ICBioMark               ICBioMark: A package for cost-effective design
                        of gene panels to predict exome-wide
                        biomarkers.
ensembl_gene_lengths    Gene Lengths from the Ensembl Database
example_first_pred_tmb
                        First-Fit Predictive Model Fitting on Example
                        Data
example_gen_model       Generative Model from Simulated Data
example_maf_data        Simulated MAF Data
example_predictions     Example Predictions
example_refit_panel     Refitted Predictive Model Fitted on Example
                        Data
example_refit_range     Refitted Predictive Models Fitted on Example
                        Data
example_tables          Mutation Matrices from Simulated Data
example_tib_tables      Tumour Indel Burden of Example Train,
                        Validation and Test Data.
example_tmb_tables      Tumour Mutation Burden of Example Train,
                        Validation and Test Data.
fit_gen_model           Fit Generative Model
fit_gen_model_uninteract
                        Fit Generative Model Without Gene/Variant
                        Type-Specific Interactions
fit_gen_model_unisamp   Fit Generative Model Without Sample-Specific
                        Effects
generate_maf_data       Generate mutation data.
get_K                   Construct Bias Penalisation
get_auprc               AUPRC Metrics for Predictions
get_biomarker_from_maf
                        Produce a Table of Biomarker Values from a MAF
get_biomarker_tables    Get True Biomarker Values on Training,
                        Validation and Test Sets
get_gen_estimates       Investigate Generative Model Comparisons
get_mutation_dictionary
                        Group and Filter Mutation Types
get_mutation_tables     Produce Training, Validation and Test Matrices
get_p                   Construct Optimisation Parameters.
get_panels_from_fit     Extract Panel Details from Group Lasso Fit
get_predictions         Produce Predictions on an Unseen Dataset
get_r_squared           R Squared Metrics for Predictions
get_stats               Metrics for Predictive Performance
get_table_from_maf      Produce a Mutation Matrix from a MAF
nsclc_maf               Non-Small Cell Lung Cancer MAF Data
nsclc_survival          Non-Small Cell Lung Cancer Survival and
                        Clinical Data
pred_first_fit          First-Fit Predicitve Model with Group Lasso
pred_intervals          Produce Error Bounds for Predictions
pred_refit_panel        Refitted Predictive Model for a Given Panel
pred_refit_range        Get Refitted Predictive Models for a First-Fit
                        Range of Panels
vis_model_fit           Visualise Generative Model Fit
