dyebias.application.subset {dyebias} | R Documentation

## Return a subset of reporters that can be dye bias-corrected reasonably well

### 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 `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.

### 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)

[Package dyebias version 1.48.0 Index]