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

View source: R/mainNetFunction.R

A function that computes the mutual information between all pairs of rows (or
specified ones) of matrix `counts`

using all the 10 different estimation
methods and evalute their performances.

1 2 | ```
mainNetFunction(counts, adjMat, nchips, plotPath = "",
tfList = NULL)
``` |

`counts` |
a numeric matrix (for the reconstruction of gene regulatory networks, genes on rows and samples on columns). |

`adjMat` |
the adjacency matrix that encodes the graph structure that is going to be predicted. |

`nchips` |
the number of cpu's to be used for making the parallel calculation. |

`plotPath` |
the folder in which the plot will be saved. |

`tfList` |
the character vector specifying which genes from the rownames of the |

`miEst` |
a list containing the estimates of all methods. |

`valMet` |
a list contatining the performance indices (i.e. "Recall", "FPR", "Precision", "Accuracy", "Fscore") calculated in all methods and usable for creating curves like ROC and PR. |

`resTable` |
a matrix with the best performces for each method. |

Luciano Garofano [email protected], Stefano Maria Pagnotta, Michele Ceccarelli

Stehman, S.V. (1997). Selecting and interpreting measures of thematic classification
accuracy. *Remote Sensing of Environment* 62 (1): 77-89.

1 2 3 4 5 6 | ```
simData <- simulatedData(p = 5, n = 10, mu = 50, sigma = 0.25,
ppower = 0.73, noise = FALSE)
counts <- simData$counts
adjMat <- simData$adjMat
#netData <- mainNetFunction(counts, adjMat, nchips = 2)
``` |

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