runMultiUMAP {scater} | R Documentation

## Multi-modal UMAP

### Description

Perform UMAP with multiple input matrices by intersecting their simplicial sets. Typically used to combine results from multiple data modalities into a single embedding.

### Usage

    runMultiUMAP(inputs, ..., metric = "euclidean")

### Arguments

`inputs` | A list of numeric matrices where each row is a cell and each column is some dimension/variable. For gene expression data, this is usually the matrix of PC coordinates.
`...` | Further arguments to pass to `umap`.
`metric` | String specifying the type of distance to use.

### Details

This is simply a convenience wrapper around `umap` for multi-modal analysis. All modes use the distance metric of `metric` to construct the simplicial sets within each mode. Comparisons across modes are then performed after intersecting the sets to obtain a single graph.

### Value

A numeric matrix containing the low-dimensional UMAP embedding.

### Author(s)

Aaron Lun

### See Also

`runUMAP`, for the more straightforward application of UMAP.

### Examples

    # Mocking up a gene expression + ADT dataset:
    exprs_sce <- mockSCE()
    exprs_sce <- logNormCounts(exprs_sce)
    exprs_sce <- runPCA(exprs_sce)

    adt_sce <- mockSCE(ngenes=20)
    adt_sce <- logNormCounts(adt_sce)
    altExp(exprs_sce, "ADT") <- adt_sce

    # Running a multimodal analysis using PCs for expression
    # and log-counts for the ADTs:
    output <- runMultiUMAP(
        list(
            reducedDim(exprs_sce, "PCA"),
            t(logcounts(altExp(exprs_sce, "ADT")))
        )
    )

    reducedDim(exprs_sce, "combinedUMAP") <- output
    plotReducedDim(exprs_sce, "combinedUMAP")

[Package scater version 1.16.2 Index]