Nothing
context("gene filter")
test_that("gene filtering is working", {
cts <- matrix(rnbinom(120, mu=100, size=10), ncol=10,
dimnames=list(1:12,paste0("s",1:10)))
cts[1,] <- 0
cts[2:3,] <- 10
cts[1:3,1] <- c(10,0,0)
counts <- data.frame(gene_id=factor(rep(1:4, each=3)),
feature_id=factor(1:12), cts)
samples <- data.frame(sample_id=paste0("s",1:10), condition=rep(c("A","B"),each=5))
d <- dmDSdata(counts, samples)
d <- dmFilter(d, min_samps_gene_expr = 10, min_gene_expr = 10,
min_samps_feature_expr = 5, min_feature_expr = 0,
min_samps_feature_prop = 5, min_feature_prop = 0)
d2 <- dmFilter(d, min_samps_gene_expr = 10, min_gene_expr = 10,
min_samps_feature_expr = 5, min_feature_expr = 10,
min_samps_feature_prop = 5, min_feature_prop = 0)
expect_true(length(d2) == 4)
sum(counts(d2[1,])$s1) # has 0 counts for this gene
# now use 'run_gene_twice'
d3 <- dmFilter(d, min_samps_gene_expr = 10, min_gene_expr = 10,
min_samps_feature_expr = 5, min_feature_expr = 10,
min_samps_feature_prop = 5, min_feature_prop = 0,
run_gene_twice=TRUE)
expect_true(length(d3) == 3)
})
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