R/qc_graph_pactr-class.R

In mpactr: Correction of Preprocessed MS Data

graph_qc_pactr <- R6Class("graph_qc_pactr", public = list(
  initialize = function(filter_pactr) {
    private$filter_pactr_data <- filter_pactr
  },
  generate_QC_Summary = function() {
    list_of_failed_ions <-
      lapply(
        private$filter_pactr_data$logger$list_of_summaries,
        function(x) {
          x$get_failed_ions()
        }
      )
    status <- gsub("[[:digit:]]+", "", names(unlist(list_of_failed_ions)))
    compounds <- unlist(unname(list_of_failed_ions))

    failed_ions_dt <- data.table(status, compounds)

    passed_ions_dt <- data.table(
      "status" = rep("Passed", length(
        private$filter_pactr_data$mpactr_data$get_peak_table()$Compound
      )),
      "compounds" =
        private$filter_pactr_data$mpactr_data$get_peak_table()$Compound
    )

    private$filter_summarized <- rbind(passed_ions_dt, failed_ions_dt)
  },
  plot_QC_Tree = function() {
    ion_counts <- private$filter_summarized[, .(count = .N), by = status][
      , percent := (count / sum(count) * 100)
    ]

    return(ggplot2::ggplot(ion_counts) +
      ggplot2::aes(area = percent, fill = status) +
      treemapify::geom_treemap() +
      treemapify::geom_treemap_text(
        aes(
          label = paste(status, count, paste0("(", round(percent, 2), "%)"),
                        sep = "\n")
        ),
        colour = "darkorchid1",
        fontface = c("bold")
      ) +
      ggplot2::theme(legend.position = "none") +
      viridis::scale_fill_viridis(option = "G", discrete = TRUE))
  },
  get_summarized_dt = function() {
    return(private$filter_summarized)
  }
), private = list(
  filter_summarized = NA,
  filter_pactr_data = NA
))