Get and plot PCA components for a SCtkE object

Source: R/getPCA.R

Selects the 500 most variable genes in the SCE, performs PCA based on them and stores the values in the reducedDims slot of the SCE object.

getPCA(inSCE, useAssay = "logcounts", reducedDimName = "PCA")

Arguments

inSCE

Input SCtkExperiment object. Required

useAssay

Indicate which assay to use for PCA. Default is "counts"

reducedDimName

Store the PCA data with this name. The default is PCA. The toolkit will store data with the pattern <ASSAY>_<ALGORITHM>.

Value

A SCtkE object with the specified reducedDim and pcaVariances updated

Examples

data("mouseBrainSubsetSCE")
#add a CPM assay
assay(mouseBrainSubsetSCE, "cpm") <- apply(assay(mouseBrainSubsetSCE,
                                                 "counts"),
                                           2, function(x) {
                                             x / (sum(x) / 1000000)
                                           })
mouseBrainSubsetSCE <- getPCA(mouseBrainSubsetSCE,
                              useAssay = "cpm",
                              reducedDimName = "PCA_cpm")
reducedDims(mouseBrainSubsetSCE)
#> List of length 5
#> names(5): PCA_counts PCA_logcounts TSNE_counts TSNE_logcounts PCA_cpm