multiGenePlots {spatialDE} | R Documentation

## Plot Spatial Patterns of Multiple Genes

### Description

Plot Spatial Patterns of Multiple Genes

### Usage

    multiGenePlots(x, ...)

    ## S4 method for signature 'matrix'
    multiGenePlots(
      x,
      coordinates,
      genes_plot,
      viridis_option = "D",
      ncol = 2,
      point_size = 1,
      dark_theme = TRUE
    )

    ## S4 method for signature 'SpatialExperiment'
    multiGenePlots(
      x,
      assay_type = "counts",
      genes_plot,
      viridis_option = "D",
      ncol = 2,
      point_size = 1,
      dark_theme = TRUE
    )

### Arguments

`x` | A numeric `matrix` of stabilized counts (e.g. resulting from `stabilize()`) where genes are rows and cells are columns. Alternatively, a SpatialExperiment object.
`...` | For the generic, arguments to pass to specific methods.
`coordinates` | A `data.frame` with sample coordinates. Each row is a sample, the columns with coordinates should be named 'x' and 'y'. For the SpatialExperiment method, coordinates are taken from `spatialCoords(x)`.
`genes_plot` | character vector specifying which genes are to be plotted.
`viridis_option` | This function uses the `viridis` palette to color cells for gene expression. Four options are available: "magma" (or "A"), "inferno" (or "B"), "plasma" (or "C"), "viridis" (or "D", the default option) and "cividis" (or "E").
`ncol` | Number of columns to arrange the plots.
`point_size` | Point size of each plot.
`dark_theme` | Whether dark background should be used; this is helpful to highlight cells with high expression when using the `viridis` palette.
`assay_type` | A `character` string specifying the assay from `x` to use as input. Defaults to `"counts"`.

### Value

This function draws a plot for each specified genes

### Author(s)

Davide Corso, Milan Malfait, Lambda Moses

### References

Svensson, V., Teichmann, S. & Stegle, O. SpatialDE: identification of spatially variable genes. Nat Methods 15, 343–346 (2018). https://doi.org/10.1038/nmeth.4636

SpatialDE 1.1.3: the version of the Python package used under the hood.

### See Also

The individual steps performed by this function: `stabilize()`, `spatialDE()`.

For further analysis of the DE results: `model_search()` and `spatial_patterns()`.

### Examples

    ## Mock up a SpatialExperiment object wit 100 cells, 200 genes
    set.seed(42)
    spe <- mockSVG(size = 10, tot_genes = 200, de_genes = 10, return_SPE = TRUE)

    ## Run spatialDE
    results <- spatialDE(spe)

    ordered_spe_results <- results[order(results$qval), ]
    head(ordered_spe_results)

    plots <- multiGenePlots(spe,
        assay_type = "counts",
        ordered_spe_results[1:4, ]$g,
        point_size = 4,
        viridis_option = "D"
    )

[Package spatialDE version 1.0.0 Index]