R/merge_mifs.R

In FridleyLab/spatialTIME: Spatial Analysis of Vectra Immunoflourescent Data

#' Merge several MIF objects together
#'
#' @description This function merges MIF objects that were run separately so they
#' can be used as a single MIF. MIF objects don't *need* but *should* have the same
#' column names in the summary file and clinical data file. The MIF objects **DO**
#' need to have the same patient_id and sample_id.
#' @param mifs A list of MIF objects to merge together
#' @param check.names whether to check names of spatial files and summary enttries
#'  
#' @return Returns a new MIF object list
#'    \item{clinical_data}{clinical information from all}
#'    \item{sample}{cell level summary data from all}
#'    \item{spatial}{contains all spatial files from all MIFs}
#'    \item{derived}{appended derived variables}
#'    \item{patient_id}{patient_id from the first MIF - this is
#'    why it is important to have the same patient_id for all MIFs}
#'    \item{sample_id}{sample_id from the first MIF - also important
#'    for all MIFs to have the same sample_id}
#' @examples 
#' #merge several MIF objects
#' library(dplyr)
#' x <- create_mif(clinical_data = example_clinical %>% 
#' mutate(deidentified_id = as.character(deidentified_id)),
#' sample_data = example_summary %>% 
#' mutate(deidentified_id = as.character(deidentified_id)),
#' spatial_list = example_spatial,
#' patient_id = "deidentified_id", 
#' sample_id = "deidentified_sample")
#' x <- merge_mifs(mifs = list(x, x), check.names = FALSE)
#' 
#'@export


merge_mifs = function(mifs = NULL, check.names = T){
  #check for proper number of MIF objects
  if(is.null(mifs) | length(mifs) == 1){
    stop("Please enter at least 2 MIF objects to merge")
  }
  #find patient_id values
  patient_id = sapply(mifs, function(mif){
    mif$patient_id
  }) %>% unique()
  if(length(patient_id) > 1 & check.names == T){
    stop("MIF objects have different patient_id values")
  }
  #find sample_id values
  sample_id = sapply(mifs, function(mif){
    mif$sample_id
  }) %>% unique()
  if(length(sample_id) > 1 & check.names == T){
    stop("MIF objects have different sample_id values")
  }
  
  #merge clinical variables
  clinical = lapply(mifs, function(mif){
    mif$clinical
  }) %>%
    do.call(dplyr::bind_rows, .) %>%
    dplyr::distinct()
  #merge clinical variables
  sample = lapply(mifs, function(mif){
    mif$sample
  }) %>%
    do.call(dplyr::bind_rows, .) %>%
    dplyr::distinct()
  
  #merging spatial data
  spatial = lapply(mifs, function(mif){
    mif$spatial
  }) %>% 
    do.call(c, .)
  if(TRUE %in% duplicated(names(spatial)) & check.names == TRUE){
    stop("Multiple files have the same name")
  }
  
  #merging the derived variables
  derived_names = sapply(mifs, function(mif){
    names(mif$derived)
  }) %>%
    unlist() %>%
    as.character() %>%
    unique()
  #alert no derived
  if(is.null(derived_names)){
    message("No variables have been derived yet")
  }
  #find mif with the most to use as "base" mif for merging
  sizes = sapply(mifs, function(mif){
    length(mif$derived)
  })
  names(sizes) = seq(length(sizes))
  derived = lapply(mifs, function(mif){
    mif$derived
  })
  names(derived) = names(sizes)
  #sort derived to have order with most derived first
  derived = derived[names(sort(sizes, decreasing = T))]
  #begin merging
  derived2 = lapply(derived_names, function(name){
    lapply(derived, function(mif){
      metric = mif[[name]]
      if(is.null(metric)){
        return()
      } else {
        return(metric)
      }
    }) %>%
      do.call(bind_rows, .)
  })
  rm(derived)
  names(derived2) = derived_names
  mif <- list(clinical = clinical,
              sample = sample,
              spatial = spatial,
              derived = derived2,
              patient_id = patient_id,
              sample_id = sample_id)
  
  structure(mif, class="mif")
}