carrierprob {FamEvent} | R Documentation |
Compute mutation carrier probabilities for individuals with missing gentoypes
Description
Computes model- or data-based carrier probabilities for individuals with missing genotypes based on the observed mutation status of family members and the individual's phenotype.
Usage
carrierprob(condition = "geno", method = "data", fit = NULL, data, mode = "dominant",
q = 0.02)
Arguments
condition |
Choice of conditional information to use for computing the carrier probability. Possible choices are |
method |
Choice of methods to calculate the carrier probability. Possible choices are |
fit |
An object of class |
data |
Family data that includes missing genotypes using the same data format generated by the function |
mode |
Choice of modes of inheritance when using |
q |
Frequency of the disease causing allele when using |
Details
When method="model"
along with the choice of condition="geno+pheno"
, the carrier probability for individual i
is calculated by conditioning on her/his observed phenotype and carrier statuses of family members
P(Xi = 1 | Yi , Xo ) =
P(Yi | Xi = 1) * P(Xi = 1 | Xo) /
(P(Yi | Xi = 1) * P(Xi = 1 | Xo) + P(Yi | Xi = 0) * P(Xi = 0 | Xo))
where Xi indicates the unknown carrier status of individual i
and Xo represents the observed carrier statuses in his or her family members; Yi represents the observed phenotype ti, δi of individual i
in terms of age at onset ti and disease status indicator δi with 1 used for affected individuals and 0 for unaffected individuals.
When method="mendelian"
along with the choice of condition="geno"
, the carrier probability is calculated based on Mendelian laws of genetic transmission with a fixed allele frequency.
Value
Returns a data frame with a vector of carrier probabilities called carrp.geno
when condition="geno"
or carrp.pheno
when condtion="geno+pheno"
added after the last column of the family data.
Author(s)
Yun-Hee Choi
See Also
simfam, penmodelEM, plot.simfam, summary.simfam
Examples
# Simulated family data with 30% of members missing their genetic information.
set.seed(4321)
fam <- simfam(N.fam = 100, design = "pop+", base.dist = "Weibull", mrate = 0.3,
base.parms = c(0.01,3), vbeta = c(-1.13, 2.35), agemin = 20)
# EM algorithm for fitting family data with missing genotypes assuming a Weibull
# baseline hazard and dominant mode of Mendelian inheritance for a major gene.
fitEM <- penmodelEM(Surv(time, status) ~ gender + mgene, cluster = "famID", gvar = "mgene",
parms = c(0.01, 3, -1.13, 2.35), data = fam, design = "pop+", base.dist = "Weibull",
method = "mendelian", mode = "dominant")
# Carrier probability obtained by conditioning on the observed genotypes and phenotype,
# assuming a dominant Mendelian mode of inheritance
fam.added <- carrierprob(condition = "geno+pheno", method = "model", fit = fitEM,
data = fam, mode = "dominant", q = 0.02)
# pedigree plot for family 1 displaying carrier probabilities
plot.simfam(fam.added, famid = 1)