featurePlot {BayesSpace} | R Documentation

## Plot spatial gene expression.

### Description

Plot spatial gene expression.

### Usage

    featurePlot(
      sce,
      feature,
      assay.type = "logcounts",
      diverging = FALSE,
      low = NULL,
      high = NULL,
      mid = NULL,
      color = NULL,
      platform = NULL,
      is.enhanced = NULL,
      ...
    )

### Arguments

`sce` | SingleCellExperiment. If `feature` is specified and is a string, it must exist as a row in the specified assay of `sce`.
`feature` | Feature vector used to color each spot. May be the name of a gene/row in an assay of `sce`, or a vector of continuous values.
`assay.type` | String indicating which assay in `sce` the expression vector should be taken from.
`diverging` | If true, use a diverging color gradient in `featurePlot()` (e.g. when plotting a fold change) instead of a sequential gradient (e.g. when plotting expression).
`low, mid, high` | Optional hex codes for low, mid, and high values of the color gradient used for continuous spot values.
`color` | Optional hex code to set color of borders around spots. Set to `NA` to remove borders.
`platform` | Spatial sequencing platform. If "Visium", the hex spot layout will be used, otherwise square spots will be plotted. NOTE: specifying this argument is only necessary if `sce` was not created by `spatialCluster()` or `spatialEnhance()`.
`is.enhanced` | True if `sce` contains subspot-level data instead of spots. Spatial sequencing platform. If true, the respective subspot lattice for each platform will be plotted. NOTE: specifying this argument is only necessary if `sce` was not created by `spatialCluster()` or `spatialEnhance()`.
`...` | Additional arguments for `geom_polygon()`. `size`, to specify the linewidth of these borders, is likely the most useful.

### Value

Returns a ggplot object.

### See Also

Other spatial plotting functions: `clusterPlot()`

### Examples

    sce <- exampleSCE()
    featurePlot(sce, "gene_2")

[Package BayesSpace version 1.2.1 Index]