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Generates a spatial plot of pixel classifications for a given gene.

pixelClass.Rd

This function visualizes the spatial distribution of gene expression similarity by classifying pixels into three categories: below threshold, similar, and not similar. The plot is generated using spatial geometry from the SpatialExperiment object.

Usage

pixelClass(input, gene, assayName = NULL)

Arguments

input

A list. Results from `spatialSimilarity()`. This includes the similarity table, log-transformed pixel data, and analysis parameters.

gene

Character. The name of the gene to visualize.

assayName

A character string or numeric specifying the assay in the Spatial Experiment to use. Default is NULL. If no value is supplied for assayName, then the first assay is used as a default

Value

A ggplot2 spatial plot displaying classified pixels, where:

  • bluePixels classified as similar (within the fold-change threshold).

  • yellowPixels with greater expression in dataset X than Y.

  • redPixels with greater expression in dataset Y than X.

  • greyPixels with gene expression below the threshold in both experiments.

The plot is generated using `sf` (simple features) for spatial representation and is overlaid with pixel classifications. The plot title includes the gene name and its similarity score.

Examples

data(speKidney)
##### Rasterize to get pixels at matched spatial locations #####
rastKidney <- SEraster::rasterizeGeneExpression(speKidney,
                assay_name = 'counts', resolution = 0.2, fun = "mean",
                BPPARAM = BiocParallel::MulticoreParam(), square = FALSE)
s <- spatialSimilarity(list(rastKidney$A, rastKidney$B))
pixelClass(s, "Gene")
#> Coordinate system already present. Adding new coordinate system, which will
#> replace the existing one.