Allows estimating the best cutoff. For a sequence of cutoff, the p value corresponding to each cutoff value of the sequence. Mainly recommended for single time cascade networks. To achieve more sparsity in other settings, please use a fiiting function based on the stability selection or selectboost algorithms.
# S4 method for omics_network
cutoff(Omega, sequence = NULL, x_min = 0)Arguments
- Omega
a omics_network object
- 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
Examples
# \donttest{
data(network)
cutoff(network)
#> [1] "This computation 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 0.078 0.970 0.591 0.050 0.378 0.179 0.054 0.004
#> $p.value
#> [1] 0.000 0.000 0.078 0.970 0.591 0.050 0.378 0.179 0.054 0.004
#>
#> $p.value.inter
#> [1] -0.10420437 0.13779581 0.39526849 0.72296312 0.59703284 0.23771400
#> [7] 0.22354394 0.17858763 0.09799055 -0.01492960
#>
#> $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
# }