gl.LDNe {dartR.popgen}

Estimates effective population size using the Linkage Disequilibrium method based on NeEstimator (V2)

Description

This function is basically a convenience function that runs the LD Ne estimator using Neestimator2 (http://www.molecularfisherieslaboratory.com.au/neestimator-software/) within R using the provided genlight object. To be able to do so, the software has to be downloaded from their website and the appropriate executable Ne2-1 has to be copied into the path as specified in the function (see example below).

Usage

gl.LDNe(
  x,
  outfile = "genepopLD.txt",
  outpath = tempdir(),
  neest.path = getwd(),
  critical = 0,
  singleton.rm = TRUE,
  mating = "random",
  pairing = "all",
  Waples.correction = NULL,
  Waples.correction.value = NULL,
  naive = FALSE,
  plot.out = TRUE,
  plot_theme = theme_dartR(),
  plot_colors_pop = gl.select.colors(x, verbose = 0),
  plot.file = NULL,
  plot.dir = NULL,
  verbose = NULL
)

Arguments

x

Name of the genlight object containing the SNP data [required].

outfile

File name of the output file with all results from Neestimator 2 [default 'genepopLD.txt'].

outpath

Path where to save the output file. Use outpath=getwd() or outpath='.' when calling this function to direct output files to your working directory [default tempdir(), mandated by CRAN].

neest.path

Path to the folder of the NE2-1 file. Please note there are 3 different executables depending on your OS: Ne2-1.exe (=Windows), Ne2-1M (=Mac), Ne2-1L (=Linux). You only need to point to the folder (the function will recognise which OS you are running) [default getwd()].

critical

(vector of) Critical values that are used to remove alleles based on their minor allele frequency. This can be done before using the gl.filter.maf function, therefore the default is set to 0 (no loci are removed). To run for MAF 0 and MAF 0.05 at the same time specify: critical = c(0,0.05) [default 0].

singleton.rm

Whether to remove singleton alleles [default TRUE].

mating

Formula for Random mating='random' or monogamy= 'monogamy' [default 'random'].

pairing

'all' [default] if all possible loci should be paired, or 'separate' if only loci on different chromosomes should be used.

Waples.correction

The type of Waples et al 2016 correction to apply. This is ignored if pairing is set to 'separate'. Options are 'nChromosomes', for eq 1a, or 'genomeLength' for eq 1b. NULL if none should be applied [default NULL].

Waples.correction.value

The number of chromosomes or the genome length in cM. See Waples et al 2016 for details.

naive

Whether the naive (uncorrected for samples size - see eq 7 and eq 8 in Waples 2006) should also be reported. This is mostly to diagnose the source of Inf estimate.

plot.out

Specify if plot is to be produced [default TRUE].

plot_theme

User specified theme [default theme_dartR()].

plot_colors_pop

population colors with as many colors as there are populations in the dataset [default discrete_palette].

plot.file

Name for the RDS binary file to save (base name only, exclude extension) [default NULL] temporary directory (tempdir) [default FALSE].

plot.dir

Directory in which to save files [default = working directory]

verbose

Verbosity: 0, silent or fatal errors; 1, begin and end; 2, progress log; 3, progress and results summary; 5, full report [default 2, unless specified using gl.set.verbosity].

Value

Dataframe with the results as table

Author(s)

Custodian: Bernd Gruber (Post to https://groups.google.com/d/forum/dartr)

References

• Waples, R. S. (2006). "A bias correction for estimates of effective population size based on linkage disequilibrium at unlinked gene loci*." Conservation Genetics 7(2): 167-184.

• Waples, R. K., et al. (2016). "Estimating contemporary effective population size in non-model species using linkage disequilibrium across thousands of loci." Heredity 117(4): 233-240.

Examples

## Not run: 
# SNP data (use two populations and only the first 100 SNPs)
pops <- possums.gl[1:60, 1:100]
nes <- gl.LDNe(pops,
  outfile = "popsLD.txt", outpath = tempdir(),
  neest.path = "./path_to Ne-21",
  critical = c(0, 0.05), singleton.rm = TRUE, mating = "random"
)
nes

# Using only pairs of loci on different chromosomes
# make up some chromosome location
pops@chromosome <- as.factor(sample(1:10, size = nLoc(pops), replace = TRUE))
nessep <- gl.LDNe(pops,
              outfile = "popsLD.txt", outpath = "./TestNe", pairing="separate",
              neest.path = "./path_to Ne-21",
              critical = c(0, 0.05), singleton.rm = TRUE, mating = "random"
nessep

## End(Not run)