context("grm")
test_that("basic example (BEDMatrix)", {
stopifnot(require(BEDMatrix))
path <- system.file("extdata", "example.bed", package = "BEDMatrix")
bmat <- BEDMatrix(path)
grm1 <- bigdat_grm(bmat, num_batches = 2, check_na = TRUE)
grm2 <- bigdat_grm(bmat, num_batches = 2, check_na = FALSE)
})
test_that("all markers filtered out", {
nrows <- 5
ncols <- 100
# sparse matrix
set.seed(1)
vals <- rbinom(100, 1, 0.5)
mat <- matrix(vals, nrows, ncols)
grm <- bigdat_grm(mat, num_batches = 2, maf_min = 0.6)
})
test_that("grm: jacard", {
nrows <- 5
ncols <- 100
# sparse matrix
set.seed(1)
vals <- rbinom(100, 1, 0.1)
mat <- matrix(vals, nrows, ncols)
jac1 <- jacard(mat)
jac2 <- bigdat_grm(mat, "Jacard", num_batches = 2)
expect_equal(as.numeric(jac1), as.numeric(jac2))
# more dense matrix
set.seed(1)
vals <- rbinom(100, 1, 0.5)
mat <- matrix(vals, nrows, ncols)
jac3 <- jacard(mat)
jac4 <- bigdat_grm(mat, "Jacard", num_batches = 2)
expect_equal(as.numeric(jac3), as.numeric(jac4))
})
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