RunPCA: PCA transformation of the joint probability matrix

RunPCAR 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)



elolab/ILoReg documentation built on March 28, 2022, 1:17 a.m.