library(fgsea)
library(data.table)
library(BiocParallel)
data(exampleRanks)
data(examplePathways)
ranks <- sort(exampleRanks, decreasing = TRUE)
ranks <- abs(floor(ranks * 0.5 + 0.5))
write.table(c(length(ranks), ranks), file="roundRanks.txt", row.names = FALSE, col.names = FALSE)
fgseaRes <- fgsea(examplePathways, ranks, nperm=100,
minSize = 15, maxSize=500)
inpData <- fgseaRes[, .(size, ES)]
filePath <- "inpPathways.txt"
write.table(nrow(inpData), file = filePath,
col.names = FALSE,
row.names = FALSE)
write.table(inpData,
file = filePath,
append = TRUE,
col.names = FALSE,
row.names = FALSE,
sep = "\t")
set.seed(42)
inpData[, `seed` := sample.int(1e9, size = nrow(inpData))]
inpData <- split(inpData, seq(nrow(inpData)))
sampleSize <- 1001
multilevelPvals <- unlist(bplapply(inpData, function(x) fgsea:::fgseaMultilevelCpp(enrichmentScores = x$ES,ranks = ranks,
pathwaySize = x$size, sampleSize = sampleSize,
seed = x$seed,
eps = 0.0,
sign = TRUE)))
write.table(multilevelPvals,
file="multilevelResults.tsv",
col.names = FALSE,
row.names = FALSE,
sep = "\t")
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