KRIS (version 1.1.6)

fst.each.snp.hudson: Calculate the fixation index (Fst) for all SNPs between two groups of individuals from Single-nucleotide polymorphism (SNP)

Description

Fixation index (Fst) calculation was implemented using Hudson method as in Bhatia (2013) and Hudson (1992).

Fixation index (Fst) calculation was implemented using Hudson method as in Bhatia (2013) and Hudson (1992).

Usage

fst.each.snp.hudson(X, idx.p1, idx.p2)
fst.each.snp.hudson(X, idx.p1, idx.p2)

Arguments

X

A matrix contains the number 0, 1, and 2 representing SNP in additive coding. Rows represent individuals and columns represent SNP.

idx.p1

An integer vector contains the row indices of first population in the matrix X.

idx.p2

An integer vector contains the row indices of second population in the matrix X.

Value

The function returns a matrix of pairwise Fst values for all SNPs between 2 specified groups.

The function returns a matrix of pairwise Fst values for all SNPs between 2 specified groups.

References

Bhatia, G., Patterson, N., Sankararaman, S., and Price, A.L. (2013). Estimating and interpreting FST: The impact of rare variants. Genome Res. 23, 1514-1521.

Hudson, R.R., Slatkin, M., and Maddison, W.P. (1992). Estimation of levels of gene flow from DNA sequence data. Genetics 132, 583-589.

Bhatia, G., Patterson, N., Sankararaman, S., and Price, A.L. (2013). Estimating and interpreting FST: The impact of rare variants. Genome Res. 23, 1514-1521.

Hudson, R.R., Slatkin, M., and Maddison, W.P. (1992). Estimation of levels of gene flow from DNA sequence data. Genetics 132, 583-589.

See Also

fst.hudson

fst.hudson

Examples

# NOT RUN {

#Load simulated dataset
data(example_SNP)

idx1 <- which(sample_labels == 'pop1')
idx2 <- which(sample_labels == 'pop2')
fst.pairwise <- fst.each.snp.hudson(simsnp$snp, idx1, idx2)

#Print out the Fst values of the first three SNPs between 'pop1' and 'pop2'
print(fst.pairwise[1:3])



#Load simulated dataset
data(example_SNP)

idx1 <- which(sample_labels == 'pop1')
idx2 <- which(sample_labels == 'pop2')
fst.pairwise <- fst.each.snp.hudson(simsnp$snp, idx1, idx2)

#Print out the Fst values of the first three SNPs between 'pop1' and 'pop2'
print(fst.pairwise[1:3])

# }