R/mutate_fc.R

In tidymass/massstat: Statistical analysis for LC-MS-based metabolomics data

#' @title mutate_fc
#' @description Calculate fold change.
#' @author Xiaotao Shen
#' \email{shenxt1990@@outlook.com}
#' @param object tidymass-class object.
#' @param control_sample_id A character vector.
#' @param case_sample_id A character vector
#' @param mean_median mean or median.
#' @param return_mass_dataset logical default TRUE
#' @return object with fold change (fc) in variable_info.
#' @importFrom massdataset check_column_name update_variable_info
#' @export
#' @examples
#' library(massdataset)
#' library(magrittr)
#' library(dplyr)
#'
#' data("liver_aging_pos")
#' liver_aging_pos
#'
#' w_78 =
#'   liver_aging_pos %>%
#'   activate_mass_dataset(what = "sample_info") %>%
#'   dplyr::filter(group == "78W") %>%
#'   dplyr::pull(sample_id)
#'
#' w_24 =
#'   liver_aging_pos %>%
#'   activate_mass_dataset(what = "sample_info") %>%
#'   dplyr::filter(group == "24W") %>%
#'   dplyr::pull(sample_id)
#'
#'
#' control_sample_id = w_24
#' case_sample_id = w_78
#'
#' liver_aging_pos =
#'   mutate_fc(
#'     object = liver_aging_pos,
#'     control_sample_id = control_sample_id,
#'     case_sample_id = case_sample_id,
#'     mean_median = "mean"
#'   )
#'
#' head(extract_variable_info(liver_aging_pos))
#'
#' liver_aging_pos =
#'   mutate_fc(
#'     object = liver_aging_pos,
#'     control_sample_id = control_sample_id,
#'     case_sample_id = case_sample_id,
#'     mean_median = "median"
#'   )
#'
#' head(extract_variable_info(liver_aging_pos))
#'
#' extract_variable_info(liver_aging_pos) %>%
#'   ggplot(aes(fc, fc.1)) +
#'   geom_point()

mutate_fc <-
  function(object,
           control_sample_id,
           case_sample_id,
           mean_median = c("mean", "median"),
           return_mass_dataset = TRUE) {
    mean_median = match.arg(mean_median)
    massdataset::check_object_class(object = object, class = "mass_dataset")
    
    if (missing(control_sample_id) | missing(case_sample_id)) {
      stop("control_sample_id and/or case_sample_id are not provided.\n")
    }
    
    if (any(!control_sample_id %in% object@sample_info$sample_id)) {
      stop("some control_sample_id are not in object.\n")
    }
    
    if (any(!case_sample_id %in% object@sample_info$sample_id)) {
      stop("some case_sample_id are not in object.\n")
    }
    
    if (sum(is.na(object@expression_data)) > 0) {
      stop("Missing values in object (expression_data).\n")
    }
    
    if (length(control_sample_id) < 3 |
        length(case_sample_id) < 3) {
      stop("control or case group have less than 3 samples.\n")
    }
    
    message(paste(length(control_sample_id), "control samples."))
    
    message(paste(length(case_sample_id), "case samples."))
    
    control_index <-
      match(control_sample_id, colnames(object@expression_data))
    
    case_index <-
      match(case_sample_id, colnames(object@expression_data))
    
    expression_data <-
      object@expression_data
    
    if (mean_median == "mean") {
      fc <-
        apply(expression_data, 1, function(x) {
          x = as.numeric(x)
          mean(x[case_index], na.rm = TRUE) / mean(x[control_index], na.rm = TRUE)
        })
    } else{
      fc <-
        apply(expression_data, 1, function(x) {
          x = as.numeric(x)
          median(x[case_index], na.rm = TRUE) / median(x[control_index], na.rm = TRUE)
        })
    }
    
    fc[is.na(fc)] <- 1
    fc[is.infinite(fc)] <- max(fc[!is.infinite(fc)])
    
    if (!return_mass_dataset) {
      names(fc) <- object@variable_info$variable_id
      return(fc)
    }
    
    new_column_name <-
      massdataset::check_column_name(object@variable_info ,
                                     column.name = "fc")
    
    object@variable_info =
      cbind(object@variable_info,
            fc = fc) %>%
      as.data.frame()
    
    colnames(object@variable_info)[ncol(object@variable_info)] <-
      new_column_name
    
    object <-
      massdataset::update_variable_info(object = object)
    
    process_info <- object@process_info
    
    parameter <- new(
      Class = "tidymass_parameter",
      pacakge_name = "massdataset",
      function_name = "mutate_fc()",
      parameter = list(
        "control_sample_id" = control_sample_id,
        case_sample_id = case_sample_id,
        mean_median = mean_median
      ),
      time = Sys.time()
    )
    
    if (all(names(process_info) != "mutate_fc")) {
      process_info$mutate_fc <- parameter
    } else{
      process_info$mutate_fc <- c(process_info$mutate_fc,
                                  parameter)
    }
    
    object@process_info <- process_info
    return(object)
  }