#----Setup----------------------------------------------------------------------
data(network)
data(clusters)
set.seed(123)
#----Start tests----------------------------------------------------------------
test_that("cluster_network() clusters genes using the infomap algorithm", {
cluster <- cluster_network(network[1:100, ])
expect_equal(class(cluster), "data.frame")
expect_equal(class(cluster$Gene), "character")
expect_equal(class(cluster$Cluster), "numeric")
expect_equal(ncol(cluster), 2)
})
test_that("phylogenomic_profile() returns cluster profiles", {
fclusters <- sample(clusters$Cluster, size = 50, replace = FALSE)
fclusters <- clusters[clusters$Cluster %in% fclusters, ]
profiles <- phylogenomic_profile(fclusters)
expect_true("matrix" %in% class(profiles))
expect_equal(nrow(profiles), length(unique(fclusters$Cluster)))
})
test_that("find_GS_clusters() finds group-specific clusters", {
profile_matrix <- phylogenomic_profile(clusters)
species_order <- c(
"vra", "van", "pvu", "gma", "cca", "tpr", "mtr", "adu", "lja",
"Lang", "car", "pmu", "ppe", "pbr", "mdo", "roc", "fve",
"Mnot", "Zjuj", "hlu", "jcu", "mes", "rco", "lus", "ptr"
)
species_annotation <- data.frame(
Species = species_order,
Family = c(rep("Fabaceae", 11), rep("Rosaceae", 6),
"Moraceae", "Ramnaceae", "Cannabaceae",
rep("Euphorbiaceae", 3), "Linaceae", "Salicaceae")
)
gs_clusters <- find_GS_clusters(profile_matrix, species_annotation)
expect_error(
find_GS_clusters(profile_matrix, matrix(NA, 2, 2))
)
expect_equal(class(gs_clusters), "data.frame")
expect_equal(names(gs_clusters), c("Group", "Percentage", "Cluster"))
})
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