prep_geno_data: Prepare your genetic cline data for loading into Stan

In tjthurman/BAHZ: Bayesian Analysis of Hybrid Zones

Description

Converts a dataframe containing your genetic data into the list format required for input to Stan. See details below for a description of the possible input formats.

Usage

prep_geno_data(dataframe, type = c("bi", "multi"))

Arguments

dataframe	A dataframe containing your cline data. See details for possible formats.
type	Model type. Either "bi", for the binomial model, or "multi", for the multinomial model.

Details

The input dataframe can be a data frame or a tibble. Each row should contain the information for one sampling site. For the multinomial model, four named columns must be present, all other columns will be ignored:

• transectDist: A numeric column, giving the position along the cline/transect for each site.

• AA: The number of sampled individuals that are homozygous for the focal allele. Integer.

• Aa: The number of sampled individuals that are heterozygotes. Integer.

• aa: The number of sampled individuals that are homozygous for the non-focal allele. Integer.

For the binomial model, the user can supply either a data frame with the four columns above, or a dataframe with three named columns present (again, other columns are ignored):

• transectDist: A numeric column, giving the position along the cline/transect for each site.

• nFocalAllele: The allele count for the focal allele.

• nTotalAlleles: The total number of alleles sampled (twice the number of diploid individiduals).

Value

Your data in Stan-ready list format.

See Also

fit_geno_cline

Examples

## Not run: 
prep_geno_data(yourdata, type = "bi")

## End(Not run)

tjthurman/BAHZ documentation built on May 30, 2020, 8:28 a.m.