R/impute_missForest.R

In nicohuttmann/pOmics: Framework for proteomics data analysis

#' Imputes missing values based on a Random Forest algorithm
#'
#' @param data_ list or tibble
#' @param input name of input data
#' @param output name of output data
#' @param ... arguments for missForest function
#'
#' @return
#' @export
#'
#'
impute_missForest <- function(data_, input, output, ...) {

  # Handle input
  input_list <- data_input(data_ = data_, input = input)

  if (input_list[["error"]]) return(invisible(input_list[["data"]]))

  else {
    data <- input_list[["data"]]
    input <- input_list[["input"]] # Remove if not used

  }


  # Impute by missForest
  data <- data %>%
    do_expr(expr = ifelse(x > 0, x, NA)) %>%
    tibble2matrix() %>%
    missForest::missForest(...) %>%
    purrr::pluck("ximp") %>%
    matrix2tibble()


  # Output name
  if (!hasArg(output)) output <- input

  # Prepare return
  if (input_list[["list.input"]]) {
    data_[[output]] <- data
    attr(data_, "data") <- output
  }

  else data_ <- data

  # Return
  return(data_)

}