R: Principal components analysis

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

Examples

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

[Package BiocSingular version 1.4.0 Index]