comparison scran-normalize.R @ 2:6864acb21714 draft default tip

planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/main/tools/gsc_scran_normalize commit a14fb3d106b647c4f1dea2c8d3ac7c1e8848b21c

1:fb2f1b8b0013

# load packages that are provided in the conda env
options(show.error.messages = FALSE,
  error = function() {
    cat(geterrmessage(), file = stderr())
    q("no", 1, FALSE)
    }
)
loc <- Sys.setlocale("LC_MESSAGES", "en_US.UTF-8")
warnings()

library(optparse)
library(scran)

# Arguments
option_list <- list(
  make_option(
    c("-d", "--data"),
    default = NA,
    type = "character",
    help = "Input file that contains count values to transform"
  ),
  make_option(
    c("-s", "--sep"),
    default = "\t",
    type = "character",
    help = "File separator [default : '%default' ]"
  ),
  make_option(
    "--cluster",
    default = FALSE,
    action = "store_true",

    help = "Output name [default : '%default' ]"
  )
)

opt <- parse_args(OptionParser(option_list = option_list),
                 args = commandArgs(trailingOnly = TRUE))

if (opt$sep == "tab") {
  opt$sep <- "\t"
  }

data <- read.table(
  opt$data,
  check.names = FALSE,
  header = TRUE,
  row.names = 1,
  sep = opt$sep
)

## Import data as a SingleCellExperiment object
sce <- SingleCellExperiment(list(counts = as.matrix(data)))

  ## Compute sum factors
  sce <- computeSumFactors(sce)
}

sce <- normalize(sce)

logcounts <- data.frame(genes = rownames(sce), round(logcounts(sce), digits = 5), check.names = FALSE)


write.table(

2:6864acb21714

options(show.error.messages = FALSE,
  error = function() {
    cat(geterrmessage(), file = stderr())
    q("no", 1, FALSE)
  }
)
loc <- Sys.setlocale("LC_MESSAGES", "en_US.UTF-8")
warnings()

library(optparse)
library(scran)
library(dynamicTreeCut)

# Arguments
option_list <- list(
  make_option(
    c("-d", "--data"),
    default = NA,
    type = "character",
    help = "Input file that contains count values to transform"
  ),
  make_option(
    "--cluster",
    default = FALSE,
    action = "store_true",

    help = "Output name [default : '%default' ]"
  )
)

opt <- parse_args(OptionParser(option_list = option_list),
                  args = commandArgs(trailingOnly = TRUE))


data <- read.table(
  opt$data,
  check.names = FALSE,
  header = TRUE,
  row.names = 1,
  sep = "\t"
)

## Import data as a SingleCellExperiment object
sce <- SingleCellExperiment(list(counts = as.matrix(data)))

  ## Compute sum factors
  sce <- computeSumFactors(sce)
}

sce <- logNormCounts(sce)

logcounts <- data.frame(genes = rownames(sce), round(logcounts(sce), digits = 5), check.names = FALSE)


write.table(