Decomposition tables of the data-adaptive parameter after data-mining

Customized informative tables for examining data-adaptive statistics.

get_composition(object, type = "small")

Arguments

object	(data_adapt) - object of class data_adapt as returned by adaptest
type	(character) - 'small' or 'big'. 'small' mode returns composition of data-adaptive parameters after multiple testing stage. 'big' mode returns composition of data-adaptive parameters before multiple testing stage.

Value

(numeric matrix) containing what fraction of the data-adaptive parameter comes from which biomarker in the original dataset.

Examples

set.seed(1234)
data(simpleArray)
simulated_array <- simulated_array
simulated_treatment <- simulated_treatment

adaptest_out <- adaptest(Y = simulated_array,
                         A = simulated_treatment,
                         W = NULL,
                         n_top = 5,
                         n_fold = 3,
                         learning_library = 'SL.glm',
                         parameter_wrapper = adaptest::rank_DE,
                         absolute = FALSE,
                         negative = FALSE)
get_composition(adaptest_out, type = 'small')
#> [[1]]
#>           3         5        10       505         1       519
#> 1 0.3333333 0.3333333 0.3333333 0.0000000 0.0000000 0.0000000
#> 4 0.3333333 0.3333333 0.0000000 0.3333333 0.0000000 0.0000000
#> 5 0.3333333 0.0000000 0.0000000 0.0000000 0.3333333 0.3333333
#> 
#> [[2]]
#>           3         5        10       505         1       519    q-values
#> 1 0.3333333 0.3333333 0.3333333 0.0000000 0.0000000 0.0000000 0.033311197
#> 4 0.3333333 0.3333333 0.0000000 0.3333333 0.0000000 0.0000000 0.005005752
#> 5 0.3333333 0.0000000 0.0000000 0.0000000 0.3333333 0.3333333 0.005005752
#>