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Here we apply the penetrance package to simulated families where the data-generating penetrance function is known and based on existing penetrance estimates.
The data-generating distribution of the age-specific penetrances is based on existing penetrance estimates for Colorectal cancer in carriers of any pathogenic variant in MLH1 from the PanelPRO Database.
The families were simulated using the PedUtils Rpackage.
dat <- test_fam2Then we run the estimation using the default settings.
# Set the random seed
set.seed(2024)
# Set the prior
prior_params <- list(
asymptote = list(g1 = 1, g2 = 1),
threshold = list(min = 5, max = 30),
median = list(m1 = 2, m2 = 2),
first_quartile = list(q1 = 6, q2 = 3)
)
# Set the allele frequency for MLH1 based on PanelPRO Database
prevMLH1 <- 0.0004453125
# We use the default baseline (non-carrier) penetrance
print(baseline_data_default)
# We run the estimation procedure with one chain and 20k iterations
out_sim <- penetrance(
pedigree = dat, twins = NULL, n_chains = 1, n_iter_per_chain = 20000,
ncores = 2, baseline_data = baseline_data_default , prev = prevMLH1,
prior_params = prior_params, burn_in = 0.1, median_max = TRUE,
ageImputation = FALSE, removeProband = FALSE
)Lee G, Liang JW, Zhang Q, Huang T, Choirat C, Parmigiani G, Braun D. Multi-syndrome, multi-gene risk modeling for individuals with a family history of cancer with the novel R package PanelPRO. Elife. 2021;10:e68699. doi:10.7554/eLife.6869
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They may not be fully stable and should be used with caution. We make no claims about them.
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