calculateTSNE {scater}R Documentation

Perform t-SNE on cell-level data

Description

Perform t-stochastic neighbour embedding (t-SNE) for the cells, based on the data in a SingleCellExperiment object.

Usage

calculateTSNE(x, ...)

## S4 method for signature 'ANY'
calculateTSNE(x, ncomponents = 2, ntop = 500,
  subset_row = NULL, feature_set = NULL, scale = FALSE,
  scale_features = NULL, transposed = FALSE, perplexity = NULL,
  normalize = TRUE, theta = 0.5, ..., external_neighbors = FALSE,
  BNPARAM = KmknnParam(), BPPARAM = SerialParam())

## S4 method for signature 'SummarizedExperiment'
calculateTSNE(x, ...,
  exprs_values = "logcounts")

## S4 method for signature 'SingleCellExperiment'
calculateTSNE(x, ...,
  pca = is.null(dimred), exprs_values = "logcounts", dimred = NULL,
  use_dimred = NULL, n_dimred = NULL)

runTSNE(x, ..., altexp = NULL, name = "TSNE")

Arguments

x

For calculateTSNE, a numeric matrix of log-expression values where rows are features and columns are cells. Alternatively, a SummarizedExperiment or SingleCellExperiment containing such a matrix.

For runTSNE, a SingleCellExperiment object.

...

For the calculateTSNE generic, additional arguments to pass to specific methods. For the ANY method, additional arguments to pass to Rtsne. For the SummarizedExperiment and SingleCellExperiment methods, additional arguments to pass to the ANY method.

For runTSNE, additional arguments to pass to calculateTSNE.

ncomponents

Numeric scalar indicating the number of t-SNE dimensions to obtain.

ntop

Numeric scalar specifying the number of features with the highest variances to use for PCA, see ?"scater-red-dim-args".

subset_row

Vector specifying the subset of features to use for PCA, see ?"scater-red-dim-args".

feature_set

Deprecated, same as subset_row.

scale

Logical scalar, should the expression values be standardised? See ?"scater-red-dim-args" for details.

scale_features

Deprecated, same as scale but with a different default.

transposed

Logical scalar, is x transposed with cells in rows? See ?"scater-red-dim-args" for details.

perplexity

Numeric scalar defining the perplexity parameter, see ?Rtsne for more details.

normalize

Logical scalar indicating if input values should be scaled for numerical precision, see normalize_input.

theta

Numeric scalar specifying the approximation accuracy of the Barnes-Hut algorithm, see Rtsne for details.

external_neighbors

Logical scalar indicating whether a nearest neighbors search should be computed externally with findKNN.

BNPARAM

A BiocNeighborParam object specifying the neighbor search algorithm to use when external_neighbors=TRUE.

BPPARAM

A BiocParallelParam object specifying how the neighbor search should be parallelized when external_neighbors=TRUE.

exprs_values

Integer scalar or string indicating which assay of x contains the expression values, see ?"scater-red-dim-args".

pca

Logical scalar indicating whether a PCA step should be performed inside Rtsne.

dimred

String or integer scalar specifying the existing dimensionality reduction results to use, see ?"scater-red-dim-args".

use_dimred

Deprecated, same as dimred.

n_dimred

Integer scalar or vector specifying the dimensions to use if dimred is specified, see ?"scater-red-dim-args".

altexp

String or integer scalar specifying an alternative experiment to use to compute the PCA, see ?"scater-red-dim-args".

name

String specifying the name to be used to store the result in the reducedDims of the output.

Details

The function Rtsne is used internally to compute the t-SNE. Note that the algorithm is not deterministic, so different runs of the function will produce differing results. Users are advised to test multiple random seeds, and then use set.seed to set a random seed for replicable results.

The value of the perplexity parameter can have a large effect on the results. By default, the function will set a “reasonable” perplexity that scales with the number of cells in x. (Specifically, it is the number of cells divided by 5, capped at a maximum of 50.) However, it is often worthwhile to manually try multiple values to ensure that the conclusions are robust.

If external_neighbors=TRUE, the nearest neighbor search step will use a different algorithm to that in the Rtsne function. This can be parallelized or approximate to achieve greater speed for large data sets. The neighbor search results are then used for t-SNE via the Rtsne_neighbors function.

If dimred is specified, the PCA step of the Rtsne function is automatically turned off by default. This presumes that the existing dimensionality reduction is sufficient such that an additional PCA is not required.

Value

For calculateTSNE, a numeric matrix is returned containing the t-SNE coordinates for each cell (row) and dimension (column).

For runTSNE, a modified x is returned that contains the t-SNE coordinates in reducedDim(x, name).

Author(s)

Aaron Lun, based on code by Davis McCarthy

References

van der Maaten LJP, Hinton GE (2008). Visualizing High-Dimensional Data Using t-SNE. J. Mach. Learn. Res. 9, 2579-2605.

See Also

Rtsne, for the underlying calculations.

plotTSNE, to quickly visualize the results.

?"scater-red-dim-args", for a full description of various options.

Examples

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

example_sce <- runTSNE(example_sce, scale_features=NULL)
reducedDimNames(example_sce)
head(reducedDim(example_sce))

[Package scater version 1.14.0 Index]