scoreFunction: Scoring function for p-values

In BioNet: Routines for the functional analysis of biological networks

Description

The function calculates a score for each gene with a given FDR from the fitted beta-uniform mixture model.

Usage

scoreFunction(fb, fdr=0.01)

Arguments

fb	Model from the beta-uniform mixture fitting.
fdr	Numeric constant, from the false discovery rate a p-value threshold is calculated. P-values below this threshold are considered to be significant and will score positively, p-values a bove the threshold are supposed to arise from the null model. The FDR can be used to control the size of the maximum scoring subnetwork, by zooming in and out in the same region.

Value

Score vector for the given p-values.

Author(s)

Marcus Dittrich and Daniela Beisser

References

For details on the score calculation see: M. T. Dittrich, G. W. Klau, A. Rosenwald, T. Dandekar, T. Mueller (2008) Identifying functional modules in protein-protein interaction networks: an integrated exact approach. (ISMB2008) Bioinformatics, 24: 13. i223-i231 Jul.

Examples

data(pvaluesExample)
pvals <- pvaluesExample[,1]
bum.mle <- fitBumModel(pvals, plot=FALSE)
scores <- scoreFunction(fdr=0.1, fb=bum.mle)
scores

BioNet documentation built on Nov. 8, 2020, 5:48 p.m.