# Creating a common SCE for further operations.
set.seed(100)
sce <- mockSCE()
# Killing alternative Experiments for simplicity.
altExps(sce) <- NULL
# Generating a normalized SCE for specific methods.
normed <- logNormCounts(sce)
# Because SnowParam() is too slow, yet MulticoreParam() fails on Windows.
# See discussion at https://github.com/Bioconductor/BiocParallel/issues/98.
safeBPParam <- function(nworkers) {
if (.Platform$OS.type=="windows") {
BiocParallel::SnowParam(nworkers)
} else {
BiocParallel::MulticoreParam(nworkers)
}
}
# Using an exact algorithm to avoid needing to set the seed for reproducibility.
options(BiocSingularParam.default=BiocSingular::ExactParam())
# Adding a test to flush out any uncontrolled parallelization.
library(BiocParallel)
failgen <- setRefClass("FailParam",
contains="BiocParallelParam",
fields=list(),
methods=list())
FAIL <- failgen()
# register(FAIL) # TODO: once DelayedArray's %*% fix gets in.
library(DelayedArray)
setAutoBPPARAM(FAIL)
expect_ggplot <- function(g) {
expect_s3_class(g, "ggplot")
expect_error(ggplot_build(g), NA)
}
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