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.

1 |

`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 |

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(X_i = 1 | Y_i, X^o ) = \frac{P(Y_i | X_i=1) P(X_i=1|X^o)}{P(Y_i | X_i=1) P(X_i=1|X^o) + P(Y_i| X_i=0) P(X_i=0|X^o)}, *

where *X_i* indicates the unknown carrier status of individual *i* and *X^o* represents the observed carrier statuses in his or her family members; *Y_i* represents the observed phenotype *(t_i, δ_i)* of individual *i* in terms of age at onset *t_i* and disease status indicator *δ_i* with 1 used for affected individuals and 0 for unaffected individuals.

When `method="model"`

along with the choice of `condition="geno"`

, the carrier probability is calculated based on Mendelian laws of genetic transmission with a fixed allele frequency.

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.

Yun-Hee Choi

`simfam, penmodelEM, plot.simfam, summary.simfam`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ```
# Simulated family data with 30% of members missing their genetic information.
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(parms=c(0.01, 3), vbeta=c(-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)
``` |

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