Accessors {adegenet}

Accessors for adegenet objects

Description

An accessor is a function that allows to interact with slots of an object in a convenient way. Several accessors are available for genind or genpop objects. The operator "$" and "$<-" are used to access the slots, being equivalent to "@" and "@<-".

The operator "[" is a flexible way to subset data by individuals, populations, alleles, and loci. When using a matrix-like syntax, subsetting will apply to the dimensios of the @tab slot. In addition, specific arguments loc and pop can be used to indicate subsets of loci and populations. The argument drop is a logical indicating if alleles becoming non-polymorphic in a new dataset should be removed (default: FALSE). Examples:

• "obj[i,j]" returns "obj" with a subset 'i' of individuals and 'j' of alleles.
  

• "obj[1:10,]" returns an object with only the first 10 genotypes (if "obj" is a genind) or the first 10 populations (if "obj" is a genpop)
  

• "obj[1:10, 5:10]" returns an object keeping the first 10 entities and the alleles 5 to 10.
  

• "obj[loc=c(1,3)]" returns an object keeping only the 1st and 3rd loci, using locNames(obj) as reference; logicals, or named loci also work; this overrides other subsetting of alleles.
  

• "obj[pop=2:4]" returns an object keeping only individuals from the populations 2, 3 and 4, using popNames(obj) as reference; logicals, or named populations also work; this overrides other subsetting of individuals.
  

• "obj[i=1:2, drop=TRUE]" returns an object keeping only the first two individuals (or populations), dropping the alleles no longer present in the data.
  

The argument treatOther handles the treatment of objects in the @other slot (see details). The argument drop can be set to TRUE to drop alleles that are no longer represented in the subset.

Usage

nInd(x, ...)
nLoc(x, ...)
nAll(x, onlyObserved = FALSE, ...)
nPop(x, ...)
pop(x)
indNames(x, ...)
## S4 method for signature 'genind'
indNames(x, ...)
locNames(x, ...)
## S4 method for signature 'genind'
locNames(x, withAlleles=FALSE, ...)
## S4 method for signature 'genpop'
locNames(x, withAlleles=FALSE, ...)
popNames(x, ...)
## S4 method for signature 'genind'
popNames(x, ...)
popNames(x, ...)
## S4 method for signature 'genpop'
popNames(x, ...)
ploidy(x, ...)
## S4 method for signature 'genind'
ploidy(x, ...)
## S4 method for signature 'genpop'
ploidy(x, ...)
## S4 method for signature 'genind'
other(x, ...)
## S4 method for signature 'genpop'
other(x, ...)

Arguments

x

a genind or a genpop object.

onlyObserved

a logical indicating whether the allele count should also include the alleles with onlyObserved columns in the matrix. Defaults to FALSE, which will report only the observed alleles in the given population. onlyObserved = TRUE will be the equivalent of table(locFac(x)), but faster.

withAlleles

a logical indicating whether the result should be of the form [locus name].[allele name], instead of [locus name].

...

further arguments to be passed to other methods (currently not used).

Details

The "[" operator can treat elements in the @other slot as well. For instance, if obj@other$xy contains spatial coordinates, the obj[1:3, ]@other$xy will contain the spatial coordinates of the genotypes (or population) 1,2 and 3. This is handled through the argument treatOther, a logical defaulting to TRUE. If set to FALSE, the @other returned unmodified.

Note that only matrix-like, vector-like and lists can be proceeded in @other. Other kind of objects will issue a warning an be returned as they are, unless the argument quiet is left to TRUE, its default value.

The drop argument can be set to TRUE to retain only alleles that are present in the subset. To achieve better control of polymorphism of the data, see isPoly.

nAll() reflects the number of columns per locus present in the current gen object. If onlyObserved = TRUE, then the number of columns with at least one non-missing allele is shown.

Value

A genind or genpop object.

Methods

nInd

returns the number of individuals in the genind object

nLoc

returns the number of loci

nAll

returns the number of observed alleles in each locus

nPop

returns the number of populations

pop

returns a factor assigning individuals to populations.

pop<-

replacement method for the @pop slot of an object.

popNames

returns the names of populations.

popNames<-

sets the names of populations using a vector of length nPop(x).

indNames

returns the names of individuals.

indNames<-

sets the names of individuals using a vector of length nInd(x).

locNames

returns the names of markers and/or alleles.

locNames<-

sets the names of markers using a vector of length nLoc(x).

locFac

returns a factor that defines which locus each column of the @tab slot belongs to

ploidy

returns the ploidy of the data.

ploidy<-

sets the ploidy of the data using an integer.

alleles

returns the alleles of each locus.

alleles<-

sets the alleles of each locus using a list with one character vector for each locus.

other

returns the content of the @other slot (misc. information); returns NULL if the slot is onlyObserved or of length zero.

other<-

sets the content of the @other slot (misc. information); the provided value needs to be a list; it not, provided value will be stored within a list.

Author(s)

Thibaut Jombart [e-mail]

Examples

data(nancycats)
nancycats
pop(nancycats) # get the populations
indNames(nancycats) # get the labels of individuals
locNames(nancycats) # get the labels of the loci
alleles(nancycats)  # get the alleles
nAll(nancycats)     # count the number of alleles

head(tab(nancycats)) # get allele counts

# get allele frequencies, replace NAs
head(tab(nancycats, freq = TRUE, NA.method = "mean")) 

# let's isolate populations 4 and 8
popNames(nancycats)
obj <- nancycats[pop=c(4, 8)]
obj
popNames(obj)
pop(obj)
nAll(obj, onlyObserved = TRUE) # count number of alleles among these two populations
nAll(obj) # count number of columns in the data
all(nAll(obj, onlyObserved = TRUE) == lengths(alleles(obj))) # will be FALSE since drop = FALSE
all(nAll(obj) == lengths(alleles(obj))) # will be FALSE since drop = FALSE

# let's isolate two markers, fca23 and fca90
locNames(nancycats)
obj <- nancycats[loc=c("fca23","fca90")]
obj
locNames(obj)

# illustrate pop
obj <- nancycats[sample(1:100, 10)]
pop(obj)
pop(obj) <- rep(c('b', 'a'), each = 5)
pop(obj)

# illustrate locNames
locNames(obj)
locNames(obj, withAlleles = TRUE)
locNames(obj)[1] <- "newLocus"
locNames(obj)
locNames(obj, withAlleles=TRUE)

# illustrate how 'other' slot is handled
data(sim2pop)
nInd(sim2pop)
other(sim2pop[1:6]) # xy is subsetted automatically
other(sim2pop[1:6, treatOther=FALSE]) # xy is left as is