# Initialize E-gene attachment prior for empirical Bayes

### 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

1 | ```
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

1 2 3 4 5 6 7 | ```
# 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)
``` |