Nothing
library(martini)
source("big_network.R")
# GI network
causal2 <- simulate_causal_snps(gi, 2)
causal3 <- simulate_causal_snps(gi, 3)
test_that("we get causal SNPs from two different genes", {
expect_equal(intersect(causal2$gene, c("A", "B", "C")) %>% length(), 2)
expect_equal(intersect(causal3$gene, c("A", "B", "C")) %>% length(), 3)
})
test_that("genes with less than 6 single-gene SNPs are discarded", {
expect_false("D" %in% causal2$gene)
expect_false("D" %in% causal3$gene)
})
test_that("SNPs are interconnected", {
expect_equal((igraph::components(igraph::induced_subgraph(gi, names(causal2))) %>%
.$membership %>%
unique), 1 )
expect_equal((igraph::components(igraph::induced_subgraph(gi, names(causal3))) %>%
.$membership %>%
unique), 1 )
})
half <- simulate_causal_snps(gi, 2, 0.5)
test_that("we can modulate the proportion of SNPs", {
expect_equal(length(causal2), length(half) * 2)
})
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