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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