R/Spatial_module_expression.R

In Platypus: Single-Cell Immune Repertoire and Gene Expression Analysis

#' Plotting the expression of a gene module on the spatial image with or without a threshold.
#' @param sample_names Character vector containing the name of the sample.
#' @param gene.set Charcter vector containing the markers name.
#' @param GEX.out.directory.list Character vector that give the path to filtered_feature_bc_matrix data.
#' @param bcs_merge Data frame containing imagerow, imagecol and barcode of the cells belonging to the spatial image. It can also be created by the function scaling_spatial_image_parameter by selecting the output parameter 10.
#' @param images_tibble Tbl-df containing the sample name, grob, height and width of the spatial image. It can also be created by the function scaling_spatial_image_parameter by selecting the output parameter 5.
#' @param title Character vector to name the plot.
#' @param size Number, to define the size of the text, default = 15.
#' @param threshold Number, to define the threshold. If threshold = No, plot of the module and if threshold is a number, plot show the cells above the threshold.
#' @param legend_title Character vector to name the legend scale.
#' @return Returns a ggplot of gene module expression.
#' @export
#' @examples
#' \dontrun{
#' gene.set <- list() # make empty list
#' gene.set[[1]] <- c("CD19","XBP1","SDC1") # put gene set in list
#'
#' #Without expression threshold
#' Spatial_module_expression(sample_names = sample_names,gene.set = gene.set,
#' GEX.out.directory.list = GEX.out.directory.list[[1]],bcs_merge = scaling_parameters[[10]],
#' images_tibble = scaling_parameters[[5]], threshold = "No")
#'
#' #With expression threshold
#' Spatial_module_expression(sample_names = sample_names,gene.set = gene.set,
#' GEX.out.directory.list = GEX.out.directory.list[[1]],bcs_merge = scaling_parameters[[10]],
#' images_tibble = scaling_parameters[[5]], threshold = 1)
#' }

Spatial_module_expression<-function(sample_names,gene.set,GEX.out.directory.list,bcs_merge,images_tibble,title,size,threshold,legend_title){

  if (missing(threshold)){
    threshold = "No"
  }
  if (missing(title)){
    title = ""
  }
  if (missing(legend_title)){
    legend_title = ""
  }
  if(missing(size)){
    size = 15
  }
  if(missing(sample_names)) stop("Please provide sample_names input for this function")
  if(missing(images_tibble)) stop("Please provide images_tibble input for this function")
  if(missing(bcs_merge)) stop("Please provide bcs_merge input for this function")
  if(missing(gene.set)) stop("Please provide gene.set input for this function")
  if(missing(GEX.out.directory.list)) stop("Please provide GEX.out.directory.list input for this function")

  platypus.version <- "v3"

  barcode = NULL
  module = NULL
  imagerow = NULL
  imagecol = NULL
  grob = NULL
  width = NULL
  height = NULL
  seurat_object<-NULL
  seurat_data_frame<-NULL
  coordinates<-NULL
  module_data_frame<-NULL

  geom_spatial <-  function(mapping = NULL,
                            data = NULL,
                            stat = "identity",
                            position = "identity",
                            na.rm = FALSE,
                            show.legend = NA,
                            inherit.aes = FALSE,
                            ...) {

    GeomCustom <- ggplot2::ggproto(
      "GeomCustom",
      ggplot2::Geom,
      setup_data = function(self, data, params) {
        data <- ggplot2::ggproto_parent(ggplot2::Geom, self)$setup_data(data, params)
        data
      },

      draw_group = function(data, panel_scales, coord) {
        vp <- grid::viewport(x=data$x, y=data$y)
        g <- grid::editGrob(data$grob[[1]], vp=vp)
        #ggplot2:::ggname("geom_spatial", g)
      },

      required_aes = c("grob","x","y")

    )

    ggplot2::layer(
      geom = GeomCustom,
      mapping = mapping,
      data = data,
      stat = stat,
      position = position,
      show.legend = show.legend,
      inherit.aes = inherit.aes,
      params = list(na.rm = na.rm, ...)
    )
  }

  #Seurat object
  seurat_object<-Seurat::CreateSeuratObject(Seurat::Read10X(GEX.out.directory.list))
  #this Adds the module score to your object as a Feature
  seurat_object <- Seurat::AddModuleScore(object = seurat_object,features = list(gene.set[[1]]))
  seurat_data_frame<-seurat_object@meta.data
  seurat_data_frame$barcode <- row.names(seurat_data_frame)
  names(seurat_data_frame)[4]<-"module"
  seurat_data_frame<-dplyr::select(seurat_data_frame, barcode, module)
  coordinates<-bcs_merge
  coordinates<-dplyr::select(coordinates, imagerow, imagecol, barcode)
  module_data_frame<-merge(seurat_data_frame, coordinates, by="barcode")

  if (threshold == "No"){
    #Colors
    myPalette <- grDevices::colorRampPalette(rev(RColorBrewer::brewer.pal(11, "Spectral")))
    #Plotting
    p<-ggplot2::ggplot(data = module_data_frame, ggplot2::aes(x=imagecol,y=imagerow, fill = module))+
      geom_spatial(data=images_tibble[1,], ggplot2::aes(grob=grob), x=0.5, y=0.5)+
      ggplot2::geom_point(shape=21, colour = "black", size = 1.75, stroke = 0.5)+
      ggplot2::coord_cartesian(expand=FALSE)+
      ggplot2::scale_fill_gradientn(colours = myPalette(100))+
      ggplot2::xlim(0,max(bcs_merge %>%
                            dplyr::filter(sample ==sample_names[1]) %>%
                            dplyr::select(width)))+
      ggplot2::ylim(max(bcs_merge %>%
                          dplyr::filter(sample ==sample_names[1]) %>%
                          dplyr::select(height)),0)+
      ggplot2::xlab("") +
      ggplot2::ylab("") +
      ggplot2::ggtitle(sample_names[1],title)+
      ggplot2::theme(axis.text=ggplot2::element_text(size=size),
            axis.title=ggplot2::element_text(size=size))+
      ggplot2::labs(fill = legend_title)+
      ggplot2::theme_set(ggplot2::theme_bw(base_size = size))+
      ggplot2::theme(panel.grid.major = ggplot2::element_blank(),
            panel.grid.minor = ggplot2::element_blank(),
            panel.background = ggplot2::element_blank(),
            axis.line = ggplot2::element_line(colour = "black"),
            axis.text = ggplot2::element_blank(),
            axis.ticks = ggplot2::element_blank())
  } else {
    for (i in 1:length(module_data_frame$barcode)){
      if (module_data_frame$module[[i]]>=threshold){
        module_data_frame$threshold[[i]] = 1
      } else{
        module_data_frame$threshold[[i]] = 0
      }
    }
    module_data_frame$module<-as.numeric(module_data_frame$threshold)
    module_data_frame<-dplyr::filter(module_data_frame,module==1)
    p<-ggplot2::ggplot(data = module_data_frame, ggplot2::aes(x=imagecol,y=imagerow, fill = as.factor(module)))+
      geom_spatial(data=images_tibble[1,], ggplot2::aes(grob=grob), x=0.5, y=0.5)+
      ggplot2::geom_point(shape=21, colour = "black", size = 1.75, stroke = 0.5)+
      ggplot2::coord_cartesian(expand=FALSE)+
      ggplot2::scale_fill_discrete(guide = ggplot2::guide_legend(reverse=TRUE))+
      ggplot2::xlim(0,max(bcs_merge %>%
                            dplyr::filter(sample ==sample_names[1]) %>%
                            dplyr::select(width)))+
      ggplot2::ylim(max(bcs_merge %>%
                          dplyr::filter(sample ==sample_names[1]) %>%
                          dplyr::select(height)),0)+
      ggplot2::xlab("") +
      ggplot2::ylab("") +
      ggplot2::ggtitle(sample_names[1], title)+
      ggplot2::theme(axis.text=ggplot2::element_text(size=size),
            axis.title=ggplot2::element_text(size=size))+
      ggplot2::labs(fill = legend_title)+
      ggplot2::guides(fill = ggplot2::guide_legend(override.aes = list(size=3)))+
      ggplot2::theme_set(ggplot2::theme_bw(base_size = size))+
      ggplot2::theme(legend.key = ggplot2::element_rect(fill = "white"))+
      ggplot2::theme(panel.grid.major = ggplot2::element_blank(),
            panel.grid.minor = ggplot2::element_blank(),
            panel.background = ggplot2::element_blank(),
            axis.line = ggplot2::element_line(colour = "black"),
            axis.text = ggplot2::element_blank(),
            axis.ticks = ggplot2::element_blank())
  }
  return(p)
}