RunPCA {ILoReg} | R Documentation

## PCA transformation of the joint probability matrix

### Description

Perform the PCA transformation of the joint probability matrix, which reduces the dimensionality from k*L to p

### Usage

    RunPCA.SingleCellExperiment(object, p, scale, threshold)

    ## S4 method for signature 'SingleCellExperiment'
    RunPCA(object, p = 50, scale = FALSE, threshold = 0)

### Arguments

`object` | object of `SingleCellExperiment` class
`p` | a positive integer denoting the number of principal components to calculate and select. Default is `50`.
`scale` | a logical specifying whether the probabilities should be standardized to unit-variance before running PCA. Default is `FALSE`.
`threshold` | a thresfold for filtering out ICP runs before PCA with the lower terminal projection accuracy below the threshold. Default is `0`.

### Value

object of `SingleCellExperiment` class

### Examples

    library(SingleCellExperiment)
    sce <- SingleCellExperiment(assays = list(logcounts = pbmc3k_500))
    sce <- PrepareILoReg(sce)
    ## These settings are just to accelerate the example, use the defaults.
    sce <- RunParallelICP(sce,L=2,threads=1,C=0.1,k=5,r=1)
    sce <- RunPCA(sce,p=5)

[Package ILoReg version 1.2.0 Index]