assignClones: Group Individuals Based on a Distance Threshold

View source: R/individual_distance.R

assignClonesR Documentation

Group Individuals Based on a Distance Threshold

Description

assignClones uses a distance matrix such as that produced by meandistance.matrix or meandistance.matrix2 to place individuals into groups representing asexually-related ramets, or any other grouping based on a distance threshold.

Usage

assignClones(d, samples = dimnames(d)[[1]], threshold = 0)

Arguments

d

A symmetrical, square matrix containing genetic distances between individuals. Both dimensions should be named according to the names of the individuals (samples). A matrix produced by meandistance.matrix or meandistance.matrix2 when all.distances = FALSE, or the matrix that is the second item in the list produced if all.distances = TRUE, will be in the right format. meandist.from.array will also produce a matrix in the correct format.

samples

A character vector containing the names of samples to analyze. This should be all or a subset of the names of d.

threshold

A number indicating the maximum distance between two individuals that will be placed into the same group.

Details

This function groups individuals very similarly to the software GenoType (Meirmans and van Tienderen, 2004). If a distance matrix from polysat is exported to GenoType, the results will be the same as those from assignClones assuming the same threshold is used. Note that GenoType requires that distances be integers rather than decimals, so you will have to multiply the distances produced by polysat by a large number and round them to the nearest integer if you wish to export them to GenoType. When comparing the results of assignClones and GenoType using my own data, the only differences I have seen have been the result of rounding; a decimal that was slightly above the threshold in when analyzed in R was rounded down to the threshold when analyzed in GenoType.

Note that when using a distance threshold of zero (the default), it is advisable to exclude all samples with missing data, in order to prevent the merging of non-identical clones. At higher thresholds, some missing data are allowable, but samples that have missing data at many loci should be excluded.

The write.table function can be used for exporting the results to GenoDive. See the R documentation for information on how to make a tab-delimited file with no header.

Value

A numeric vector, named by samples. Each clone or group is given a number, and the number for each sample indicates the clone or group to which it belongs.

Author(s)

Lindsay V. Clark

References

Meirmans, P. G. and Van Tienderen, P. H. (2004) GENOTYPE and GENODIVE: two programs for the analysis of genetic diversity of asexual organisms. Molecular Ecology Notes 4, 792–794.

See Also

genotypeDiversity

Examples

# set up a simple matrix with three samples
test <- matrix(c(0,0,.5,0,0,.5,.5,.5,0), ncol=3, nrow=3)
abc <- c("a", "b", "c")
dimnames(test) <- list(abc,abc)

# assign clones with a threshold of zero or 0.5
assignClones(test)
assignClones(test, threshold=0.5)

polysat documentation built on Aug. 23, 2022, 5:07 p.m.