bumOptim: Fitting a beta-uniform mixture model to p-value distribution

In BioNet: Routines for the functional analysis of biological networks

Description

The function fits a beta-uniform mixture model to a given p-value distribution.

Usage

bumOptim(x, starts=1, labels=NULL)

Arguments

x	Numerical vector of p-values, has to be named with the gene names or the gene names can be given in the labels paramater.
starts	Number of start points for the optimization.
labels	Gene names for the p-values.

Value

List of class fb with the following elements:

lambda	Fitted parameter lambda for the beta-uniform mixture model.
a	Fitted parameter a for the beta-uniform mixture model.
negLL	Negative log-likelihood.
pvalues	P-value vector.

Author(s)

Marcus Dittrich and Daniela Beisser

References

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.

S. Pounds, S.W. Morris (2003) Estimating the occurrence of false positives and false negatives in microarray studies by approximating and partitioning the empirical distribution of p-values. Bioinformatics, 19(10): 1236-1242.

See Also

fitBumModel, plot.bum, hist.bum

Examples

data(pvaluesExample)
pvals <- pvaluesExample[,1]
bum <- bumOptim(x=pvals, starts=10)
bum

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