Nothing
context("Theoretical Model")
test_that("seqgen_base works", {
set.seed(1)
nsamp <- 100
ngene <- 101
designmat <- model.matrix(~condition,
data.frame(condition = factor(rep(c("A", "B"),
length.out = nsamp))))
coefmat <- matrix(1, nrow = ngene, ncol = 2)
dispvec <- rep(1, length.out = ngene)
temp <- seqgen_base(designmat = designmat, coefmat = coefmat, dispvec = dispvec)
meanvec <- colMeans(temp)
expect_equal(mean(meanvec[designmat[, "conditionB"] == 1]), 4, tol = 0.1)
expect_equal(mean(meanvec[designmat[, "conditionB"] == 0]), 2, tol = 0.1)
designmat <- matrix(1, nrow = nsamp)
coefmat <- matrix(10, nrow = ngene)
dispvec <- c(1, rep(0.00001, length.out = ngene - 1))
temp <- seqgen_base(designmat = designmat, coefmat = coefmat, dispvec = dispvec)
varvec <- apply(temp, 1, var)
expect_true(varvec[1] > max(varvec[-1]))
})
test_that("seqgen_diff works", {
nsamp <- 10
ngene <- 1000
nvar <- 2
designmat <- matrix(rnorm(nvar * nsamp), nrow = nsamp)
coefmat <- matrix(rnorm(nvar * ngene), nrow = ngene)
dispvec <- rchisq(n = ngene, df = 1)
thout <- seqgen_diff(designmat = designmat,
coefmat = coefmat,
dispvec = dispvec)
expect_equal(class(thout), "list")
})
test_that("seqgen_2group works", {
ngene <- 100
nsamp <- 10
dispvec <- rep(0.1, times = ngene)
prop_null <- 1
signal_fun <- stats::rnorm
signal_params <- list(mean = 0, sd = 1)
intercept_fun <- stats::rnorm
intercept_params <- list(mean = 4, sd = 2)
libvec <- rep(1, times = nsamp)
group_prop <- 0.5
design_sv <- NULL
coef_sv <- NULL
thout <- seqgen_2group(ngene = ngene, nsamp = nsamp)
expect_equal(class(thout), "list")
})
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