polysat (version 1.7-7)

recodeAllopoly: Create a New genambig Dataset with Loci Split into Isoloci

Description

Given a "genambig" object and a list of allele assignments such as those produced by testAlGroups or catalanAlleles, recodeAllopoly will generate a new "genambig" object, with genotypes split according to which alleles belong to which isoloci.

Usage

recodeAllopoly(object, x, allowAneuploidy = TRUE,
               samples = Samples(object), loci = Loci(object))

Value

A "genambig" object, with loci that are in x split into the appropriate number of isoloci.

Arguments

object

A "genambig" object containing the dataset that needs to be re-coded.

x

A list. Each item in the list should itself be a list, in the format output by testAlGroups, catalanAlleles, or mergeAlleleAssignments. Each sub-list has three items: $locus is the name of the locus, $SGploidy is an integer indicating the ploidy of each subgenome (e.g. 2 for an allotetraploid), and $assignments is a matrix of ones and zeros indicating which alleles belong to which isoloci.

allowAneuploidy

Boolean. This controls what happens when the function encounters genotypes that have more alleles than are possible for a given isolocus. (For example, the genotype has four alleles, but three belong to isolocus 1 and one belongs to isolocus 2.) If TRUE, the individual is assumed to be aneuploid at that locus, and its ploidy is adjusted only for that locus. If FALSE, missing data are recorded.

samples

An optional character vector indicating which samples to analyze and output.

loci

An optional character vector indicating which loci to analyze and output.

Author

Lindsay V. Clark

Details

The same locus may appear more than once in x, for example if distinct populations were analyzed separately to produce the allele assignments. If this is the case, recodeAllopoly will internally use mergeAlleleAssignments to consolidate items in x with the same locus name. Loci that are in x but not object are ignored with a warning. Loci that are in object but not x are retained in the output of the function, but not re-coded.

This function allows homoplasy, and uses process-of-elimination to try to determine which isoloci the homoplasious alleles belong to. In cases where genotypes cannot be determined for certain due to homoplasy, missing data are inserted.

If a genotype has more alleles than should be possible (e.g. five alleles in an allotetraploid), the genotype is skipped and will be output as missing data for all corresponding isoloci.

References

Clark, L. V. and Drauch Schreier, A. (2017) Resolving microsatellite genotype ambiguity in populations of allopolyploid and diploidized autopolyploid organisms using negative correlations between alleles. Molecular Ecology Resources, 17, 1090--1103. DOI: 10.1111/1755-0998.12639.

Examples

# generate a dataset for this example
testdata <- new("genambig", samples = paste("S", 1:9, sep = ""),
                loci = c("L1", "L2","L3"))
Genotypes(testdata, loci="L1") <-
    list(c(120,124),c(124,126,130),c(120,126),c(126,132,134),
         c(120,124,130,132),c(120,126,130),c(120,132,134),
         c(120,124,126,130),c(120,132,138))
Genotypes(testdata, loci="L2") <-
    list(c(210,219,222,225),c(216,228),c(210,213,219,222),c(213,222,225,228),
         c(210,213,216,219),c(222,228),c(213),c(210,216),c(219,222,228))
Genotypes(testdata, loci="L3") <-
    list(c(155,145,153),c(157,155),c(151,157,159,165),c(147,151),c(149,153,157),
         c(149,157),c(153,159,161),c(163,165),c(147,163,167))
viewGenotypes(testdata)

# generate allele assignments for this example
myAssign <- list(list(locus="L1", SGploidy=2,
             assignments=matrix(c(1,0,0,1,1,1,0,1,1,0,1,1), nrow=2,
                                ncol=6, dimnames=list(NULL,
                                  c("120","124","126","130","132","134")))),
    list(locus="L2", SGploidy=2,
         assignments=matrix(c(1,1,1,1,1,1,1,0,1,0,1,0,0,1), nrow=2, ncol=7,
    dimnames=list(NULL,c("210","213","216","219","222","225","228")))),
    list(locus="L3", SGploidy=2, assignments="No assignment"))
myAssign

# recode the dataset
splitdata <- recodeAllopoly(testdata, myAssign)

# view results
viewGenotypes(splitdata)
Ploidies(splitdata)