PostSamp_Neutral: PostSamp_Neutral

In jrobledob/SSBayesCH: What the Package Does (One Line, Title Case)

Description

Estimates the Fst parameter using the 'null model' under the approach developed by Gianola et al. (2010) to infer selection signatures using genomic data from diploid individuals

Usage

PostSamp_Neutral(Data,Prior=c(1/2,1/2),N.Samples,Pop.col,Geno.cols)

Arguments

Data	A data frame or matrix containing genotypic data from m markers as well as a column indicating the subpopulation to which the individual belongs. Subpopulations must be coded using consecutive integer numbers starting from 1.
Prior	A vector of dimension 2 containing the values of model hyperpameters (positive real numbers). The default value is (1/2,1/2).
N.Samples	Integer corresponding to the number of samples used to perform the Monte Carlo estimation of the Fst parameter.
Pop.col	Integer indicating the column that contains the subpopulation each individual belongs to.
Geno.cols	Vector containing the columns corresponding to genotypes in the input dataset.

Value

A list containing two elements. Theta.samples. Matrix of dimension (number of markers) X N.Samples containing each sample used to compute the Monte Carlo estimate of Fst. PosteriorMeans. Vector of dimension equal to the number of markers containing the Monte Carlo estimates of Fst under the 'null model'.

Author(s)

Carlos Alberto Martínez Niño ([e-mail]).

References

Gianola, D., Simianer, H., Qanbari, S. 2010. A two-step method for detecting selection signatures using genetic markers. Genetic Research Cambridge, 92; 141-155.

Examples

data(Genodata1)
Ex1=PostSamp_Neutral(Genodata1,Prior=c(1/2,1/3),N.Samples=5000,
Pop.col=1,Geno.cols= c(2:ncol(Genodata1)))
head(Ex1$ Theta.Samples)
tail(Ex1$ Theta.Samples)

jrobledob/SSBayesCH documentation built on Dec. 21, 2021, 3:15 a.m.