R/mutate_rsd.R

In tidymass/massdataset: massdataset

#' Mutate Relative Standard Deviation (RSD) in mass_dataset Object
#'
#' This function adds a new column to the `variable_info` slot of a mass_dataset object,
#' which contains the relative standard deviation (RSD) for each variable according to the samples specified.
#' @param object A mass_dataset object.
#' @param according_to_samples A character vector specifying the sample IDs to consider when
#'                            calculating the RSD. Default is "all", which considers all samples.
#'
#' @return A modified mass_dataset object with an updated `variable_info` slot.
#'
#'
#' @author Xiaotao Shen <shenxt1990@outlook.com>
#' @export
#' @examples
#' data("expression_data")
#' data("sample_info")
#' data("variable_info")
#' 
#' object =
#'   create_mass_dataset(
#'     expression_data = expression_data,
#'     sample_info = sample_info,
#'     variable_info = variable_info,
#'   )
#' 
#' object
#' 
#' ##calculate RSDs according to all the samples
#' object =
#'   mutate_rsd(object = object)
#' 
#' object
#' 
#' head(extract_variable_info(object))
#' 
#' ##calculate RSDs according to only QC samples
#' object =
#'   mutate_rsd(object = object,
#'                 according_to_samples =
#'               get_sample_id(object)[extract_sample_info(object)$class == "QC"])
#' 
#' object
#' 
#' head(extract_variable_info(object))

mutate_rsd <-
  function(object, 
           according_to_samples = "all") {
    
    check_object_class(object = object, class = "mass_dataset")
    
    variable_id <- get_variable_id(object)
    sample_id <- get_sample_id(object)
    
    if(any(according_to_samples == "all")){
      according_to_samples <- sample_id
    }else{
      according_to_samples <- sample_id[sample_id %in% according_to_samples]
    }
    
    if(length(according_to_samples) == 0){
      stop("All the samples you provide in according_to_samples are not in the object.
           Please check.")
    }
    
    expression_data <-
      object@expression_data %>%
      as.data.frame()
    
    rsd <-
      expression_data[,according_to_samples, drop = FALSE] %>%
      apply(1, function(x){
        sd(x, na.rm = TRUE) * 100/mean(x, na.rm = TRUE)
      })
    
    
    new_column_name <- 
      check_column_name(object@variable_info , 
                        column.name = "rsd")
    
    object@variable_info <-
      cbind(object@variable_info,
            rsd = rsd) %>%
      as.data.frame()
    
    colnames(object@variable_info)[ncol(object@variable_info)] <-
      new_column_name
    
    ####variable_info_note
    new_variable_info_note <-
      data.frame(name = setdiff(colnames(object@variable_info), 
                                object@variable_info_note$name),
                 meaning = setdiff(colnames(object@variable_info), 
                                   object@variable_info_note$name),
                 check.names = FALSE)
    object@variable_info_note <- 
      rbind(object@variable_info_note,
            new_variable_info_note)
    object@variable_info <- 
      object@variable_info[, object@variable_info_note$name, drop = FALSE] 
    
    process_info <- object@process_info
    
    parameter <- new(
      Class = "tidymass_parameter",
      pacakge_name = "massdataset",
      function_name = "mutate_rsd()",
      parameter = list("according_to_samples" = according_to_samples),
      time = Sys.time()
    )
    
    if (all(names(process_info) != "mutate_rsd")) {
      process_info$mutate_rsd <- parameter
    }else{
      process_info$mutate_rsd <- c(process_info$mutate_rsd, 
                                       parameter)  
    }
    
    object@process_info <- process_info
    
    return(object)
      
  }