# Data-Driven Design of Targeted Gene Panels for Estimating Immunotherapy Biomarkers

## Documentation for package ‘ICBioMark’ version 0.1.4

- DESCRIPTION file.
- Package NEWS.

## Help Pages

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_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_K | Construct Bias Penalisation
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
ICBioMark | ICBioMark: A package for cost-effective design of gene panels to predict exome-wide biomarkers.
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