# Estimate network between active regulators using Nested Effects Models (NEMs).

### Description

Given a biRte model, this function makes posterior inference about possible upstream-downstream relationships between active regulators. This is done based on observed differential expression of putative target genes. The idea is that regulator A acts upstream of regulator B, if differentially expressed targets of B are a subset of those of A.

### Usage

1 2 | ```
estimateNetwork(model, thresh=0.1, select=c("marginal", "MAP"), method="pairwise",
de.genes, bootstrap=0, typeII=0.1)
``` |

### Arguments

`model` |
biRte model |

`thresh` |
cutoff for marginal posterior probabilities |

`select` |
"marginal": select regulators based on marginal posterior probabilities; "MAP": select regulators based on MAP configuration |

`method` |
algorithm used for NEM based network inference, see |

`de.genes` |
set of differentially expressed genes |

`bootstrap` |
optional: number of bootstrap replicates to draw (non-parameteric bootstrap) |

`typeII` |
assumed type-II error rate |

### Value

nem-model

### Author(s)

Holger Froehlich

### Examples

1 | ```
# see vignette
``` |