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Genotype likelihood ratio distance (Dlr)

Source: R/dlr.R
dlr.Rd

The function computes Paetkau's et al. (1997) genotype likelihood ratio distance (Dlr).

Usage

dlr(
  data,
  strata,
  plots = FALSE,
  filename = NULL,
  parallel.core = parallel::detectCores() - 1
)

Arguments

data

The output assignment file (home likelihood or likelihood ratio statistics) from GENODIVE.

strata

A tab delimited file with 2 columns with header: INDIVIDUALS and STRATA. The STRATA column is used here as the populations id of your sample.

plots

(optional) Generate Dlr plots for all the pairwise populations in the dataset. The plots are ggplot2 objects that can be modified with the proper ggplot2 syntax. Default: plots = FALSE.

filename

(optional) Name of the file prefix for the matrix and the table written in the working directory.

parallel.core

(optional) The number of core for parallel computation. Default: parallel.core = parallel::detectCores() - 1.

Value

A list with 5 objects:

  1. the assignment results ($assignment),

  2. the dlr pairwise table ($dlr.table),

  3. the lower diagonal dlr distance matrix ($dlr.dist),

  4. a data.frame with the dlr distance mirrored ($dlr.matrix),

  5. the list of dlr plots ($dlr.plots)

References

Paetkau D, Slade R, Burden M, Estoup A (2004) Genetic assignment methods for the direct, real-time estimation of migration rate: a simulation-based exploration of accuracy and power. Molecular Ecology, 13, 55-65.

Paetkau D, Waits LP, Clarkson PL, Craighead L, Strobeck C (1997) An empirical evaluation of genetic distance statistics using microsatellite data from bear (Ursidae) populations. Genetics, 147, 1943-1957.

Meirmans PG, Van Tienderen PH (2004) genotype and genodive: two programs for the analysis of genetic diversity of asexual organisms. Molecular Ecology Notes, 4, 792-794.

Author

Thierry Gosselin thierrygosselin@icloud.com

Examples

if (FALSE) { # \dontrun{
dlr <- assigner::dlr(
data = "assignment.gdv", strata = "my.strata.tsv", plots = TRUE)

# to get the plots list:
plot.list <- dlr$dlr.plots
# access and isolate in different object a plot with $
} # }