Package: penetrance 0.1.0

Nicolas Kubista

penetrance: Methods for Penetrance Estimation in Family-Based Studies

Implements statistical methods for estimating disease penetrance in family-based studies. Penetrance refers to the probability of disease§ manifestation in individuals carrying specific genetic variants. The package provides tools for age-specific penetrance estimation, handling missing data, and accounting for ascertainment bias in family studies. Cite as: Kubista, N., Braun, D. & Parmigiani, G. (2024) <doi:10.48550/arXiv.2411.18816>.

Authors:Nicolas Kubista [aut, cre], BayesMendel Lab [aut]

penetrance_0.1.0.tar.gz
penetrance_0.1.0.zip(r-4.5)penetrance_0.1.0.zip(r-4.4)penetrance_0.1.0.zip(r-4.3)
penetrance_0.1.0.tgz(r-4.5-any)penetrance_0.1.0.tgz(r-4.4-any)penetrance_0.1.0.tgz(r-4.3-any)
penetrance_0.1.0.tar.gz(r-4.5-noble)penetrance_0.1.0.tar.gz(r-4.4-noble)
penetrance_0.1.0.tgz(r-4.4-emscripten)penetrance_0.1.0.tgz(r-4.3-emscripten)
penetrance.pdf |penetrance.html✨
penetrance/json (API)

# Install 'penetrance' in R:
install.packages('penetrance', repos = c('https://nicokubi.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/nicokubi/penetrance/issues

Pkgdown site:https://nicokubi.github.io

Datasets:

On CRAN:

Conda:

5.41 score 27 exports 11 dependencies

Last updated 16 days agofrom:1045928c2c. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 04 2025
R-4.5-winOKMar 04 2025
R-4.5-macOKMar 04 2025
R-4.5-linuxOKMar 04 2025
R-4.4-winOKMar 04 2025
R-4.4-macOKMar 04 2025
R-4.4-linuxOKMar 04 2025
R-4.3-winOKMar 04 2025
R-4.3-macOKMar 04 2025

Exports:absValuebaseline_data_defaultcalculate_weibull_parameterscalculateBaselinecalculateEmpiricalDensitycalculateNCPencombine_chains_noSexdistribution_data_defaultgenerate_density_plotsgenerate_summarygenerate_summary_noSeximputeAgesimputeAgesInitmakePriorsmhChainmhLogLikelihood_clipppenetranceplot_acfplot_loglikelihoodplot_pdfplot_penetranceplot_traceprintRejectionRatesprior_params_defaultrisk_proportion_defaulttransformDFvalidate_weibull_parameters

Dependencies:clippevaluatehighrkinship2knitrlatticeMASSMatrixquadprogxfunyaml

Using penetrance

BayesMendel Lab

Rendered fromusing_penetrance.Rmdusingknitr::rmarkdownon Mar 04 2025.

Last update: 2025-02-18
Started: 2024-08-07

Simulation study from empirical data with penetrance

BayesMendel Lab

Rendered fromsimulation_study_real.Rmdusingknitr::rmarkdownon Mar 04 2025.

Last update: 2025-02-18
Started: 2024-08-12

Simulation Study with penetrance

BayesMendel Lab

Rendered fromsimulation_study.Rmdusingknitr::rmarkdownon Mar 04 2025.

Last update: 2025-02-18
Started: 2024-08-07

Readme and manuals

Help Manual

Help pageTopics
Function to return absolute valuesabsValue
Apply Burn-Inapply_burn_in
Apply Thinningapply_thinning
Default Baseline Databaseline_data_default
Calculate Weibull Parameterscalculate_weibull_parameters
Calculate Baseline RiskcalculateBaseline
Calculate Empirical Age DensitycalculateEmpiricalDensity
Calculate Age-Specific Non-Carrier PenetrancecalculateNCPen
Combine Chains Function to combine the posterior samples from the multiple chains.combine_chains
Combine Chains for Non-Sex-Specific Estimationcombine_chains_noSex
Default Distribution Datadistribution_data_default
Draw Ages Using the Inverse CDF Method from the baseline datadrawBaseline
Draw Ages Using the Inverse CDF Method from Empirical DensitydrawEmpirical
Generate Posterior Density Plotsgenerate_density_plots
Generate Summarygenerate_summary
Generate Summary for Non-Sex-Specific Estimationgenerate_summary_noSex
Impute Missing Ages in Family-Based DataimputeAges
Initialize Age ImputationimputeAgesInit
Impute Ages for Unaffected IndividualsimputeUnaffectedAges
Likelihood Calculation without Sex Differentiationlik_noSex
Penetrance Functionlik.fn
Make PriorsmakePriors
Execution of a Single Chain in Metropolis-Hastings for Cancer Risk EstimationmhChain
Calculate Log Likelihood using clipp PackagemhLogLikelihood_clipp
Calculate Log Likelihood without Sex DifferentiationmhLogLikelihood_clipp_noSex
Simulated Output Dataout_sim
penetrance: A Package for Penetrance Estimationpenetrance-package penetrance
Plot Autocorrelation for Multiple MCMC Chains (Posterior Samples)plot_acf
Plot Log-Likelihood for Multiple MCMC Chainsplot_loglikelihood
Plot Weibull Probability Density Function with Credible Intervalsplot_pdf
Plot Weibull Distribution with Credible Intervalsplot_penetrance
Plot MCMC Trace Plotsplot_trace
Print MCMC Rejection RatesprintRejectionRates
Default Prior Parametersprior_params_default
Default Risk Proportionsrisk_proportion_default
Processed Family Datasimulated_families
Processed Family Datatest_fam2
Transform Data FrametransformDF
Validate Weibull Parametersvalidate_weibull_parameters