DEMEtics (version 0.8.1)

all.pops: Genetic Differentiation Averaged Over all Populations

Description

These functions calculate variables (D, Dest, Dest.Chao, Gst and Gst.est; see Jost, 2008) that indicate genetic differentiation for every locus and their mean values over all loci averaged over all populations. P-values indicating the strength of evidence against the null hypothesis of no genetic differentiation. 95% confidence limits are obtained from a bootstrap method. If all populations are in Hardy Weinberg Equilibrium for a given locus, alleles are randomized over populations. Otherwise, genotypes are randomized (see Goudet, 1996).

Usage

all.pops.D(filename, object=FALSE, format.table=TRUE, p.Val=TRUE, bt=1000)
all.pops.Dest(filename, object=FALSE, format.table=TRUE, p.Val=TRUE, bt=1000)
all.pops.Dest.Chao(filename, object=FALSE, format.table=TRUE, p.Val=TRUE, bt=1000)
all.pops.Gst(filename, object=FALSE, format.table=TRUE, p.Val=TRUE, bt=1000)
all.pops.Gst.est(filename, object=FALSE, format.table=TRUE, p.Val=TRUE, bt=1000)

Arguments

filename

It's syntax depends on the setting of the argument 'object'. If 'object=FALSE' (default), the filename has to be a combination of (1) the name of the data file ('.txt format') in which the raw data are saved and (2) the extension '.txt'. It has to be encl

object

This argument can be set as TRUE or FALSE (default), depending on the format of the argument 'filename'.

format.table

A logical argument either set as TRUE (default) or FALSE that defines if the format of the table has to be transformed before analysis (see details).

p.Val

A logical argument set as TRUE (default) or FALSE, that determines whether p-values shall be calculated.

bt

A numeric argument (default=1000) that defines the times of bootstrap-resamplings for the calculation of p-values and the 95% confidence intervals. If p.Val=FALSE, 'bt' will be ignored.

Value

• Four data tables (space-delimited) and in '.txt'-format are returned and saved to the actual working directory. The location of the actual working directory can be requested by typing 'getwd()' and changed by using the function setwd. You will be informed about the filenames under which the data tables have been saved automatically. The name includes the argument 'filename' and the actual date.

  If an analysis is carried out more than once at the same day, the results will all be found, one written below the other, separated by a row of column names, in the same file (if the working directory was not changed).

• differentiation.for.loci
  A data table comprising the value of genetic differentiation for each locus separately. When p.Val was set as TRUE, each value is listed with the 95% confidence limits and the p-value. The table is assigned to the workspace (.GlobalEnv) and can be called up by typing 'D.all.pops','Dest.all.pops', 'Dest.Chao.all.pops, 'Gst.all.pops' or 'Gst.est.all.pops'.
• mean.differentiation.over.all.loci
  A data table listing the mean value of genetic differentiation over all loci with the according 95% confidence limits and the p-value (p.Val=TRUE). The table is assigned to the workspace (.GlobalEnv) and can be called up by typing 'D.all.pops', 'Dest.all.pops', 'Dest.Chao.all.pops, 'Gst.all.pops or 'Gst.est.all.pops'.
• allelefrequencies
  Frequencies of the allele that were calculated by the function allelefreq that is included in this package
• sample.sizes
  The sample sizes for each locus that were calculated by the function allelefreq that is included in this package

Details

The data table comprising the raw data can be of two different formats. Format 1 equals the output of the function inputformat. Format 2 equals the input of the function inputformat. Please refer to this description file for details. If format 1 is used, the argument 'format.table' has to be set as FALSE. Using format 2, the argument 'format.table' has to be set as TRUE (default). In this case, the data table is automatically transformed to format 1.

In the data table that will be returned at the end, the loci will be sorted alphabetically and additionally numerically if numbers are included in.

The bootstrap 95% confidence limits are obtained automatically when the argument p.Val is set as TRUE. For further details of the bootstrapping and the calculation of the confidence limits, see the help file for Bootstrapping.D.

The p-values are calculated automatically using the function p.val that is included in this package.

References

Goudet, J., Raymond, M., deMee{"u}s, T. and Rousset, F. 1996 Testing differentiation in diploid populations. Genetics 144, 4, p. 1933--1940.

Jost, L. 2008 Gst and its relatives do not measure differentiation. Molecular Ecology 17, 18, p. 4015--4026.

See Also

Bootstrapping.D, p.val, p.value.correcture, Hardy.Weinberg, pair.pops.Dest, allelefreq, setwd, quantile, inputformat

Examples

data(Example.transformed)
Example1 <- Example.transformed
all.pops.D("Example1", object=TRUE, format.table=FALSE, p.Val=FALSE)
all.pops.Dest.Chao("Example1", object=TRUE, format.table=FALSE, p.Val=FALSE)
all.pops.Gst("Example1", object=TRUE, format.table=FALSE, p.Val=FALSE)

data(Example.untransformed)
Example2 <- Example.untransformed
all.pops.Dest("Example2",object=TRUE,format.table=TRUE, p.Val=FALSE)
all.pops.Gst.est("Example2",object=TRUE,format.table=TRUE, p.Val=FALSE)