PCA

Source: R/DimReduction.R

Select top variable genes and perform prcomp

PCA(expression.matrix = NULL, ngenes = 1500, scaling = TRUE, npcs = 50)

Arguments

expression.matrix

An expression matrix, with genes in rows
ngenes

number of genes used for clustering calculations.
scaling

a logical of whether we want to scale the matrix
npcs

an integer specifying the number of principal components to use.

Value

a list containing PCA results and variance explained

Examples

day2 <- day_2_cardio_cell_sample
mixedpop1 <-new_scGPS_object(ExpressionMatrix = day2$dat2_counts, 
    GeneMetadata = day2$dat2geneInfo, CellMetadata = day2$dat2_clusters)
t <-PCA(expression.matrix=assay(mixedpop1))

#> Preparing PCA inputs using the top 1500 genes ...
#> Computing PCA values...