calculate.all.pairwise.Fst {BEDASSLE}

Calculates unbiased pairwise Fst between all sampled populations

Description

This function calculates unbiased F_{ST} (based on Weir and Hill's \theta, 2002), between all populations/individuals included in the counts matrix, and returns the results in a k by k matrix, where k = nrow(counts). Loci for which either of the populations/individuals has missing data (i.e. - the sample size is zero) are excluded.

Usage

calculate.all.pairwise.Fst(allele.counts, sample.sizes)

Arguments

allele.counts

A matrix of allelic count data, for which nrow = the number of populations and ncol = the number of bi-allelic loci sampled. Each cell gives the number of times allele ‘1’ is observed in each population. The choice of which allele is allele ‘1’ is arbitrary, but must be consistent across all populations at a locus.

sample.sizes

A matrix of sample sizes, for which nrow = the number of populations and ncol = the number of bi-allelic loci sampled (i.e. - the dimensions of sample.sizes must match those of counts). Each cell gives the number of chromosomes successfully genotyped at each locus in each population.

Value

A matrix of pairwise, unbiased F_{ST}.

Author(s)

Gideon Bradburd

References

Weir,B.S. and W.G. Hill. 2002. Estimating F-statistics. Ann.Rev.Gen. 36:949-952.

Examples

#With the HGDP dataset
	data(HGDP.bedassle.data)

#Calculate pairwise Fst between all population pairs
	hgdp.pairwise.Fst <- calculate.all.pairwise.Fst(
		HGDP.bedassle.data$allele.counts,
		HGDP.bedassle.data$sample.sizes
	)	

#Plot pairwise Fst against geographic distance
	plot(HGDP.bedassle.data$GeoDistance,
		hgdp.pairwise.Fst,
		pch=19,
		col=HGDP.bedassle.data$EcoDistance+1,
		ylab="pairwise Fst",
		xlab="geographic distance",
		main="isolation by distance")
			legend(x="bottomright",pch=19,col=c(1,2),
				legend=c("same side of Himalayas",
						"opposite sides of Himalayas"))