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Plot a gene's values in two samples, coloured by similarity class

Source: R/visualizationFunctions.R
linearRegression.Rd

This function creates a scatter plot comparing gene expression levels between two spatial experiments for a specified gene. It colors data points based on similarity classification and overlays fold-change threshold lines. No regression line is fitted: the solid line is \(y = x\). Both axes end at the larger of the two 95% quantiles of the gene's values, so the pixels with the highest values are not drawn (with a warning from ggplot2).

Usage

linearRegression(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: the assay that spatialSimilarity() used (the first assay for results of STcompare 0.1.0 and earlier, which did not record it).

Value

A ggplot2 scatter plot displaying gene expression values from two spatial experiments. Data points are colored as follows:

blue

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

yellow

Pixels with greater expression in dataset X than Y.

red

Pixels with greater expression in dataset Y than X.

grey

Pixels with gene expression below the threshold in both experiments.

The plot includes:

Solid line:

y = x (equal expression).

Dashed lines:

Fold-change similarity thresholds (upper and lower bounds).

See also

plotGene(), the standardized figure of a gene in a compareSpatial() result, which includes this scatter plot.

Examples

data(speKidney)
##### Rasterize to get pixels at matched spatial locations #####
rastKidney <- SEraster::rasterizeGeneExpression(speKidney,
               assay_name = 'counts', resolution = 0.2, fun = "mean",
               square = FALSE)

s <- spatialSimilarity(list(A = rastKidney$A, C = rastKidney$C))
linearRegression(s, "Gene")
#> Warning: Removed 14 rows containing missing values or values outside the scale range
#> (`geom_point()`).