Reduced dimension plots {scater} | R Documentation

## Plot specific reduced dimensions

### Description

Wrapper functions to create plots for specific types of reduced dimension results in a SingleCellExperiment object.

### Usage

    plotPCASCE(object, ..., rerun = FALSE, ncomponents = 2,
      run_args = list())

    plotTSNE(object, ..., rerun = FALSE, ncomponents = 2,
      run_args = list())

    plotUMAP(object, ..., rerun = FALSE, ncomponents = 2,
      run_args = list())

    plotDiffusionMap(object, ..., rerun = FALSE, ncomponents = 2,
      run_args = list())

    plotMDS(object, ..., rerun = FALSE, ncomponents = 2,
      run_args = list())

    ## S4 method for signature 'SingleCellExperiment'
    plotPCA(object, ..., rerun = FALSE,
      ncomponents = 2, run_args = list())

### Arguments

`object` | A SingleCellExperiment object.
`...` | Additional arguments to pass to `plotReducedDim`.
`rerun` | Logical, should the reduced dimensions be recomputed even if `object` contains an appropriately named set of results in the `reducedDims` slot?
`ncomponents` | Numeric scalar indicating the number of dimensions components to (calculate and) plot. This can also be a numeric vector, see `?plotReducedDim` for details.
`run_args` | Arguments to pass to `runPCA`, `runTSNE`, etc.

### Details

Each function is a convenient wrapper around `plotReducedDim` that searches the `reducedDims` slot for an appropriately named dimensionality reduction result:

- `"PCA"` for `plotPCA`

- `"TSNE"` for `plotTSNE`

- `"DiffusionMap"` for `plotDiffusionMap`

- `"MDS"` for `"plotMDS"`

- `"UMAP"` for `"plotUMAP"`

Its only purpose is to streamline workflows to avoid the need to specify the `dimred` argument.

Previous versions of these functions would recompute the dimensionality reduction results if they were not already present. This has been deprecated in favour of users explicitly calling the relevant `run*` function, to avoid uncertainties about what was actually being plotted.

### Value

A ggplot object.

### Author(s)

Davis McCarthy, with modifications by Aaron Lun

### See Also

`runPCA`, `runDiffusionMap`, `runTSNE`, `runMDS`, and `runUMAP`, for the functions that actually perform the calculations.

`plotReducedDim`, for the underlying plotting function.

### Examples

    example_sce <- mockSCE()
    example_sce <- logNormCounts(example_sce)
    example_sce <- runPCA(example_sce)

    ## Examples plotting PC1 and PC2
    plotPCA(example_sce)
    plotPCA(example_sce, colour_by = "Cell_Cycle")
    plotPCA(example_sce, colour_by = "Cell_Cycle", shape_by = "Treatment")
    plotPCA(example_sce, colour_by = "Cell_Cycle", shape_by = "Treatment",
        size_by = "Mutation_Status")

    ## Force legend to appear for shape:
    example_subset <- example_sce[, example_sce$Treatment == "treat1"]
    plotPCA(example_subset, colour_by = "Cell_Cycle", shape_by = "Treatment",
        by_show_single = TRUE)

    ## Examples plotting more than 2 PCs
    plotPCA(example_sce, ncomponents = 4, colour_by = "Treatment",
        shape_by = "Mutation_Status")

    ## Same for TSNE:
    example_sce <- runTSNE(example_sce)
    plotTSNE(example_sce, run_args=list(perplexity = 10))

    ## Same for DiffusionMaps:
    example_sce <- runDiffusionMap(example_sce)
    plotDiffusionMap(example_sce)

    ## Same for MDS plots:
    example_sce <- runMDS(example_sce)
    plotMDS(example_sce)

[Package scater version 1.14.0 Index]