https://github.com/ctlab/phantasus
Tip revision: 196f3db2382e89502f3d95664a7f0bee36af7287 authored by Alexey Sergushichev on 20 July 2020, 21:37:31 UTC
version bump
version bump
Tip revision: 196f3db
testlimmaAnalysis.R
context("Limma Analysis")
test_that("limmaAnalysis finishes with result", {
load(file = system.file("testdata/GSE27112-GPL6103.rda", package="phantasus"))
expect_is(limmaAnalysis(es,
fieldValues = c(rep("A", 3), rep("B", 2))), "json")
})
test_that("limmaAnalysis works when there is only one phenotype attribute", {
load(file = system.file("testdata/GSE27112-GPL6103.rda", package="phantasus"))
pData(es) <- pData(es)[, "title", drop=F]
expect_is(limmaAnalysis(es,
fieldValues = c(rep("A", 3), rep("B", 2))), "json")
})
test_that("limmaAnalysisImpl works", {
load(file = system.file("testdata/GSE27112-GPL6103.rda", package="phantasus"))
de <- limmaAnalysisImpl(es, fieldValues = c(rep("A", 2), rep("B", 2), NA))
expect_equal(de$logFC[1], mean(exprs(es)[1, 3:4]) - mean(exprs(es)[1, 1:2]))
})
# Limma works for full dataset only
#test_that("limmaAnalysisImpl works for subsamples", {
# load(file = system.file("testdata/GSE27112-GPL6103.rda", package="phantasus"))
# de1 <- limmaAnalysisImpl(es, rows=seq_len(nrow(es)), columns=seq_len(ncol(es)),
# fieldValues = c(rep("A", 2), NA, rep("B", 2)))
#
# de2 <- limmaAnalysisImpl(es, rows=seq_len(nrow(es)), columns=c(1:2, 4:5),
# fieldValues = c(rep("A", 2), rep("B", 2)))
# expect_equal(de1$t, de2$t)
#})