Main function, see P. Zoppoli, S. Morganella, M. Ceccarelli. TimeDelay-ARACNE: Reverse engineering of gene networks from time-course data by an information theoretic approach. BMC Bioinformatics 2010, 11:154.

1 |

`eSet` |
eSet is the ExpressionSet object |

`N` |
N is respectively the number of bins in percentile normalization or in rank normalization |

`delta` |
delta is the maximum time delay allowed to infer connections |

`likehood` |
likehood is the fold change used as threshold to state the initial change expression (IcE) |

`norm` |
if you want column percentile normalization put norm == 1; if you want Rank normalization put norm == 2; |

`logarithm` |
if z is log put logarithm == 0; |

`thresh` |
the Influence threshold. if you have a threshold and a SD put them here in this format: c(thresh,SD) if you don't have threshold put 0 in thresh; |

`ksd` |
ksd is the standard deviation multiplier; |

`tolerance` |
tolerance is the DPI tolerance; 0 means no tolerance 1 means no DPI 0.15 is the default ARACNE tolerance as it is for TDARACNE |

`plot` |
plot must be TRUE to obtain automatically the graph |

`dot` |
dot must be TRUE to obtain a .dot file |

`name` |
name must be written with quotation marks(like this:'examplename') and is the name of the .dot file produced; |

`adj` |
adj must be TRUE to obtain an adjacent matrix |

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | ```
## take paper data
library(TDARACNE)
data(dataIRMAon)
data(threshIRMAon)
## main function; in output gives to you and adj matrix and a .dot file
# eSet is the ExpressionSet object
# N is respectively the number of bins in percentile normalization or in rank normalization
# delta is the maximum time delay allowed to infer connections
# likehood is the fold change used as threshold to state the initial change expression (IcE)
# if you want column percentile normalization put norm == 1;
# if you want Rank normalization put norm == 2;
# if z is log put logarithm == 0;
# if you don't have threshold put 0 in thresh;
# ksd is the standard deviation multiplier;
# tolerance is the DPI tolerance;
# plot must be TRUE to obtain automatically the graph
# dot must be TRUE to obtain a .dot file
# name must be written with quotation marks(like this:'examplename') and is the name of the .dot file produced;
# adj must be TRUE to obtain an adjacent matrix
TDARACNE(dataIRMAon,11,"netIRMAon",delta=3,likehood=1.2,norm=2,logarithm=1,thresh=threshIRMAon,ksd=0,tolerance=0.15);
``` |

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