Nothing
skip_if_not_installed("hierfstat")
test_genotypes <- rbind(
c(1, 1, 0, 1, 1, 0),
c(2, 1, 0, NA, 0, 0),
c(2, NA, 0, 0, 1, 1),
c(1, 0, 0, 1, 0, 0),
c(1, 2, 0, 1, 2, 1),
c(0, 0, 0, 0, NA, 1),
c(0, 1, 1, 0, 1, NA)
)
test_indiv_meta <- data.frame(
id = c("a", "b", "c", "d", "e", "f", "g"),
population = c("pop1", "pop1", "pop2", "pop2", "pop1", "pop3", "pop3")
)
test_loci <- data.frame(
name = paste0("rs", 1:6),
chromosome = paste0("chr", c(1, 1, 1, 1, 2, 2)),
position = as.integer(c(3, 5, 65, 343, 23, 456)),
genetic_dist = as.double(rep(0, 6)),
allele_ref = c("A", "T", "C", "G", "C", "T"),
allele_alt = c("T", "C", NA, "C", "G", "A")
)
test_gt <- gen_tibble(
x = test_genotypes,
loci = test_loci,
indiv_meta = test_indiv_meta,
quiet = TRUE
)
test_that("pairwise_grm compute correctly", {
# expect error if the tibble is not grouped
coa_hier <- hierfstat::beta.dosage(test_genotypes, inb = FALSE)
grm_hier <- 2 * coa_hier
grm_gt <- pairwise_grm(test_gt)
expect_true(all.equal(grm_hier, grm_gt, check.attributes = FALSE))
})
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