## code to prepare `rse_bulk_test` dataset goes here
set.seed(1234)
nrows <- 1000
ncols <- 100
counts <- matrix(runif(nrows * ncols, 1, 1e4), nrows)
gene_sym <- paste0("G", stringr::str_pad(seq(nrows), nchar(nrows), side = "left", pad = 0))
rowRanges <- GenomicRanges::GRanges(rep(c("chr1", "chr2"), c(500, nrows - 500)),
IRanges::IRanges(floor(runif(nrows, 1e5, 1e6)), width = 100),
strand = sample(c("+", "-"), nrows, TRUE),
feature_id = sprintf("ID%03d", seq(nrows)),
Symbol = gene_sym
)
BrNums <- paste0("Br", stringr::str_pad(1:ncols, nchar(ncols), side = "left", pad = 0))
RNums_raw <- sample(seq((ncols * 10)), ncols, replace = FALSE)
RNums <- paste0("R", stringr::str_pad(RNums_raw, nchar(max(RNums_raw)), side = "left", pad = 0))
colData <- S4Vectors::DataFrame(
RNum = RNums,
BrNum = BrNums,
Sex = sample(c("M", "F"), ncols, replace = TRUE),
Dx = sample(c("Case", "Control"), ncols, replace = TRUE),
Age = runif(ncols, min = -1, max = 100)
)
rse_bulk_test <- SummarizedExperiment::SummarizedExperiment(
assays = list(counts = counts),
rowRanges = rowRanges, colData = colData
)
colnames(rse_bulk_test) <- RNums
rownames(rse_bulk_test) <- gene_sym
usethis::use_data(rse_bulk_test, overwrite = TRUE)
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