Description Usage Arguments Value Author(s) Examples

The function calculates consensus scores for a network, given a list of replicate modules.

1 | ```
consensusScores(modules, network, ro=length(modules)/2)
``` |

`modules` |
Calculated modules from pseudo-replicates of expression values in |

`network` |
Interaction network, which shoupld be scores. In |

`ro` |
Threshold which is subtracted from the scores to obtain positive and negative value. The default value is half of the number of replicates. |

A result list is returned, consisting of:

`N.scores` |
Numerical vector node scores. |

`E.scores` |
Numerical vector edge scores. |

`N.frequencies` |
Numerical vector node frequencies from the replicate modules. |

`E.frequencies` |
Numerical vector edge frequencies from the replicate modules. |

Daniela Beisser

1 2 3 4 5 6 7 8 9 | ```
library(DLBCL)
data(interactome)
network <- interactome
# precomputed Heinz modules from pseudo-replicates
## Not run: lib <- file.path(.path.package("BioNet"), "extdata")
modules <- readHeinzGraph(node.file=file.path(datadir, "ALL_n_resample.txt.0.hnz"), network=network)
cons.scores <- consensusScores(modules, network)
## End(Not run)
``` |

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