getUMAP {singleCellTK} | R Documentation

## Uniform Manifold Approximation and Projection(UMAP) algorithm for dimension reduction.

### Description

Uniform Manifold Approximation and Projection(UMAP) algorithm for dimension reduction.

### Usage

    getUMAP(inSCE, useAssay = "logcounts", reducedDimName = "UMAP",
      n_neighbors = 5, n_iterations = 200, alpha = 1)

### Arguments

`inSCE` | Input SCtkExperiment object. Required
`useAssay` | Indicate which assay to use. The default is "logcounts".
`reducedDimName` | a name to store the results of the dimension reduction coordinates obtained from this method. This is stored in the SingleCellExperiment object in the reducedDims slot. Required.
`n_neighbors` | specify the number of nearest neighbors. Default is 5.
`n_iterations` | number of iterations performed during layout optimization. Default is 200.
`alpha` | initial value of "learning rate" of layout optimization. Default is 1.

### Value

a SCtkExperiment object with the reduced dimensions updated under reducedDimName specified.

### Examples

    umap_res <- getUMAP(inSCE = mouseBrainSubsetSCE, useAssay = "counts",
                        reducedDimName = "UMAP", n_neighbors = 3, n_iterations = 200,
                        alpha = 1)
    reducedDims(umap_res)

[Package singleCellTK version 1.4.2 Index]