For a chosen individual within a specified family, calculate the person's conditional genotype probabilities, given the family's phenotypes and relationship structure
genotype_probabilities(target, fam, geno_freq, trans, penet, monozyg = NULL)A vector of length length(geno_freq), whose jth element is
the conditional probability that the target person has genotype j,
given the family's relationship structure and phenotypes. A vector of NAs
will be returned if a row of penet consists entirely of zeroes or if
the pedigree is impossible for any other reason
(after restricting fam and penet to the connected component of
the pedigree containing target).
The individual identifier (an element of fam$indiv)
of the person in the pedigree fam whose genotype probabilities are being
sought.
A data frame specifying the family's relationship structure,
with rows corresponding to people and columns
corresponding to the following variables (other variables can be included
but will be ignored), which will be coerced to character type:
indiv, an identifier for each individual person, with no duplicates
in fam.
mother, the individual identifier of each person's mother, or missing
(NA) for founders.
father, the individual identifier of each person's father, or missing
(NA) for founders.
A vector of strictly positive numbers that sum to 1.
If the possible genotypes of the underlying genetic model are
1:length(geno_freq) then geno_freq[j] is interpreted as the population
frequency of genotype j.
For certain genetic models that often occur in applications, these genotype
frequencies can be calculated by geno_freq_monogenic,
geno_freq_phased, etc.
An ngeno^2 by ngeno matrix of non-negative numbers whose rows
all sum to 1, where ngeno = length(geno_freq) is the number of possible
genotypes. The rows of trans correspond to joint parental
genotypes and the columns correspond to offspring genotypes.
If the possible genotypes are 1:length(geno_freq) then the element
trans[ngeno * gm + gf - ngeno, go] is interpreted as the conditional
probability that a person has genotype go, given that his or her
biological mother and father have genotypes gm and gf, respectively.
For certain genetic models that often occur in applications,
this transmission matrix can be calculated by trans_monogenic,
trans_phased, etc.
An nrow(fam) by length(geno_freq) matrix of non-negative
numbers. The element penet[i,j] is interpreted as the conditional
probability (or probability density) of the phenotype of the person
corresponding to row i of fam, given that his or her genotype is j
(where the possible genotypes are 1:length(geno_freq)).
Note that genotype data can be incorporated into penet by regarding
observed genotypes as part of the phenotype, i.e. by regarding observed
genotypes as (possibly noisy) measurements of the underlying true genotypes.
For example, if the observed genotype of person i is 1
(and if genotype measurement error is negligible) then penet[i,j]
should be 0 for j != 1 and penet[i,1] should be the same as if
person i were ungenotyped.
An optional list that can be used to specify genetically
identical persons, such as monozygotic twins, monozygotic triplets,
a monozygotic pair within a set of dizygotic triplets, etc.
Each element of the list should be a vector containing the individual
identifiers of a group of genetically identical persons, e.g. if fam
contains a set of monozygotic twins (and no other genetically identical
persons) then monozyg will be a list
with one element, and that element will be a vector of length two containing
the individual identifiers of the twins. The order of the list
and the orders of its elements do not affect the output of the function.
Each group of genetically identical persons should contain two or more
persons, the groups should not overlap, and all persons in each group must
have the same (non-missing) parents.
The genotype probabilities are calculated by essentially the same algorithm
as pedigree_loglikelihood;
see there for details. The genotype probabilities only depend on the
connected component of the pedigree that contains target, so the
function first restricts fam and penet to the rows corresponding to this
connected component. For example, if fam is the union of two
unrelated families then this function will restrict to the subfamily
containing target before performing the calculation.
# Read in some sample data
data("dat_small", "penet_small")
str(dat_small)
str(penet_small)
# Calculate the genotype probabilities for individual "ora008" in the family "ora"
w <- which(dat_small$family == "ora")
fam <- dat_small[w, -1]
penet <- penet_small[w, ]
monozyg <- list(c("ora024", "ora027")) # ora024 and ora027 are identical twins
trans <- trans_monogenic(2)
geno_freq <- geno_freq_monogenic(p_alleles = c(0.9, 0.1))
genotype_probabilities(target = "ora008", fam, geno_freq, trans, penet, monozyg)
Run the code above in your browser using DataLab