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.

Usage

# S4 method for class 'network'
cutoff(Omega, sequence = NULL, x_min = 0)

Arguments

Omega

a network object

sequence

(optional) a vector corresponding to the sequence of cutoffs that will be tested.

x_min

(optional) 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.

Author

Nicolas Jung, Frédéric Bertrand , Myriam Maumy-Bertrand.

Examples

# \donttest{
  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 0.001 0.127 0.122 0.089 0.566 0.867 0.671 0.595 0.332

#> $p.value
#>  [1] 0.000 0.001 0.127 0.122 0.089 0.566 0.867 0.671 0.595 0.332
#> 
#> $p.value.inter
#>  [1] -0.001490825  0.025014232  0.057341190  0.088355340  0.183669112
#>  [6]  0.537769423  0.794451285  0.768411316  0.611308228  0.312285009
#> 
#> $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
# }