tests/testthat/helper-functions.R

In Peyronlab/MACSQuantifyR: Fast treatment of MACSQuantify FACS data

create_output_folder <- function(MACSQuant) {
  # Create folder containing various output files
  # and variables
  
  if (length(MACSQuant@param.output$path) > 0) {
    if (!dir.exists(MACSQuant@param.output$path))
    {stop("Provided path does not exists, please sepecify a valid path")}
    path <- paste(MACSQuant@param.output$path, "/outputMQ", sep = "")
  } else {
    path <- "./outputMQ"
  }
  if (!dir.exists(file.path(path))) {
    dir.create(file.path(path))
    message("--> Done: Folder ./outputMQ created")
  }
  return(MACSQuant)
}

init_GUI <- function()
  # intialize GUI plate plot for user to select replicates on
{
  well_letter <- sort(toupper(letters[seq_len(8)]), decreasing = TRUE)
  df <- data.frame(df2 = seq_len(12), df1 = c(
    rep(1, 12), rep(2, 12),
    rep(3, 12), rep(4, 12), rep(5, 12), rep(6, 12), rep(7, 12), rep(
      8,
      12
    )
  ))
  rownames(df) <- vapply(toupper(letters[seq(8, 1)]), function(x) {
    paste(x, seq(12:1), sep = "")
  }, character(12))
  # TODO external X11()
  par(mar = c(3.1, 3.1, 3.1, 9), xpd = TRUE)
  plot(df,
       yaxt = "n", xaxt = "n", xlab = "", ylab = "", axes = FALSE,
       ylim = c(-0.49, 8.49), lwd = 3, pch = 21, cex = 4.5, col = "lightblue"
  )
  title("Well plate")
  axis(2, at = seq_len(8), labels = well_letter, las = 2, line = "1")
  axis(1, at = seq_len(12), labels = seq_len(12), line = "-2.5")
  text(df, labels = rownames(df), cex = 0.8, font = 1)
  return(well_letter)
}

to_well_names <- function(point_matrix, col, well_letter) {
  # interprete locations plot and return vector containing
  # the replicates names
  coordinates_raw <- unlist(point_matrix)
  coordinates_mat <- matrix(coordinates_raw, ncol = 2)
  coordinates_mat <- round(coordinates_mat)
  points(coordinates_mat, lwd = 1, pch = 21, cex = 3.2, col = col)
  coordinates_mat[, 2] <- well_letter[coordinates_mat[, 2]]
  coordinates_names <- paste(coordinates_mat[, 2], coordinates_mat[, 1],
                             sep = ""
  )
  return(coordinates_names)
}

match_id_line <- function(MACSQuant, wid_vector) {
  # match replicate id in raw data table (my_data)
  # returns indices in raw data
  matched <- c()
  for (j in wid_vector) {
    matched <- c(matched, which(MACSQuant@my_data$WID == j))
  }
  return(matched)
}

compute_statistics <- function(MACSQuant,
                               lines,
                               stats = "mean") {
  data_selected <- MACSQuant@my_data[lines, ]
  Counts <- c()
  Percent <- c()
  for (rep in seq(1, MACSQuant@param.experiment$number_of_replicates * 2,
                  2)) {
    Counts <- c(
      Counts,
      data_selected$`Count/mL`[rep] -
        data_selected$`Count/mL`[rep + 1]
    )
    Percent <- c(Percent, (data_selected$`%-#`[rep + 1]) / 100)
  }
  Full.path.first <- unlist(strsplit(
    data_selected$`Full path`[1],
    "\\\\P1"
  ))
  WID.first <- sort(data_selected$WID)[1]
  
  if (stats == "mean") {
    Count.minus <- mean(Counts)
    Percent.plus <- mean(Percent)
  } else if (stats == "median") {
    Count.minus <- median(Counts)
    Percent.plus <- median(Percent)
  } else {
    stop(paste("Values for argument stats",
               "should be c('mean','median'). Other not supported",
               sep = " "
    ))
  }
  sd_count <- sd(Counts)
  Percent.minus <- 1 - Percent.plus
  sd_percent <- sd(Percent)
  
  results <- c(
    Full.path.first, WID.first, Percent.plus, Percent.minus,
    sd_percent, Count.minus, sd_count
  )
  return(results)
}



order_data <- function(MACSQuant) {
  
  # is_variable_missing=(check_variables()) if
  # (length(is_variable_missing)>0){stop(is_variable_missing)}
  
  # pre allocate indice matrix
  indice_matrix <- matrix(nrow = 1)
  # turn sorted matrix into vector
  sorted_vector <- as.vector(t(MACSQuant@my_replicates_sorted))
  
  for (i in sorted_vector) {
    matched <- t(which(MACSQuant@my_data$WID == i))
    if (length(matched) != 2) {
      warning(paste("Your file do not contains 2 gates",
                    " for replicate: ",
                    i, "\nPlease be sure to only have",
                    "P1 and P1/P2 gates in your file",
                    sep = ""
      ))
    }
    indice_matrix <- cbind(indice_matrix, matched)
  }
  indices <- indice_matrix[, -c(1)]
  ignored <- which(!(seq_len(dim(MACSQuant@my_data)[1]) %in% indices))
  ignored_print <- paste(unique(MACSQuant@my_data$WID[ignored]),
                         collapse = ",")
  
  if (length(indices) != dim(MACSQuant@my_data)[1]) {
    warning(paste("!!! ",
                  ignored_print,
                  " not selected and will be ignored",
                  sep = "", collapse = ""
    ))
  }
  if (MACSQuant@param.output$save.files == TRUE) {
    write.table(MACSQuant@my_data[indices, ],
                paste(MACSQuant@param.output$path,
                      "/outputMQ/sorted_table.txt", sep = ""),
                sep = "\t"
    )
    message("--> Done: New data table saved table in ./outputMQ")
  }
  message("--> Done: sorted data stored in variable my_data_sorted")
  
  return(indices)
}

#
# check_variables <- function() {
#     warn <- NULL
#     if (!exists("my_data_sorted")) {
#         warn <- paste("Variables 'my_data_sorted'",
#                 "missing: Please run order_data() first",
#                 sep = " "
#         )
#     }
#     if (!exists("my_replicates_sorted")) {
#         warn <- paste("Variables 'my_replicates_sorted'",
#                 "missing: Please run on_plate_selection() first",
#                 sep = " "
#         )
#     }
#     if (!(exists("my_data"))) {
#         warn <- paste("Variable 'my_data'",
#                 "missing: Please run load_maxQuant() first",
#                 sep = " "
#         )
#     }
#     return(warn)
# }