Sample spatial gene visualization workhorse function for Xenium data with centroid based spatailCoords

This function visualizes the gene expression stored in assays(spe) or any continuous variable stored in colData(spe) for one given sample at the spot-level using (by default) the histology information on the background. This is the function that does all the plotting behind vis_clus() when datatype = "Xenium". To visualize clusters (or any discrete variable) use vis_clus_c().

vis_gene_c(
  spe,
  d,
  sampleid = unique(spe$sample_id)[1],
  title,
  viridis = TRUE,
  alpha = NA,
  cont_colors = if (viridis) {
     viridisLite::viridis(21)
 } else {
    
    c("aquamarine4", "springgreen", "goldenrod", "red")
 },
  point_size = 2,
  na_color = "#CCCCCC40",
  legend_title = ""
)

Arguments

spe

A SpatialExperiment-class object. See fetch_data() for how to download some example objects or read10xVisiumWrapper() to read in spaceranger --count output files and build your own spe object.

d

A data.frame() with the sample-level information. This is typically obtained using cbind(colData(spe), spatialCoords(spe)). The data.frame has to contain a column with the continuous variable data to plot stored under d$COUNT.

sampleid

A character(1) specifying which sample to plot from colData(spe)$sample_id (formerly colData(spe)$sample_name).

title

The title for the plot.

viridis

A logical(1) whether to use the color-blind friendly palette from viridis or the color palette used in the paper that was chosen for contrast when visualizing the data on top of the histology image. One issue is being able to differentiate low values from NA ones due to the purple-ish histology information that is dependent on cell density.

alpha

A numeric(1) in the [0, 1] range that specifies the transparency level of the data on the spots.

cont_colors

A character() vector of colors that supersedes the viridis argument.

point_size

A numeric(1) specifying the size of the points. Defaults to 1.25. Some colors look better if you use 2 for instance.

na_color

A character(1) specifying a color for the NA values. If you set alpha = NA then it's best to set na_color to a color that has alpha blending already, which will make non-NA values pop up more and the NA values will show with a lighter color. This behavior is lost when alpha is set to a non-NA value.

legend_title

A character(1) specifying the legend title.

Value

A ggplot2 object.

See also

Other Spatial gene visualization functions: vis_gene(), vis_gene_p(), vis_grid_gene()

Examples

if (enough_ram()) {
    ## Obtain the necessary data
    if (!exists("spe_xenium")) spe_xenium <- fetch_data("spe_xenium_example")

    ## Prepare the data for the plotting function
    spe_sub <- spe_xenium[, spe_xenium$sample_id == "Br1039"]
    df <- as.data.frame(cbind(colData(spe_sub), SpatialExperiment::spatialCoords(spe_sub)), optional = TRUE)
    df$COUNT <- df$detected_gex

    ## Don't plot the histology information
    p <- vis_gene_c(
        spe = spe_sub,
        d = df,
        sampleid = "Br1039",
        title = "Br1039 detected_gex",
        point_size = 1
    )
    print(p)

    ## Clean up
    rm(spe_sub)
}
#> 2026-09-28 14:56:08.009874 loading file /github/home/.cache/R/BiocFileCache/e2d6c76d1f9_spe_Xenium_test.rds%3Frlkey%3D0ql1pu5d9qe448sjmkh3ja3o8%26st%3Dnpwqxtdk%26dl%3D1