g2_microsats: Estimating g2 from microsatellite data
In inbreedR: Analysing Inbreeding Based on Genetic Markers

Description Usage Arguments Details Value Author(s) References Examples

Estimating g2 from microsatellite data

1 2	g2_microsats(genotypes, nperm = 0, nboot = 0, boot_over = "inds", CI = 0.95, verbose = TRUE)

`genotypes`	`data.frame` with individuals in rows and loci in columns, containing genotypes coded as 0 (homozygote), 1 (heterozygote) and `NA` (missing)
`nperm`	Number of permutations for testing the hypothesis that the empirical g2-value is higher than the g2 for random associations between individuals and genotypes.
`nboot`	Number of bootstraps for estimating a confidence interval
`boot_over`	Bootstrap over individuals by specifying "inds" and over loci with "loci". Defaults to "ind".
`CI`	Confidence interval (default to 0.95)
`verbose`	If FALSE, nothing will be printed to show the status of bootstraps and permutations.

Calculates g2 from smaller datasets. The underlying formula is compationally expensive due to double summations over all paits of loci (see David et al. 2007). Use convert_raw to convert raw genotypes (with 2 columns per locus) into the required format.

g2_microsats returns an object of class "inbreed". The functions 'print' and 'plot' are used to print a summary and to plot the distribution of bootstrapped g2 values and CI.

An 'inbreed' object from g2_microsats is a list containing the following components:

`call`	function call.
`g2`	g2 value
`p_val`	p value from permutation test
`g2_permut`	g2 values from permuted genotypes
`g2_boot`	g2 values from bootstrap samples
`CI_boot`	confidence interval from bootstraps
`se_boot`	standard error of g2 from bootstraps
`nobs`	number of observations
`nloc`	number of markers

Martin A. Stoffel (martin.adam.stoffel@gmail.com) & Mareike Esser (messer@techfak.uni-bielefeld.de)

David, P., Pujol, B., Viard, F., Castella, V. and Goudet, J. (2007), Reliable selfing rate estimates from imperfect population genetic data. Molecular Ecology, 16: 2474

data(mouse_msats)
# tranform raw genotypes into 0/1 format
genotypes <- convert_raw(mouse_msats)
(g2_mouse <- g2_microsats(genotypes, nperm = 1000, nboot = 100, boot_over = "inds", CI = 0.95))