as.kfold.posterr — as.kfold.posterr • TRONCO

Returns a dataframe with all the posterior classification error score in a TRONCO model. It is possible to specify a subset of events or models if multiple reconstruction have been performed.

as.kfold.posterr(
  x,
  events = as.events(x),
  models = names(x$model),
  values = FALSE,
  table = FALSE
)

Arguments

x: A TRONCO model.
events: A subset of events as of as.events(x), all by default.
models: A subset of reconstructed models, all by default.
values: If you want to see also the values
table: Keep the original table (defaul false)

Value

All the posterior classification error scores in a TRONCO model

Examples

data(test_model_kfold)
data(test_model)
as.kfold.posterr(test_model_kfold)
#> $capri_bic
#>                                SELECTS                                SELECTED
#> 1                         ins_del TET2            missense_point_mutations KIT
#> 2                        ins_del ASXL1           missense_point_mutations TET2
#> 3      missense_point_mutations SETBP1          nonsense_point_mutations ASXL1
#> 4  missense_point_mutations NRAS_Ex2_3 missense_point_mutations JARID_2_Ex1_18
#> 5  missense_point_mutations NRAS_Ex2_3          missense_point_mutations IRAK4
#> 6        missense_point_mutations EZH2                            ins_del TET2
#> 7        missense_point_mutations EZH2          missense_point_mutations CEBPA
#> 8        missense_point_mutations EZH2          missense_point_mutations ETNK1
#> 9         missense_point_mutations KIT                 nonsense_ins_del RUNX_1
#> 10              nonsense_ins_del CEBPA     missense_point_mutations EED_Ex2_12
#> 11              nonsense_ins_del CEBPA                    nonsense_ins_del WT1
#> 12      nonsense_point_mutations ASXL1     missense_point_mutations CBL_Ex_8_9
#> 13      nonsense_point_mutations ASXL1          missense_point_mutations EPHB3
#>    MEAN.POSTERR  SD.POSTERR
#> 1        0.0475 0.021889876
#> 2        0.0800 0.015811388
#> 3        0.1000 0.000000000
#> 4        0.0525 0.018446620
#> 5        0.0525 0.007905694
#> 6        0.0875 0.021245915
#> 7        0.0250 0.000000000
#> 8        0.0250 0.000000000
#> 9        0.0500 0.000000000
#> 10       0.0475 0.007905694
#> 11       0.0500 0.000000000
#> 12       0.1225 0.007905694
#> 13       0.0325 0.012076147
#> 
#> $capri_aic
#>                                SELECTS                                SELECTED
#> 1                         ins_del TET2     missense_point_mutations CBL_Ex_8_9
#> 2                         ins_del TET2            missense_point_mutations KIT
#> 3                        ins_del ASXL1     missense_point_mutations KRAS_Ex2_3
#> 4                        ins_del ASXL1           missense_point_mutations TET2
#> 5      missense_point_mutations SETBP1           nonsense_point_mutations EZH2
#> 6      missense_point_mutations SETBP1          nonsense_point_mutations ASXL1
#> 7  missense_point_mutations NRAS_Ex2_3 missense_point_mutations JARID_2_Ex1_18
#> 8  missense_point_mutations NRAS_Ex2_3          missense_point_mutations IRAK4
#> 9        missense_point_mutations TET2                  nonsense_ins_del CEBPA
#> 10       missense_point_mutations EZH2                            ins_del TET2
#> 11       missense_point_mutations EZH2          missense_point_mutations CEBPA
#> 12       missense_point_mutations EZH2          missense_point_mutations ETNK1
#> 13      missense_point_mutations CSF3R           missense_point_mutations TET2
#> 14        missense_point_mutations KIT                 nonsense_ins_del RUNX_1
#> 15              nonsense_ins_del CEBPA     missense_point_mutations EED_Ex2_12
#> 16              nonsense_ins_del CEBPA                    nonsense_ins_del WT1
#> 17      nonsense_point_mutations ASXL1     missense_point_mutations CBL_Ex_8_9
#> 18      nonsense_point_mutations ASXL1          missense_point_mutations EPHB3
#> 19                    Pattern XOR_EZH2                           ins_del ASXL1
#> 20                    Pattern OR_CSF3R                  nonsense_ins_del CEBPA
#>    MEAN.POSTERR  SD.POSTERR
#> 1        0.0875 0.017677670
#> 2        0.0475 0.018446620
#> 3        0.0250 0.000000000
#> 4        0.0750 0.000000000
#> 5        0.0250 0.000000000
#> 6        0.1000 0.000000000
#> 7        0.0450 0.010540926
#> 8        0.0475 0.021889876
#> 9        0.0500 0.000000000
#> 10       0.0825 0.016873714
#> 11       0.0250 0.000000000
#> 12       0.0250 0.000000000
#> 13       0.0775 0.007905694
#> 14       0.0500 0.000000000
#> 15       0.0500 0.000000000
#> 16       0.0500 0.000000000
#> 17       0.1250 0.000000000
#> 18       0.0300 0.010540926
#> 19       0.1900 0.033747428
#> 20       0.0500 0.000000000
#> 
as.kfold.posterr(test_model_kfold, events=as.events(test_model)[5:15,])
#> $capri_bic
#>                               SELECTS                                SELECTED
#> 1 missense_point_mutations NRAS_Ex2_3 missense_point_mutations JARID_2_Ex1_18
#> 2       missense_point_mutations EZH2          missense_point_mutations CEBPA
#>   MEAN.POSTERR SD.POSTERR
#> 1       0.0525 0.01844662
#> 2       0.0250 0.00000000
#> 
#> $capri_aic
#>                               SELECTS                                SELECTED
#> 1 missense_point_mutations NRAS_Ex2_3 missense_point_mutations JARID_2_Ex1_18
#> 2       missense_point_mutations EZH2          missense_point_mutations CEBPA
#>   MEAN.POSTERR SD.POSTERR
#> 1        0.045 0.01054093
#> 2        0.025 0.00000000
#>