Package index • penetrance

All functions

ALL_GENE_VARIANT_TYPES: Mapping of genes to supported variants

CANCER_NAME_MAP: Mapping of short and long cancer names

CANCER_TYPES: Currently supported cancer types

GENE_TYPES: Currently supported gene types

apply_burn_in(): Apply Burn-In

apply_thinning(): Apply Thinning

baseline_data_default: Default Baseline Data

calcPedDegree(): Calculate Degree of Relationship in Pedigree

calculateBaseline(): Calculate Baseline Risk

calculateEmpiricalDensity(): Calculate Empirical Density for Non-Affected Individuals

calculateNCPen(): Calculate Age-Specific Non-Carrier Penetrance

calculate_lifetime_risk(): Calculate Lifetime Risk of Cancer

calculate_weibull_parameters(): Calculate Weibull Parameters

combine_chains(): Combine Chains Function to combine the posterior samples from the multiple chains.

combine_chains_noSex(): Combine Chains for Non-Sex-Specific Estimation

distribution_data_default: Default Distribution Data

drawBaseline(): Draw Ages Using the Inverse CDF Method from the baseline data

drawEmpirical(): Draw Ages Using the Inverse CDF Method from Empirical Density

generate_density_plots(): Generate Posterior Density Plots

generate_summary(): Generate Summary

generate_summary_noSex(): Generate Summary

imputeAges(): Impute Ages Based on Affection Status and Sex

imputeAgesInit(): Initialize Ages Using a Uniform Distribution

lik.fn(): Penetrance Function

lik_noSex(): Likelihood Calculation without Sex Differentiation

makePriors(): Make Priors

mhChain(): Execution of a Single Chain in Metropolis-Hastings for Cancer Risk Estimation with Sex Differentiation

mhChain_noSex(): Execution of a Single Chain in Metropolis-Hastings for Cancer Risk Estimation without Sex Differentiation

mhLogLikelihood_clipp(): Calculate Log Likelihood using clipp Package

mhLogLikelihood_clipp_noSex(): Calculate Log Likelihood without Sex Differentiation

out_sim: Simulated Output Data

penetrance(): Bayesian Inference using Independent Metropolis-Hastings for Penetrance Estimation

plot_pdf(): Plot Weibull Probability Density Function with Credible Intervals

plot_penetrance(): Plot Weibull Distribution with Credible Intervals

plot_trace(): Plot Trace

printRejectionRates(): Print Rejection Rates

prior_params_default: Default Parameter Settings for Prior Distributions

risk_proportion_default: Default Risk Proportion Data

test_fam1: Processed Family Data

test_fam2: Processed Family Data

transformDF(): Transform Data Frame

validate_weibull_parameters(): Validate Weibull Parameters