annotate center_scale.R @ 2:163befe5f05b draft default tip

planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/main/tools/gsc_center_scale commit 41ba5435a8ad12c1fe0703a9ce44b759003f3f73

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)

# Arguments
option_list <- list(
  make_option(
    "--data",
    default = NA,
    type = "character",
    help = "Input file that contains values to transform. Must be tabular separated,
            with columns and row names, variables in rows, observations in columns  [default : '%default' ]"
  ),
  make_option(
    "--center",
    default = TRUE,
    type = "logical",
    help = "center data to the mean [default : '%default' ]"
  ),
  make_option(
    "--scale",
    default = TRUE,
    type = "logical",
    help = "scale data to standard deviation [default : '%default' ]"
  ),
  make_option(
    "--factor",
    default = "",
    type = "character",
    help = "A two-column observations|factor_levels table, to group observations to be transformed by levels  [default : '%default' ]"
  ),
  make_option(
    "--output",
    default = "res.tab",
    type = "character",
    help = "Table of transformed values [default : '%default' ]"
  )
)

transform <- function(df, center = TRUE, scale = TRUE) {
  transfo <- scale(t(df),
    center = center,
    scale = scale
  )
  return(as.data.frame(t(transfo)))
}

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

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

if (opt$factor != "") {
  data_factor <- read.delim(
    opt$factor,
    check.names = FALSE,
    header = TRUE,
    sep = "\t",
    stringsAsFactors = TRUE
  )
  colnames(data_factor) <- c("cellid", "level")
  data_transformed <- data.frame(row.names = rownames(data))
  for (group in levels(data_factor$level)) {
    subcells <- as.data.frame(subset(data_factor, level == group, select = cellid))
    subdata <- as.data.frame(subset(data, select = as.vector(subcells$cellid)))
    subdata_transformed <- transform(subdata, center = as.logical(opt$center),
                                     scale = as.logical(opt$scale))
    data_transformed <- cbind(data_transformed, subdata_transformed)
  }
} else {
  data_transformed <- transform(data, center = as.logical(opt$center),
                                scale = as.logical(opt$scale))
}


write.table(
  cbind(gene = rownames(data_transformed), data_transformed),
  opt$output,
  col.names = TRUE,
  row.names = FALSE,
  quote = FALSE,
  sep = "\t"
)