lik.fn: Penetrance Function

In penetrance: Methods for Penetrance Estimation in Family-Based Studies

Penetrance Function

Description

Calculates the penetrance for an individual based on Weibull distribution parameters. This function estimates the probability of developing cancer given the individual's genetic and demographic information.

Usage

lik.fn(
  i,
  data,
  alpha_male,
  alpha_female,
  beta_male,
  beta_female,
  delta_male,
  delta_female,
  gamma_male,
  gamma_female,
  max_age,
  baselineRisk,
  BaselineNC,
  prev
)

Arguments

i	Integer, index of the individual in the data set.
data	Data frame, containing individual demographic and genetic information. Must include columns for 'sex', 'age', 'aff' (affection status), and 'geno' (genotype).
alpha_male	Numeric, Weibull distribution shape parameter for males.
alpha_female	Numeric, Weibull distribution shape parameter for females.
beta_male	Numeric, Weibull distribution scale parameter for males.
beta_female	Numeric, Weibull distribution scale parameter for females.
delta_male	Numeric, shift parameter for the Weibull function for males.
delta_female	Numeric, shift parameter for the Weibull function for females.
gamma_male	Numeric, asymptote parameter for males (only scales the entire distribution).
gamma_female	Numeric, asymptote parameter for females (only scales the entire distribution).
max_age	Integer, maximum age considered in the analysis.
baselineRisk	Numeric matrix, baseline risk for each age by sex. Columns correspond to sex (1 for male, 2 for female) and rows to age.
BaselineNC	Logical, indicates if non-carrier penetrance should be based on SEER data.
prev	Numeric, the carrier prevalence (heterozygote frequency) in the population. This should be approximately 2p where p is the allele frequency when the allele is rare.

Value

Numeric vector, containing penetrance values for unaffected and affected individuals.

penetrance documentation built on Sept. 9, 2026, 1:07 a.m.