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:

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]