utilities | R Documentation |
The first three functions extract information on loci,
expand.genotype
creates a table of all possible genotypes given
a set of alleles, proba.genotype
calculates expected
probabilities of genotypes under Hardy–Weinberg equilibrium,
is.snp
tests whether a locus is a SNP, is.phased
tests
whether a gentotype is phased, and unphase
unphase phased
genotypes.
getPloidy(x)
getAlleles(x)
getGenotypes(x)
expand.genotype(n, alleles = NULL, ploidy = 2, matrix = FALSE)
proba.genotype(alleles = c("1", "2"), p, ploidy = 2)
is.snp(x)
## S3 method for class 'loci'
is.snp(x)
is.phased(x)
unphase(x)
x |
an object of class |
n |
an integer giving how many alleles to consider (ignored if
|
alleles |
the allele names as a vector of mode character. |
ploidy |
an integer giving the ploidy level (either 2 or 4 for the moment). |
matrix |
a logical specifying whether to return the genotypes in a matrix or as a character vector. |
p |
a vector of allele probabilities; if missing, equal probabilities are assumed. |
expand.genotype
and proba.genotype
accept any level of
ploidy and any number of alleles.
For is.snp
, a locus is defined as a SNP if it has two alleles
and their labels are made of a single character (e.g., A and T, or 1
and 2, but not A and AT).
getPloidy
returns the ploidy level of all genotypes as a matrix
of integers with rownames and colnames taken from x
.
getAlleles
and getGenotypes
return the alleles and
genotypes, respectively, observed in all loci in an object of class
"loci"
as a list.
expand.genotype
returns a character vector (the default) or a
matrix where the rows are the genotypes and the columns are the
alleles. The matrix is numeric by default, or character if the
argument alleles
is given.
proba.genotype
returns a numeric vector with names set as the
genotypes.
is.snp
returns a logical vector specifying whether each locus
is a SNP.
is.phased
returns a matrix of the same size than the original
data specifying whether each genotype is phased or not.
unphase
unphases the genotypes and eventually pools those that
become identical once unphased (e.g., A|T and T|A).
Emmanuel Paradis
data(jaguar)
X <- jaguar[, 1:2]
getAlleles(X)
getGenotypes(X)
expand.genotype(2)
expand.genotype(2, LETTERS[1:3])
expand.genotype(3, ploidy = 4)
proba.genotype() # classical HWE with 2 alleles
## an octoploid with a six-allele locus (1287 possible genotypes):
length(p <- proba.genotype(alleles = LETTERS[1:6], ploidy = 8))
max(p) # ~ 0.006
## back to the jaguar data:
s <- summary(X)
## allele counts from the first locus:
p <- s[[1]]$allele
## expected probabilities for the 136 possible genotypes...
proba.genotype(names(p), p/sum(p))
## ... to be compared with s[[1]]$genotype
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