pa.calls: Presence-Absence Calls from Negative Strand Matching...
In panp: Presence-Absence Calls from Negative Strand Matching Probesets

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

Function to make gene presence/absence calls based on distance from empirical distribution of chip-specific negative strand matching probesets (NSMP).

1	pa.calls(object, looseCutoff = 0.02, tightCutoff = 0.01, verbose = FALSE)

`object`	an ExpressionSet object (result of running expression-generating function, like expresso(), rma(), mas5(), etc.) Currently, this must be of chip type HGU133A or HGU133 Plus 2.0
`looseCutoff`	the larger P-value cutoff (see details)
`tightCutoff`	the smaller, more strict P-value cutoff
`verbose`	logical. If 'TRUE' detailed progress messages are reported.

The function calculates a matrix of P-values for the expression values in the input ExpressionSet. P-values are calculated based on the empirical survivor function (1-CDF) of the set of negative probesets identified by Affymetrix as negative strand matching probesets (NSMP) with no cross hybridization. These probesets are therefore assumed to show nothing but background/machine noise plus some occasional non-specific binding. The P-value returned for any probeset expression value in ExpressionSet is the value of the NSMP survivor function for that expression level.

Presence/Absence calls are derived by applying the two cutoff values to the matrix of P-values for all genes in the ExpressionSet, as follows:

Present ('P'): P-values <= tightCutoff
Absent ('A'): P-values > looseCutoff
Marginal ('M'): P-values between tightCutoff and looseCutoff

`list`	a new list containing two matrices: Pcalls and Pvals, as follows:
`Pcalls`	a matrix of Presence (P), Marginal (M), Absent (A) indicators
`Pvals`	a matrix of P-values. Each data point is the P-value for the expr at the same x, y coordinates.

NSMP sets have been established for the HGU133A and HGU133-Plus-2.0 chipsets to date. Hence only these two are currently supported by PANP.

Peter Warren

Warren, P., Bienkowska, J., Martini, P., Jackson, J., and Taylor, D., PANP - a New Method of Gene Detection on Oligonucleotide Expression Arrays (2007), in preparation

## Load example ExpressionSet 
data(gcrma.ExpressionSet)

## Generate Pvals and Pcalls matrices from ExpressionSet, using default cutoffs
PA <- pa.calls(gcrma.ExpressionSet)

## to access the Pcalls and Pvals:
myPcalls <- PA$Pcalls
myPvals <-  PA$Pvals

Loading required package: affy
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,
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    IQR, mad, sd, var, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, basename, cbind, colMeans, colSums, colnames,
    dirname, 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,
    rowMeans, rowSums, rownames, sapply, setdiff, sort, table, tapply,
    union, unique, unsplit, which, which.max, which.min

Loading required package: Biobase
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    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Warning message:
In read.dcf(con) :
  URL 'http://bioconductor.org/BiocInstaller.dcf': status was 'Couldn't connect to server'

Processing 3 chips: ###
Processing complete.


Intensities at cutoff P-values of  0.02  and  0.01 :
Array:                                       value at 0.02    value at 0.01 
12_13_02_U133A_Mer_Latin_Square_Expt1_R1.CEL 	 3.81 		 4.1 
12_13_02_U133A_Mer_Latin_Square_Expt10_R1.CEL 	 3.77 		 4.07 
12_13_02_U133A_Mer_Latin_Square_Expt11_R1.CEL 	 3.89 		 4.11 

[NOTE: 'Collapsing to unique x values...' warning messages are benign.]