plgem.obsStn {plgem}R Documentation

Computation of Observed and Resampled PLGEM-STN statistics

Description

These functions compute the observed and resampled signal to noise ratio (STN) statistic using PLGEM fitting parameters (obtained using the function ‘plgem.fit’) to detect differential expression in a microarray exprSet ‘data’.

Usage

plgem.obsStn(data, plgemFit, baseline.condition = 1, verbose = FALSE)
plgem.resampledStn(data, plgemFit, baseline.condition = 1,
iterations = "automatic", verbose=FALSE)

Arguments

data an object of class ‘exprSet’ with a ‘conditionName’ covariate, see details.
plgemFit list; the output of ‘plgem.fit’.
baseline.condition the condition to be treated as the baseline.
verbose logical; if TRUE, comments are printed out while running.
iterations number of iterations for the resampling step; if "automatic" it is automatically determined.

Details

The exprSet ‘data’ must have at least two conditions; by default the first one is considered the baseline. ‘data’ must have a phenoData slot with a covariate called ‘conditionName’. The values of this covariate must be sample labels, that have to be identical for samples to be treated as replicates.

PLGEM-STN statistic determines the degree of differential expression between a condition and the baseline:

PLGEM-STN = [mean(condition)-mean(baseline)] / [modeledSpread(condition)+modeledSpread(baseline)],

where: ln(modeledSpread) = PLGEMslope * ln(mean) + PLGEMintercept

‘plgem.obsStn’ determines the observed PLGEM-STN values for each probeset of ‘data’. ‘plgem.resampledStn’ determines the resampled PLGEM-STN values for each probeset of ‘data’ using a resampling approach; see References for details. The number of iterations should be correlated with the number of replicates of the condition used for model fitting.

Value

‘plgem.obsStn’ returns a matrix of observed PLGEM-STN. The rownames of the matrix are the ‘data’ probeset ids.
‘plgem.resampledStn’ returns a list with two items:

RESAMPLED.STN matrix of resampled PLGEM-STN whose rownames of the matrix are the ‘data’ probeset ids, and the columns represent the different replication schema of the provided comparisons; see References for details.
REPL.NUMBER the number of replicates found for each experimental condition; see References for details.

Author(s)

Mattia Pelizzola mattia.pelizzola@unimib.it and Norman Pavelka norman.pavelka@unimib.it

References

N. Pavelka et al., BMC Bioinformatics, 2004 Dec 17;5(1):203; http://www.genopolis.it

See Also

plgem.fit,plgem.deg,run.plgem

Examples

data(LPSeset)
LPSfit<-plgem.fit(data = LPSeset, fittingEval = TRUE)
LPSobsStn<-plgem.obsStn(data = LPSeset, plgemFit = LPSfit)
LPSresampledStn<-plgem.resampledStn(data = LPSeset, plgemFit = LPSfit)

[Package plgem version 1.6.0 Index]