simulateData: Simulate expression data.
In birte: Bayesian Inference of Regulatory Influence on Expression (biRte)

Description Usage Arguments Details Value Author(s) Examples

The function draws expression data from a multivariate normal distribution with block structured co-variance matrix. First, data is drawn for a control condition (no active regulators). Then data is generated for the situation that a certain fraction of regulators is turned 'on' (treatment condition). Regulator activity states are sampled from a Bernoulli distribution.

1 2	simulateData(affinities, nrep = 5, miRNAExpressions = TRUE, fn.targets = 0.1, fp.targets = 0.2, exp.nTF = 5, exp.nmiR = 5, exp.interact = 5)

`affinities`	regulator-target gene network (see `humanNetworkSimul`)
`nrep`	number of replicates per condition
`miRNAExpressions`	Should miRNA expression data be simulated?
`fn.targets`	fraction of false negative target predictions (i.e. missing edges per regulator in the bipartite regulator-gene graph)
`fp.targets`	fraction of false positive target predictions
`exp.nTF`	expected number of active TFs
`exp.nmiR`	expected number of active miRNAs
`exp.interact`	expected number of active interaction terms

If active interaction terms should be simulated, a set of possible interaction terms has to be defined in affinities$other.

`dat.mRNA`	mRNA data – active regulators are expected to induce a log FC of 1
`dat.miRNA`	miRNA data – active miRNAs are expected to show a log FC of 1
`dat.TF`	TF expression data – active miRNAs are expected to show a log FC of 0.5
`miRNAstates`	simulated miRNA activities in treatment condition
`TFstates`	simulated TF activities in treatment condition
`inter.states`	simulated regulator interaction activities in treatment condition