This function computes the joint probabilities of the possible genotypes of
selected family members within each family, as an intermediate calculation
for use in ML_estimates.
genotype_combinations(dat, ncores = 1, verbose = TRUE)A data frame with rows corresponding to people and columns
corresponding to (at least) the following variables, which will be coerced to
character type:
family (family ID), an identifier for each person's family, constant
within families
indiv (individual ID), an identifier for each person, with no duplicates
across the dataset
mother (mother ID), the individual ID of each person's mother, or missing
(NA) for founders
father (father ID), the individual ID of each person's father, or missing
(NA) for founders
typed (epi-genotyped), equal to 1 for people with methylation data and
0 for all others
The number of cores to be used, with ncores = 1 (the
default) corresponding to non-parallel computing. When ncores > 1,
the parallel package is used to parallelize the calculation of the joint
probabilities of the possible genotype combinations.
FALSE if user wants to suppress messages. Default is
TRUE.
A named list, with names equal to the different family IDs and with
each element of the list being a data frame specifying the possible genotypes
of selected family members (those with dat$typed = 1) within each family,
and the joint probability of each genotype combination. For each individual,
the possible genotypes are 0, corresponding to the wildtype, and 1,
for carriers of a rare genetic variant at an autosomal locus. The calculation
makes the same assumptions as in (Joo et al., 2018), including that the
genetic variant is so rare that at most one founder is a carrier.
Currently, there is a maximum of 20 people per family with typed = 1,
due to the need to store all genotype combinations for the typed people.
It is possible to break families with more than 20 typed people into
smaller families, though this is not ideal.
Each family within dat should be a complete pedigree, meaning that each
(non-missing) mother or father ID should correspond to a row, and each person
should either have both parent IDs missing (if a founder) or non-missing
(if a non-founder). No family should contain a pedigree loop, such as those
caused by inbreeding or by two sisters having children with two brothers
from an unrelated family.
Joo JE, Dowty JG, Milne RL, Wong EM, Dugu<U+00E9> PA, English D, Hopper JL, Goldgar DE, Giles GG, Southey MC, kConFab. Heritable DNA methylation marks associated with susceptibility to breast cancer. Nat Commun. 2018 Feb 28;9(1):867. https://doi.org/10.1038/s41467-018-03058-6
# NOT RUN {
# Load family data
data(ped)
# Calculate genotype probabilites
typed_genos <- genotype_combinations(ped)
str(typed_genos)
# }
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