Understanding SpatialFeaturePlot alignment of points to image

[madsenmr2312-alt]

Hi,

I´m working with 10x HD Visium data in Seurat and trying to replicate the output of SpatialFeaturePlot - in part to understand it, but also to customize the plot to my liking.

I am having trouble aligning the points. The following code does not align points/spots to the image correctly. I have implemented size factors. What information am I missing?

feature_plot=function(object_to_use=NULL, image=NULL, gene=NULL, assay=NULL,slot="data", my_res="lowres"){
  require(dplyr)
  
  ###Checks
  if(is.null(object_to_use)){
    stop("\rPlease supply a seurat object")
  }
  
  if(is.null(assay)){
    cat("Will use assay ", Assays(object_to_use), "\t")
    assay=DefaultAssay(object_to_use)
  }
  
  if(is.null(image)){
    cat("Will use image ", Images(object_to_use)[1])
  }
  
  if(isFALSE(gene %in% rownames(object@assays[[1]]$counts))){
   stop()  
  }
  
  #Image
  tmp_img=object_to_use@images[[image]]@image
  
  #Convert to grob
  tmp_grob=as.raster(tmp_img) %>% 
    grid::rasterGrob(width = unit(1, "npc"), height = unit(1, "npc"),
                     interpolate = TRUE)
  #Dimensions
  arr=dim(tmp_img)
  im_h <- arr[1]
  im_w <- arr[2]
  
  #Spot coordinates
  coords <- SeuratObject::GetTissueCoordinates(object = object_to_use, image=image)
  names(coords)[1:2] <- c("x","y")
  coords$cell <- rownames(coords)
  
  #Get gene information
  gene_info=LayerData(object_to_use, assay = assay, layer = "data")
  coords$gene=gene_info[gene, coords$cell] %>% unlist()
  
  #Scale
  my_scale=object_to_use@images[[image]]@scale.factors[[my_res]]
  
  coords$new_x=coords$y
  coords$new_y=coords$x*-1
  
  coords$new_x=coords$new_x*my_scale
  coords$new_y=coords$new_y*my_scale
  
  #Plot everything
  p=ggplot(data=coords,aes(new_x,new_y))+
    annotation_custom(grob = tmp_grob, xmin  = 0, xmax = im_w, ymin=0, ymax=im_h)+
    geom_point(size=0.15, col="red", alpha=0.1)+
    coord_fixed(xlim = c(min(coords$new_x), max(coords$new_x)), ylim = c(min(coords$new_y), max(coords$new_y)), expand = TRUE)
    
return(p)
}

Best,

[madsenmr2312-alt]

Got it to work - here´s the solution if anyone is in the same situation. The trick is to scale the coordinates retrieved by GetTissueCoordinates() with the scale factor, then switch rows/x and cols/y coordinates - and finally, invert the y coordinates (and position the grob accordingly).

Here´s a minimalistic example:

tmp_img=object_to_use@images[[image]]@image
im_h <- dim(tmp_img)[1] *-1
im_w <- dim(tmp_img)[2]

#Convert to grob
tmp_grob=as.raster(tmp_img) %>%
grid::rasterGrob(width = unit(1, "npc"), height = unit(1, "npc"),
interpolate = TRUE)

#Spot coordinates
coords <- SeuratObject::GetTissueCoordinates(object = object_to_use, image=image)
coords$plot_x=coords$y
coords$plot_y=coords$x * -1
coords$cell <- rownames(coords)

#Scale coords to image
my_scale=object_to_use@images[[image]]@scale.factors[[my_res]]
coords$plot_x=coords$plot_x * my_scale
coords$plot_y=coords$plot_y * my_scale

#Get gene information
gene_info=LayerData(object_to_use, assay = assay, layer = "data")
coords$gene=gene_info[gene, coords$cell] %>% unlist()

#Plot everything
p=ggplot(data=coords,aes(plot_x,plot_y))+
annotation_custom(grob = tmp_grob, xmin = 0, xmax = im_w, ymin=im_h, ymax=0)+
geom_point(size=0.15, alpha=1, aes(col=gene))+
scale_color_gradient2(low="White", mid="White", high = "Red")+
coord_fixed(xlim=c(0,im_w), ylim=c(im_h,0))