prior.EgeneAttach.EB: Initialize E-gene attachment prior for empirical Bayes

In nem: (Dynamic) Nested Effects Models and Deterministic Effects Propagation Networks to reconstruct phenotypic hierarchies

Description

This function computes an initial prior for the attachment of E-genes based on observed log-pvalue densities or log-odds ratios. This prior can then be updated within an empirical Bayes procedure (MC.EMiNEM).

Usage

prior.EgeneAttach.EB(ratioMat)

Arguments

ratioMat

data matrix with experiments in the columns (log-odds ratios or log-pvalue densities)

Value

|E-genes| x (|S-genes| + 1) matrix with prior E-gene attachment probabilities. The last column denotes the virtual 'null' S-gene, which is there to filter E-genes that have no obvious attachment to any of the real S-genes.

Author(s)

Theresa Niederberger, Holger Froehlich

References

Niederberger, T.; Etzold, S.; Lidschreiber, M; Maier, K.; Martin, D.; Fr\"ohlich, H.; Cramer, P.; Tresch, A., MC Eminem Maps the Interaction Landscape of the Mediator, PLoS Comp. Biol., 2012, submitted.

See Also

set.default.parameters, nem

Examples

# only for test purposes
   data("BoutrosRNAi2002")
   D <- BoutrosRNAiDens
   control = set.default.parameters(unique(colnames(D)), Pe=prior.EgeneAttach.EB(D), mcmc.nsamples=100, mcmc.nburnin=50, type="CONTmLLBayes")  # these are *not* realistic values
   res <- nem(D,inference="mc.eminem", control=control)        
   if(require(Rgraphviz))    
    plot(res)   

nem documentation built on Oct. 31, 2019, 2:12 a.m.