calculateUMAP {scater}R Documentation

Perform UMAP on cell-level data

Description

Perform uniform manifold approximation and projection (UMAP) for the cells, based on the data in a SingleCellExperiment object.

Usage

calculateUMAP(x, ...)

## S4 method for signature 'ANY'
calculateUMAP(x, ncomponents = 2, ntop = 500,
  subset_row = NULL, feature_set = NULL, scale = FALSE,
  scale_features = NULL, transposed = FALSE, pca = if (transposed)
  NULL else 50, n_neighbors = 15, ..., external_neighbors = FALSE,
  BNPARAM = KmknnParam(), BPPARAM = SerialParam())

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

## S4 method for signature 'SingleCellExperiment'
calculateUMAP(x, ..., pca = if
  (!is.null(dimred)) NULL else 50, exprs_values = "logcounts",
  dimred = NULL, use_dimred = NULL, n_dimred = NULL)

runUMAP(x, ..., altexp = NULL, name = "UMAP")

Arguments

x

For calculateUMAP, 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 containing such a matrix.

...

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

For runUMAP, additional arguments to pass to calculateUMAP.

ncomponents

Numeric scalar indicating the number of UMAP 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.

pca

Integer scalar specifying how many PCs should be used as input into the UMAP algorithm. By default, no PCA is performed if the input is a dimensionality reduction result.

n_neighbors

Integer scalar, number of nearest neighbors to identify when constructing the initial graph.

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".

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 umap is used internally to compute the UMAP. 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.

If external_neighbors=TRUE, the nearest neighbor search is conducted using a different algorithm to that in the umap function. This can be parallelized or approximate to achieve greater speed for large data sets. The neighbor search results are then used directly to create the UMAP embedding.

Value

For calculateUMAP, a matrix is returned containing the UMAP coordinates for each cell (row) and dimension (column).

For runUMAP, a modified x is returned that contains the UMAP coordinates in reducedDim(x, name).

Author(s)

Aaron Lun

References

McInnes L, Healy J, Melville J (2018). UMAP: uniform manifold approximation and projection for dimension reduction. arXiv.

See Also

umap, for the underlying calculations.

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

[Package scater version 1.14.0 Index]