine requires an marrayRaw object since only that contains the background intensities. If you only have normalized data, use something like

    bg <- matrix(0.5, nrow=maNspots(data.norm), ncol=maNsamples(data.norm))
    data.raw <- new("marrayRaw", maRf=maR(data.norm), maGf=maG(data.norm),
                                 maRb=bg, maGb=bg, maW=maW(data.norm))
  

Value

A matrix of logicals with the same dimensions as those of maRf{data.raw} is returned.

Author(s)

Philip Lijnzaad [e-mail]

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.

See Also

dyebias.apply.correction

Examples

  ## First load data and estimate the iGSDBs
  ## (see dyebias.estimate.iGSDBs)

                                      

  ### choose the estimators and which spots to correct:
  estimator.subset <- dyebias.umcu.proper.estimators(maInfo(maGnames(data.norm)))

  ### choose which genes to dye bias correct. Typically, this is based
  ### both on flagged spots and intensity
  application.subset <- maW(data.norm) == 1 &
          dyebias.application.subset(data.raw=data.raw, use.background=TRUE)

  summary(application.subset)

dyebias documentation built on Nov. 8, 2020, 5:53 p.m.