#' Process and Correct Batch Effects in Tumor Data

#'

#' This function takes a tumor data set, asks the user for specific tumor types to retain,

#' and then corrects for batch effects using the ComBat_seq function from the 'sva' package.

#'

#' @description

#' The function first extracts histological types from the provided tumor data set.

#' After displaying these types, the user is prompted to input specific types to retain.

#' The data is then filtered based on this input.

#'

#' Note: This example assumes that different tumor types represent different batches in a general sense.

#' Users need to adjust the batch and group vectors based on real-life scenarios.

#'

#' @param tumor_data_path The path to the tumor data stored in an RDS file.

#' @param CombatTumor_output_path A character string specifying the path where the output RDS file will be saved.

#' @param auto_mode Logical. If set to TRUE, the function will not prompt the user for input and

#'                  will instead use the values provided in default_input. Default is FALSE.

#' @param default_input Character string. When auto_mode is TRUE, this parameter specifies the default

#'                      tumor types to be retained. It should be provided as a comma-separated string (e.g., "01,06").

#'

#' @return A data.frame with corrected values after the ComBat_seq adjustment. Note that this function also saves the

#'         combat_count_df data as an RDS file at the specified output path.

#'

#' @details

#' The ComBat_seq function from the sva package is used to correct batch effects.

#' The function requires the 'sva' package to be installed and loaded externally.

#'

#' @examples

#' tumor_file <- system.file("extdata",

#'                           "SKCM_Skin_TCGA_exp_tumor_test.rds",

#'                           package = "TransProR")

#' output_file <- file.path(tempdir(), "SKCM_combat_count.rds")

#'

#'   SKCM_combat_count <- combat_tumor(

#'   tumor_data_path = tumor_file,

#'   CombatTumor_output_path = output_file,

#'   auto_mode = TRUE,

#'   default_input = "01,06"

#' )

#'

#' head(SKCM_combat_count)[1:5, 1:5]

#'

#' @seealso \code{\link[sva]{ComBat_seq}}

#' @importFrom sva ComBat_seq

#' @export

combat_tumor <- function(tumor_data_path, CombatTumor_output_path, auto_mode = FALSE, default_input = "01,06") {

  # Load the tumor data

  tumor_data <- readRDS(tumor_data_path)

  # Extract histological types

  TumorHistologicalTypes <- substring(colnames(tumor_data), 14, 15)

  tumor_hist_table <- table(TumorHistologicalTypes)

  # Display the table to the user

  message(" ")

  message("TumorHistologicalTypes:")

  message(paste(names(tumor_hist_table), tumor_hist_table, sep = ": ", collapse = "\n"))

  # Add a space after the output for separation

  message(" ")

  # Ask the user for input or use default input in auto_mode

  if(auto_mode) {

    selected_types <- strsplit(default_input, ",")[[1]]

  } else {

    message("Please input the tumor types you wish to retain, separated by commas (e.g., 01,06): ")

    selected_types <- strsplit(readline(), ",")[[1]]

  }

  # Filter the tumor data based on user's input

  tumor <- tumor_data[, TumorHistologicalTypes %in% selected_types]

  # Modify the tumor values

  tumor1 <- 2^(tumor) - 1

  tumor1 <- apply(tumor1, 2, as.integer)

  rownames(tumor1) <- rownames(tumor)

  # If only one sample type is chosen, skip batch correction and return modified tumor data

  if(length(selected_types) == 1) {

    combat_count_df <- as.data.frame(tumor1)

  } else {

    # Create group vector

    selected_group = rep("all_group", length(which(TumorHistologicalTypes %in% selected_types)))

    # Create batch vector based on group vector

    selected_batch = match(TumorHistologicalTypes[TumorHistologicalTypes %in% selected_types], selected_types)

    # Correct for batch effects using ComBat_seq

    combat_count <- sva::ComBat_seq(as.matrix(tumor1),

                                    batch = selected_batch,

                                    group = selected_group)

    # Convert matrix to data frame

    combat_count_df <- as.data.frame(combat_count)

  }

  saveRDS(combat_count_df, file = CombatTumor_output_path)

  return(combat_count_df)

}