#' Prepare DESeq2 data for plotting

#'

#' This function reads a DESeq2 DEG data frame from an RDS file, filters it,

#' adjusts the log2FoldChange to absolute values, adds a pseudo-count to pvalues,

#' and transforms pvalues for plotting. The final data frame is returned and

#' optionally saved to a new RDS file.

#'

#' @param input_path Path to the RDS file containing the DESeq2 DEG data frame.

#' @param output_name Name for the processed data frame, also used as the RDS file name.

#' @return A data frame with processed DESeq2 DEG data.

#' @export

#' @examples

#' deseq2_file <- system.file("extdata",

#'                            "DEG_deseq2_test.rds",

#'                            package = "TransProR")

#' deseq2 <- prep_deseq2(deseq2_file)

#'

prep_deseq2 <- function(input_path, output_name = NULL) {

  # Read the DESeq2 DEG data frame from an RDS file

  DEG_deseq2 <- readRDS(input_path)

  # Filter DEG data using the deg_filter function from the same package

  DESeq2 <- deg_filter(DEG_deseq2)

  DEG_deseq2 <- DEG_deseq2[rownames(DEG_deseq2) %in% DESeq2, ]

  # Extract the Gene column as a regular column

  DEG_deseq2$Gene <- rownames(DEG_deseq2)

  # Select columns of interest

  DEG_deseq2 <- DEG_deseq2[, c('log2FoldChange', 'pvalue', "change", 'Gene')]

  # Adjust log2FoldChange values to absolute values

  DEG_deseq2$log2FoldChange <- abs(DEG_deseq2$log2FoldChange)

  # Add a small pseudo-count to pvalue to avoid log of zero

  DEG_deseq2$pvalue <- DEG_deseq2$pvalue + .Machine$double.eps

  # Transform p-value for plotting

  DEG_deseq2$pvalue <- -log10(DEG_deseq2$pvalue)

  # Rename columns

  names(DEG_deseq2) <- c('logFC', 'Pvalue', "change", 'Gene')

  # Optionally save the processed data frame as an RDS file

  if (!is.null(output_name)) {

    saveRDS(DEG_deseq2, paste0(output_name, ".Rdata"))

  }

  # Return the processed data frame

  return(DEG_deseq2)

}