Nothing
context("RCM output")
tmpPhy = prune_taxa(taxa_names(Zeller)[seq_len(150)],
prune_samples(sample_names(Zeller)[seq_len(100)], Zeller))
test_that("RCM returns element of class RCM", {
expect_is(RCM(tmpPhy, k = 1), "RCM")
})
test_that("RCM returns phyloseq object", {
expect_is(RCM(tmpPhy, k = 1)$physeq, "phyloseq")
})
test_that("RCM throws warning when not converged", {
expect_warning(RCM(tmpPhy, k = 1, maxItOut = 2L))
})
#Introduce some NAs
tmpPhyNA = transform_sample_counts(tmpPhy, fun = function(x){
x[sample(length(x), size = 3)] = NA
x
})
test_that("RCM allows for missingness", {
expect_is(RCM(tmpPhyNA, k = 2, allowMissingness = TRUE), "RCM")
expect_is(RCM(tmpPhyNA, k = 2, allowMissingness = TRUE,
covariates = c("Diagnosis", "Country", "Gender", "BMI"),
confounders = "Age"), "RCM")
expect_is(RCM(tmpPhyNA, k = 2, allowMissingness = TRUE,
covariates = c("Diagnosis", "Country", "Gender", "BMI"),
confounders = "Age", responseFun = "nonparametric"), "RCM")
})
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