p0G_Func {GSSE} | R Documentation |
Probability Calculation of Relative's Mutation Status
Description
This function is used to calculate the probability of a relative being a carrier.
Usage
p0G_Func (p, status, relative, model)
Arguments
p |
population frequency of mutation. |
status |
proband's carrier status ( |
relative |
relative's relationship to the proband ( |
model |
assumed genetic model ("dominant" or "recessive"). |
Details
Technical details can be found in Wang et al. (2008).
Value
The function p0G_Func
returns the probability of a relative being a carrier under the given genetic model.
References
Wang, Y., Clark, L. N., Louis, E. D., Mejia-Santana, H., Harris, J., Cote, L. J., ... & Marder, K. (2008). Risk of Parkinson disease in carriers of parkin mutations: estimation using the kin-cohort method. Archives of neurology, 65(4), 467-474.
Wang, Y., Liang, B., Tong, X., Marder, K., Bressman, S., Orr-Urtreger, A., Giladi, N. & Zeng, D. (2015). Efficient estimation of nonparametric genetic risk function with censored data. Biometrika, 102(3), 515-532.
See Also
p0G_data
, Sieve_NPMLE_Switch()
, Sieve_NPMLE_Bootstrap()
, EM_PAVA_Func()
and
Examples
# Example 1 #
data("p0G_data");
attach(p0G_data);
n = dim(p0G_data)[1];
Status = as.numeric( proband_pd == "Yes" );
Relative = rep(1, n) + 1*(relative == "Sibling") + 2*(relative == "Child");
detach(p0G_data);
p0G = rep(0, n);
for(i in 1:n)
{
p0G[i] = p0G_Func(p = 0.02, status = Status[i], relative = Relative[i], model="dominant");
}
data.frame(pd_status = Status, relatives = Relative, prob = p0G);
# Example 2 #
n = 50;
status = sample(x=c(0,1), size = n, replace = TRUE, prob = c(0.6, 0.4) );
relative = sample(x=1:3, size = n, replace = TRUE, prob = c(1/3, 1/3, 1/3) );
p0G = rep(0, n);
for(i in 1:n)
{
p0G[i] = p0G_Func(p = 0.2, status = status[i], relative = relative[i], model="dominant");
}
data.frame(status = status, relative = relative, p0G = p0G);