pred_refit_range function

Get Refitted Predictive Models for a First-Fit Range of Panels

A function producing a refitted predictive model for each panel produced by usage of the function pred_first_fit(), by repeatedly applying the function pred_refit_panel().

pred_refit_range(
  pred_first = NULL,
  gene_lengths = NULL,
  model = "T",
  biomarker = "TMB",
  marker_mut_types = c("NS", "I"),
  training_data = NULL,
  training_values = NULL,
  mutation_vector = NULL,
  t_s = NULL,
  max_panel_length = NULL
)

Arguments

• pred_first: (list) A first-fit predictive model as produced by pred_first_fit().
• gene_lengths: (dataframe) A dataframe of gene lengths (see example_maf_data$gene_lengths for format).
• model: (character) A choice of "T", "OLM" or "Count" specifying how predictions should be made.
• biomarker: (character) If "TMB" or "TIB", automatically defines marker_mut_types, otherwise this will need to be specified separately.
• marker_mut_types: (character) A vector specifying which mutation types groups determine the biomarker in question.
• training_data: (sparse matrix) Training matrix, as produced by get_mutation_tables() (select train, val or test).
• training_values: (dataframe) Training true values, as produced by get_biomarker_tables() (select train, val or test).
• mutation_vector: (numeric) Optional vector specifying the values of the training matrix (training_data$matrix) in vector rather than matrix form.
• t_s: (numeric) Optional vector specifying the frequencies of different mutation types.
• max_panel_length: (numeric) Upper bound for panels to fit refitted models to. Most useful for "OLM" and "Count" model types.

Returns

A list with three elements:

• fit, a list including a sparse matrix 'beta' giving prediction weights for each first-fit panel (one panel per column).
• panel_genes, a sparse (logical) matrix giving the genes included in prediction for each first-fit panel.
• panel_lengths, a vector giving the length of each first-fit panel.

Examples

example_refit_range <- pred_refit_range(pred_first = example_first_pred_tmb,
  gene_lengths = example_maf_data$gene_lengths)