## Not run:
# requireAll(c("proto", "foreach"))
#
# ## Toy Example
# data(brain) #already hugely filtered
# #Two default gmt files are automatically downloaded,
# #otherwise it is required to locate it correctly.
# #Refer to http://www.broadinstitute.org/gsea/downloads.jsp
# brainQC <- MetaQC(brain, "c2.cp.biocarta.v3.0.symbols.gmt",
# filterGenes=FALSE, verbose=TRUE)
# #B is recommended to be >= 1e4 in real application
# runQC(brainQC, B=1e2, fileForCQCp="c2.all.v3.0.symbols.gmt")
# brainQC
# plot(brainQC)
#
# ## For parallel computation with only 2 cores
# ## R >= 2.11.0 in windows to use parallel computing
# brainQC <- MetaQC(brain, "c2.cp.biocarta.v3.0.symbols.gmt",
# filterGenes=FALSE, verbose=TRUE, isParallel=TRUE, nCores=2)
# #B is recommended to be >= 1e4 in real application
# runQC(brainQC, B=1e2, fileForCQCp="c2.all.v3.0.symbols.gmt")
# plot(brainQC)
#
# ## For parallel computation with all cores
# ## In windows, only 2 cores are used if not specified explicitly
# brainQC <- MetaQC(brain, "c2.cp.biocarta.v3.0.symbols.gmt",
# filterGenes=FALSE, verbose=TRUE, isParallel=TRUE)
# #B is recommended to be >= 1e4 in real application
# runQC(brainQC, B=1e2, fileForCQCp="c2.all.v3.0.symbols.gmt")
# plot(brainQC)
#
# ## Real Example which is used in the paper
# #download the brainFull file
# #from https://github.com/downloads/donkang75/MetaQC/brainFull.rda
# load("brainFull.rda")
# brainQC <- MetaQC(brainFull, "c2.cp.biocarta.v3.0.symbols.gmt", filterGenes=TRUE,
# verbose=TRUE, isParallel=TRUE)
# runQC(brainQC, B=1e4, fileForCQCp="c2.all.v3.0.symbols.gmt") #B was 1e5 in the paper
# plot(brainQC)
#
# ## Survival Data Example
# #download Breast data
# #from https://github.com/downloads/donkang75/MetaQC/Breast.rda
# load("Breast.rda")
# breastQC <- MetaQC(Breast, "c2.cp.biocarta.v3.0.symbols.gmt", filterGenes=FALSE,
# verbose=TRUE, isParallel=TRUE, resp.type="Survival")
# runQC(breastQC, B=1e4, fileForCQCp="c2.all.v3.0.symbols.gmt")
# breastQC
# plot(breastQC)
# ## End(Not run)
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