runPCA {BiocSingular} | R Documentation

## Principal components analysis

### Description

Perform a principal components analysis (PCA) on a target matrix with a specified SVD algorithm.

### Usage

    runPCA(x, ...)

    ## S4 method for signature 'ANY'
    runPCA(x, rank, center=TRUE, scale=FALSE, get.rotation=TRUE,
        get.pcs=TRUE, ...)

### Arguments

`x` | A numeric matrix-like object with samples as rows and variables as columns.
`rank` | Integer scalar specifying the number of principal components to retain.
`center` | A logical scalar indicating whether columns of `x` should be centered before the PCA is performed. Alternatively, a numeric vector of length `ncol(x)` containing the value to subtract from each column of `x`.
`scale` | A logical scalar indicating whether columns of `x` should be scaled to unit variance before the PCA is performed. Alternatively, a numeric vector of length `ncol(x)` containing the scaling factor for each column of `x`.
`get.rotation` | A logical scalar indicating whether rotation vectors should be returned.
`get.pcs` | A logical scalar indicating whether the principal component scores should be returned.
`...` | For the generic, this contains arguments to pass to methods upon dispatch. For the `ANY` method, this contains further arguments to pass to `runSVD`. This includes `BSPARAM` to specify the algorithm that should be used, and `BPPARAM` to control parallelization.

### Details

This function simply calls `runSVD` and converts the results into a format similar to that returned by `prcomp`.

The generic is exported to allow other packages to implement their own `runPCA` methods for other `x` objects, e.g., scater for SingleCellExperiment inputs.

### Value

A list is returned containing:

- `sdev`, a numeric vector of length `rank` containing the standard deviations of the first `rank` principal components.

- `rotation`, a numeric matrix with `rank` columns and `nrow(x)` rows, containing the first `rank` rotation vectors. This is only returned if `get.rotation=TRUE`.

- `x`, a numeric matrix with `rank` columns and `ncol(x)` rows, containing the scores for the first `rank` principal components. This is only returned if `get.pcs=TRUE`.

### Author(s)

Aaron Lun

### See Also

`runSVD` for the underlying SVD function.

`?BiocSingularParam` for details on the algorithm choices.

### Examples

    a <- matrix(rnorm(100000), ncol=20)
    str(out <- runPCA(a, rank=10))

[Package BiocSingular version 1.0.0 Index]