test_that("chi2 are correctly calculated", {
true_vals <- c(98, 98, 97, 99, 97, 96, 0, 1, 1, 1, 1, 0,
0, 0, 99, 99, 97, 98, 98, 99, 0, 1, 0, 1, 0)
names(true_vals) <- test_gwas[['map']][['snp.name']]
c <- snp_test(test_gwas, covars, 'chi2')
expect_equal(c, true_vals, tolerance = .1)
# covariates have no effect
c <- snp_test(test_gwas, data.frame(), 'chi2')
expect_equal(c, true_vals, tolerance = .1)
})
test_that("glm's chi2 are correctly calculated", {
# without covariates
true_vals <- c(99, 99, 98, 100, 98, 97, 0, 1, 1, 1, 1, 0, 0,
0, 100, 100, 98, 99, 99, 100, 0.3, 1, 0, 1, 0)
names(true_vals) <- test_gwas[['map']][['snp.name']]
c <- snp_test(test_gwas, data.frame(), 'glm', "binomial", "logit")
expect_equal(c, true_vals, tolerance = .1)
# with explanatory covariates
true_vals <- rep(0, nrow(test_gwas[['map']]))
names(true_vals) <- test_gwas[['map']][['snp.name']]
c <- snp_test(test_gwas, covars, 'glm', "binomial", "logit")
expect_equal(c, true_vals, tolerance = .1)
})
test_that("linear model is correctly calculated", {
# without covariates
true_vals <- c(99, 99, 98, 100, 98, 97, 0, 1, 1, 1, 1, 0, 0,
0, 100, 100, 98, 99, 99, 100, 0.3, 1, 0, 1, 0)
names(true_vals) <- test_gwas[['map']][['snp.name']]
c <- snp_test(test_gwas, data.frame(), 'glm', "Gaussian", "identity")
expect_equal(c, true_vals, tolerance = .1)
})
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