Perform the assessment via cross-validation of the model inferred by the ASCETIC framework on multiple samples (using mutational trees as inputs) datasets.
asceticPhylogeniesAssessment(inference, niterations = 100, nsampling = 100)Model inferred with ASCETIC using either the function asceticPhylogeniesBootstrap or the function asceticPhylogenies.
Number of cross-validation iterations to be performed for a robust assessment of ASCETIC model. Higher values lead to improved estimates, but require higher computational burden; default value is 100.
Number of re-sampling to be performed for a robust estimation of the agony ranking. Higher values lead to improved estimates, but require higher computational burden; default value is 100.
A list of 3 elements for which the estimate by cross-validation is performed: 1) rankingEstimate, ranking among mutations estimated by agony. Lower rankings correspond to early mutations. This is returned only if nsampling > 0. 2) poset, partially order set among mutations estimated by ASCETIC from the agony ranking. 3) inference, inferred ASCETIC evolutionary model for each selected regularization.
set.seed(12345)
data(datasetExamplePhylogenies)
data(modelsPhylogenies)
resExamplePhylogeniesDatasetBootstrap <- asceticPhylogeniesBootstrap(
dataset = datasetExamplePhylogenies,
models = modelsPhylogenies,
nsampling = 3,
regularization = c("aic","bic"),
command = "hc",
restarts = 0 )
#> 0
#> 0.3333333
#> 0.6666667
#> 1
resExamplePhylogeniesAssessment <- asceticPhylogeniesAssessment(
inference = resExamplePhylogeniesDatasetBootstrap,
niterations = 3,
nsampling = 3)
#> Starting cross-validation...
#> 0
#> 0.3333333
#> 0.6666667
#> 1
#> Warning: variable 2 in the data has levels that are not observed in the data.
#> Warning: variable 13 in the data has levels that are not observed in the data.
#> Warning: variable 14 in the data has levels that are not observed in the data.
#> Warning: variable 2 in the data has levels that are not observed in the data.
#> Warning: variable 13 in the data has levels that are not observed in the data.
#> Warning: variable 14 in the data has levels that are not observed in the data.
#> Cross-validation progress: 0.3333333
#> 0
#> 0.3333333
#> 0.6666667
#> 1
#> Warning: variable 2 in the data has levels that are not observed in the data.
#> Warning: variable 16 in the data has levels that are not observed in the data.
#> Warning: variable 2 in the data has levels that are not observed in the data.
#> Warning: variable 16 in the data has levels that are not observed in the data.
#> Cross-validation progress: 0.6666667
#> 0
#> 0.3333333
#> 0.6666667
#> 1
#> Warning: variable 20 in the data has levels that are not observed in the data.
#> Warning: variable 20 in the data has levels that are not observed in the data.
#> Cross-validation progress: 1