popkin (version 1.2.2)

popkin-package: A package for estimating kinship and FST under arbitrary population structure

Description

The heart of this package is the popkin function, which estimates the kinship matrix of all individual pairs from their genotype matrix. Inbreeding coefficients, the generalized \(F_{ST}\), and the individual-level pairwise \(F_{ST}\) matrix are extracted from the kinship matrix using inbr, fst, and pwfst, respectively. fst accepts weights for individuals to balance subpopulations obtained with weights_subpops. Kinship matrices can be renormalized (to change the most recent common ancestor population or MRCA) using rescale_popkin. Lastly, kinship and pairwise \(F_{ST}\) matrices can be visualized using plot_popkin (with the help of inbr_diag for kinship matrices only).

See Also

Useful links:

• https://github.com/StoreyLab/popkin/

• Report bugs at https://github.com/StoreyLab/popkin/issues

Examples

# NOT RUN {
# estimate and visualize kinship and FST from a genotype matrix

# Construct toy data
X <- matrix(c(0,1,2,1,0,1,1,0,2), nrow = 3, byrow = TRUE) # genotype matrix
subpops <- c(1,1,2) # subpopulation assignments for individuals
subpops2 <- 1:3 # alternate labels treat every individual as a different subpop

# NOTE: for BED-formatted input, use BEDMatrix!
# "file" is path to BED file (excluding .bed extension)
## library(BEDMatrix)
## X <- BEDMatrix(file) # load genotype matrix object

# estimate the kinship matrix from the genotypes "X"!
# all downstream analysis require "kinship", none use "X" after this
kinship <- popkin(X, subpops) # calculate kinship from X and optional subpop labels

# plot the kinship matrix, marking the subpopulations
# note inbr_diag replaces the diagonal of kinship with inbreeding coefficients
plot_popkin( inbr_diag(kinship), labs = subpops )

# extract inbreeding coefficients from kinship
inbreeding <- inbr(kinship)

# estimate FST
weights <- weights_subpops(subpops) # weigh individuals so subpopulations are balanced
Fst <- fst(kinship, weights) # use kinship matrix and weights to calculate fst
Fst <- fst(inbreeding, weights) # estimate more directly from inbreeding vector (same result)

# estimate and visualize the pairwise FST matrix
pairwise_fst <- pwfst(kinship) # estimated matrix
leg_title <- expression(paste('Pairwise ', F[ST])) # fancy legend label
# NOTE no need for inbr_diag() here!
plot_popkin(pairwise_fst, labs = subpops, leg_title = leg_title)

# rescale the kinship matrix using different subpopulations (implicitly changes the MRCA)
kinship2 <- rescale_popkin(kinship, subpops2)

# }