Calculate Empirical FDR Break Points

Calculates the stability selection threshold, the mean number of false positive selected features (empirical), and the number of selected features for specified FDR break points. Relies on calc_emp_fdr() to calculate the mean false discovery based on permutations during the stability selection algorithm.

Usage

calc_emp_fdr_breaks(
  x,
  thresh_seq = seq(1, 0.1, by = -0.01),
  fdr_breaks = c(0.5, 1, 2, 3, 5)
)

Arguments

x

A stab_sel class object generated via stability_selection().

thresh_seq

numeric(n). A sequence in [0, 1] specifying the thresholds to evaluate.

fdr_breaks

numeric(n). A vector specifying the desired mean number of empirical false positives at which to calculate various thresholds.

Value

A list consisting of:

n_selected

A vector of the number of features selected at each empirical stability selection threshold

meanFPs

A vector of the mean number of false positive selected features at each empirical stability selection threshold

breaks

A tibble of containing empirical false positive summary statistics at each FDR specified break point

See also

get_stable_features(), stability_selection()

Other empirical FDR: calc_emp_fdr(), plot_emp_fdr()

Author

Stu Field

Examples

# l1-logistic
withr::with_seed(101, {
  n_feat      <- 20
  n_samples   <- 100
  x           <- matrix(rnorm(n_feat * n_samples), n_samples, n_feat)
  colnames(x) <- paste0("feat", "_", head(letters, n_feat))
  y        <- sample(1:2, n_samples, replace = TRUE)
})
stab_sel <- stability_selection(x, y, "l1-logistic", num_iter = 25,
                                num_perms = 25,
                                r_seed = 101, parallel = TRUE)
#> ✓ Using kernel: 'l1-logistic' and 1 core (serial)
calc_emp_fdr_breaks(stab_sel)
#> $fdr_data
#> # A tibble: 91 × 3
#>    MeanFPs n_selected piThresh
#>      <dbl>      <int>    <dbl>
#>  1    0.32          0     1   
#>  2    0.32          0     0.99
#>  3    0.8           0     0.98
#>  4    0.8           0     0.97
#>  5    1.6           0     0.96
#>  6    1.6           0     0.95
#>  7    2.24          2     0.94
#>  8    2.24          2     0.93
#>  9    3.68          3     0.92
#> 10    3.68          3     0.91
#> # ℹ 81 more rows
#> 
#> $breaks
#> # A tibble: 5 × 4
#>   FDR_breaks MeanFPs n_selected piThresh
#>        <dbl>   <dbl>      <int>    <dbl>
#> 1        0.5    0.8           0     0.98
#> 2        1      1.6           0     0.96
#> 3        2      2.24          2     0.94
#> 4        3      3.68          3     0.92
#> 5        5      6.48         11     0.88
#>