polysat (version 1.7-7)

simpleFreq: Simple Allele Frequency Estimator

Description

Given genetic data, allele frequencies by population are calculated. This estimation method assumes polysomic inheritance. For genotypes with allele copy number ambiguity, all alleles are assumed to have an equal chance of being present in multiple copies. This function is best used to generate initial values for more complex allele frequency estimation methods.

Usage

simpleFreq(object, samples = Samples(object), loci = Loci(object))

Value

Data frame, where each population is in one row. If each sample in object has only one ploidy, the first column of the data frame is called Genomes and contains the number of genomes in each population. Otherwise, there is a Genomes column for each locus. Each remaining column contains frequencies for one allele. Columns are named by locus and allele, separated by a period. Row names are taken from PopNames(object).

Arguments

object

A genbinary or genambig object containing genotype data. No NA values are allowed for PopInfo(object)[samples] or Ploidies(object,samples,loci). (Population identity and ploidy are needed for allele frequency calculation.)

samples

An optional character vector of samples to include in the calculation.

loci

An optional character vector of loci to include in the calculation.

Author

Lindsay V. Clark

Details

If object is of class genambig, it is converted to a genbinary object before allele frequency calculations take place. Everything else being equal, the function will work more quickly if it is supplied with a genbinary object.

For each sample*locus, a conversion factor is generated that is the ploidy of the sample (and/or locus) as specified in Ploidies(object) divided by the number of alleles that the sample has at that locus. Each allele is then considered to be present in as many copies as the conversion factor (note that this is not necessarily an integer). The number of copies of an allele is totaled for the population and is divided by the total number of genomes in the population (minus missing data at the locus) in order to calculate allele frequency.

A major assumption of this calculation method is that each allele in a partially heterozygous genotype has an equal chance of being present in more than one copy. This is almost never true, because common alleles in a population are more likely to be partially homozygous in an individual. The result is that the frequency of common alleles is underestimated and the frequency of rare alleles is overestimated. Also note that the level of inbreeding in the population has an effect on the relationship between genotype frequencies and allele frequencies, but is not taken into account in this calculation.

See Also

genbinary, genambig

Examples

# create a data set for this example
mygen <- new("genambig", samples = paste("ind", 1:6, sep=""),
             loci = c("loc1", "loc2"))
mygen <- reformatPloidies(mygen, output="sample")
Genotypes(mygen, loci="loc1") <- list(c(206),c(208,210),c(204,206,210),
    c(196,198,202,208),c(196,200),c(198,200,202,204))
Genotypes(mygen, loci="loc2") <- list(c(130,134),c(138,140),c(130,136,140),
    c(138),c(136,140),c(130,132,136))
PopInfo(mygen) <- c(1,1,1,2,2,2)
Ploidies(mygen) <- c(2,2,4,4,2,4)

# calculate allele frequencies
myfreq <- simpleFreq(mygen)

# look at the results
myfreq

# an example where ploidy is indexed by locus instead
mygen2 <- new("genambig", samples = paste("ind", 1:6, sep=""),
             loci = c("loc1", "loc2"))
mygen2 <- reformatPloidies(mygen2, output="locus")
PopInfo(mygen2) <- 1
Ploidies(mygen2) <- c(2,4)
Genotypes(mygen2, loci="loc1") <- list(c(198), c(200,204), c(200),
                                       c(198,202), c(200), c(202,204))
Genotypes(mygen2, loci="loc2") <- list(c(140,144,146), c(138,144),
                                       c(136,138,144,148), c(140),
                                       c(140,142,146,150),
                                       c(142,148,150))
myfreq2 <- simpleFreq(mygen2)
myfreq2