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

View source: R/Ac3net.cutoff.R

`Ac3net.cutoff`

A quick way to get a very rough estimate of the cutoff value for the significants of the input adjacency matrix

1 | ```
Ac3net.cutoff(mim, ratio_ = 0.002, PCmincutoff=0.6, PCmaxcutoff=0.96)
``` |

`mim` |
An adjacency matrix, where the element at row i and column j corresponds to the correlation or mutual information between variables row i and column j. Row and columns of the matrix must have the variable names. |

`ratio_` |
The ratio of all the elements in the input adjacency matrix (even if the matrix is symmetric), which the user considers as significant portion. |

`PCmincutoff` |
The minimum absolute Pearson correlation value ( by default but can be different) where the below of is not considered as significant. |

`PCmaxcutoff` |
The maximum absolute Pearson correlation value ( by default but can be different) where all the above of is considered as significant. |

`Ac3net.cutoff`

takes an adjacency matrix, ratio and minimum absolute Pearson correlation information. Then return a cutoff value that either correspond to the input ratio or the minimum.

`Ac3net.cutoff`

returns a scaler as a very rough estimate of the cutoff value for the significants of the input adjacency matrix.

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`

,

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