pa.calls {panp} | R Documentation

## Presence-Absence Calls from Negative Strand Matching Probesets

### Description

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

### Usage

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

### Arguments

`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.

### Details

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

  ### Value

  `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.

  ### Note

  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.

  ### Author(s)

  Peter Warren

  ### References

  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

  ### Examples

      ## 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

  [Package panp version 1.7.1 Index]