Description Usage Arguments Details Value Author(s) References See Also Examples

`Ac3net.MTC`

Return adjusted p-values of the adjancency matrix.

1 2 | ```
Ac3net.MTC(data, iterations=10, MTC=TRUE, MTCmethod="BH",
estmethod='pearson')
``` |

`data` |
Data matrix where rows are variables and columns are the samples. Rows must have the variable names |

`iterations` |
Number of iterations to get null distribuiton from multiple shuffling of the data. |

`MTC` |
If TRUE,as the default status, the the returned p-value matrix has the adjusted p-values |

`MTCmethod` |
The Multiple Testing Correction method. BH is default. See R p.adjust function for options. |

`estmethod` |
The default method is 'pearson' assuming that the data was normalized (at least with Log-2). If the data is not normalized, its recomended setting is 'spearman'. |

`Ac3net.MTC`

takes a data matrix and returns the adjusted p-values matrix that correspond to the adjacency matrix of the input data. This way varios p-values can be tried to get different cutoff values without re-calculating the p-values.

`Ac3net.MTC`

returns a default adjusted p-values matrix that corresponds to the input adjacency matrix. If MTC is set to FALSE then it returns raw p-values.

Gokmen Altay

G. Altay,"Directed Conservative Causal Core Gene Networks", bioRxiv, 2018. G. Altay, F. Emmert-Streib, "Inferring the conservative causal core of gene regulatory networks", BMC Systems Biology (2010) 4:132.

`Ac3net.maxmim`

, `Ac3net.commonlinks`

,

1 2 3 | ```
#data(expdata)
#mim.pvals <- Ac3net.MTC(data = expdata, iterations=10,
# MTC=TRUE, MTCmethod="BH", estmethod='pearson')
``` |

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