dabg.call: Detection Above Background Call
In xps: Processing and Analysis of Affymetrix Oligonucleotide Arrays including Exon Arrays, Whole Genome Arrays and Plate Arrays

Description Usage Arguments Details Value Note Author(s) References See Also Examples

Computes the Detection Above Background Call first implemented for the Exon arrays.

dabg.call(xps.data, filename = character(0), filedir = getwd(),
          alpha1 = 0.04, alpha2 = 0.06,
          option = "transcript", exonlevel = "", xps.scheme = NULL, add.data = TRUE, verbose = TRUE)

xpsDABGCall(object, ...)

`xps.data`	object of class `DataTreeSet`.
`filename`	file name of ROOT data file.
`filedir`	system directory where ROOT data file should be stored.
`alpha1`	a significance threshold in (0,alpha2).
`alpha2`	a significance threshold in (alpha1,0.5).
`option`	option determining the grouping of probes for summarization, one of ‘transcript’, ‘exon’, ‘probeset’; exon arrays only.
`exonlevel`	exon annotation level determining which probes should be used for summarization; exon/genome arrays only.
`xps.scheme`	optional alternative `SchemeTreeSet`.
`add.data`	logical. If `TRUE` call data will be added to slots `data` and `detcall`.
`verbose`	logical, if `TRUE` print status information.
`object`	object of class `DataTreeSet`.
`...`	the arguments described above.

This function generates a detection p-value based on comparing the perfect match probe intensity to the intensity distribution provided by background probes sharing the same GC-content as the PM probe under consideration. For exon/genome arrays special ‘antigenomic’ background probes of defined GC-content are used, while for expression arrays the Mismatch probes will be grouped by their GC-content.

For exon/genome arrays it is necessary to supply option and exonlevel.

Following options are valid for exon arrays only:

`transcript`:	expression levels are computed for transcript clusters, i.e. probe sets containing the same 'transcript_cluster_id'.
`exon`:	expression levels are computed for exon clusters, i.e. probe sets containing the same 'exon_id', where each exon cluster consists of one or more `probeset`s.
`probeset`:	expression levels are computed for individual probe sets, i.e. for each 'probeset_id'.

Following exonlevel annotations are valid for exon arrays:

	`core`:	probesets supported by RefSeq and full-length GenBank transcripts.
	`metacore`:	core meta-probesets.
	`extended`:	probesets with other cDNA support.
	`metaextended`:	extended meta-probesets.
	`full`:	probesets supported by gene predictions only.
	`metafull`:	full meta-probesets.
	`ambiguous`:	ambiguous probesets only.
	`affx`:	standard AFFX controls.
	`all`:	combination of above.

Following exonlevel annotations are valid for whole genome arrays:

	`core`:	probesets with category 'unique' and 'mixed'.
	`metacore`:	probesets with category 'unique' only.
	`affx`:	standard AFFX controls.
	`all`:	combination of above.

Exon levels can also be combined, with following combinations being most useful:

`exonlevel="metacore+affx"`:	core meta-probesets plus AFFX controls
`exonlevel="core+extended"`:	probesets with cDNA support
`exonlevel="core+extended+full"`:	supported plus predicted probesets

Exon level annotations are described in the Affymetrix whitepaper 'exon_probeset_trans_clust_whitepaper.pdf'.

In order to use an alternative SchemeTreeSet set the corresponding SchemeTreeSet xps.scheme.

xpsDABGCall is the DataTreeSet method called by function dabg.call, containing the same parameters.

A CallTreeSet

Yes, it is possible to compute DABG detection call for expression arrays, but it is very slow and thus not recommended.

Christian Stratowa

Affymetrix (2005) Exon Probeset Annotations and Transcript Cluster Groupings, Affymetrix Inc., Santa Clara, CA, exon_probeset_trans_clust_whitepaper.pdf.

mas5.call

## first, load ROOT scheme file and ROOT data file
scheme.test3 <- root.scheme(paste(path.package("xps"),"schemes/SchemeTest3.root",sep="/"))
data.test3 <- root.data(scheme.test3, paste(path.package("xps"),"rootdata/DataTest3_cel.root",sep="/"))

## DABG detection call
call.dabg <- dabg.call(data.test3,"tmp_Test3DABG",verbose=FALSE)

## get data.frames
pval.dabg <- pvalData(call.dabg)
pres.dabg <- presCall(call.dabg)
head(pval.dabg)
head(pres.dabg)

## plot results
if (interactive()) {
callplot(call.dabg)
}

rm(scheme.test3, data.test3)
gc()