Choose the best cutoff

Allows estimating the best cutoff, in function of the scale-freeness of the network. For a sequence of cutoff, the corresponding p-value is then calculated.

cutoff(Omega,...)

Arguments

Omega	a network object
...	Optional arguments: sequence a vector corresponding to the sequence of cutoffs that will be tested. x_min an integer ; only values over x_min are further retained for performing the test.

Value

A list containing two objects :

p.value

the p values corresponding to the sequence of cutoff

p.value.inter

the smoothed p value vector, using the loess function

References

Jung, N., Bertrand, F., Bahram, S., Vallat, L., and Maumy-Bertrand, M. (2014). Cascade: a R-package to study, predict and simulate the diffusion of a signal through a temporal gene network. Bioinformatics, btt705.

Vallat, L., Kemper, C. A., Jung, N., Maumy-Bertrand, M., Bertrand, F., Meyer, N., ... & Bahram, S. (2013). Reverse-engineering the genetic circuitry of a cancer cell with predicted intervention in chronic lymphocytic leukemia. Proceedings of the National Academy of Sciences, 110(2), 459-464.

Examples

        data(network)
        cutoff(network)
#> [1] "This calculation may be long"
#> [1] "1/10"
#> [1] "2/10"
#> [1] "3/10"
#> [1] "4/10"
#> [1] "5/10"
#> [1] "6/10"
#> [1] "7/10"
#> [1] "8/10"
#> [1] "9/10"
#> [1] "10/10"
#>  [1] 0.000 0.000 0.586 0.280 0.296 0.167 0.007 0.380 0.361 0.115
#> $p.value
#>  [1] 0.000 0.000 0.586 0.280 0.296 0.167 0.007 0.380 0.361 0.115
#> 
#> $p.value.inter
#>  [1] -0.06406097  0.20282417  0.35238047  0.41001534  0.25106311  0.13219518
#>  [7]  0.12216528  0.25027490  0.25857893  0.17835107
#> 
#> $sequence
#>  [1] 0.00000000 0.04444444 0.08888889 0.13333333 0.17777778 0.22222222
#>  [7] 0.26666667 0.31111111 0.35555556 0.40000000
#> 
	#See vignette for more details