polysat (version 0.1)

meandistance.matrix: Mean Pairwise Distance Matrix

Description

Given a two-dimensional list of genotypes, indexed by sample and locus, meandistance.matrix produces a symmetrical matrix of pairwise distances between samples, averaged across all loci. An array of all distances prior to averaging may also be produced.

Usage

meandistance.matrix(gendata, samples=dimnames(gendata)[[1]],
loci=dimnames(gendata)[[2]], all.distances=FALSE, usatnts=NULL, ...)

Arguments

gendata

A two-dimensional list of genotypes in the standard polysat format. The first dimension is an index of samples, the second dimension is an index of loci, and the elements are numerical vectors containing the alleles as elements.

samples

A character vector of samples to be analyzed. These should be all or a subset of the sample names used in gendata.

loci

A character vector of loci to be analyzed. These should be all or a subset of the loci names used in gendata.

all.distances

If FALSE, only the mean distance matrix will be returned. If TRUE, a list will be returned containing an array of all distances by locus and sample as well as the mean distance matrix.

usatnts

A numerical vector that contains the length of nucleotide repeats for each locus. For example, 3 would be used to indicate a locus with trinucleotide repeats. 1 should be used if alleles are written in terms of repeat number, not fragment

...

If distmetric or progress are given here they will be passed to distance.matrix.1locus. Any other arguments will be passed to distmetric.

Value

• A symmetrical matrix containing pairwise distances between all samples, averaged across all loci. Row and column names of the matrix will be the sample names provided in the samples argument. If all.distances=TRUE, a list will be produced containing the above matrix as well as a three-dimensional array containing all distances by locus and sample. The array is the first item in the list, and the mean matrix is the second.

Details

meandistance.matrix uses distance.matrix.1locus once for each locus to be analyzed, then averages values across these matrices. Any arguments that need to be passed to distance.matrix.1locus may be given to meandistance.matrix. If the loci are of different repeat types and the type of repeat is important for the distance metric being used (e.g. Bruvo.distance), the usatnts argument can be used to pass a different usatnt argument to distmetric depending on the locus. Because the user may want to omit samples or loci, the samples and loci arguments are given for convenient indexing of the data to be analyzed. If gendata contains only the data that the user wants to analyze, the user can simply omit these arguments. Missing data must be represented by the missing data symbol, rather than NA.

See Also

distance.matrix.1locus, Bruvo.distance, Lynch.distance

Examples

# create a list of genotype data
mygendata <-
  array(list(c(124,128,138),c(122,130,140,142),c(122,132,136),c(122,134,140),
             c(203,212,218),c(197,206,221),c(215),c(200,218),
             c(140,144,148,150),c(-9),c(146,150),c(152,154,158),
             c(233,236,280),c(-9),c(-9),c(-9))
        ,dim=c(4,4),dimnames=list(c("ind1","ind2","ind3","ind4"),
                                  c("locus1","locus2","locus3","locus4")))

# make index vectors of data to use
myloci <- c("locus1","locus2","locus3")
mysamples <- c("ind1","ind2","ind4")

# locus1 and locus3 have dinucleotide repeats, and locus2 has
# trinucleotide repeats
myusatnts <- c(2,3,2)
names(myusatnts) <- myloci

meandistance.matrix(mygendata, mysamples, myloci, all.distances=TRUE,
                     usatnts=myusatnts)