Run a simple PCA analysis — runPCA • shinyngs

Common function for PCA-using parts of the app

Usage

runPCA(matrix, do_log = TRUE, scale_features = FALSE)

matrix: Matrix (not logged)
do_log: Boolean- apply log transform to input matrix?
scale_features: Boolean, passed to prcomp()'s scale. argument to scale each feature to unit variance before running the PCA. Defaults to FALSE, matching DESeq2::plotPCA()'s convention for variance-stabilised input: VST/rlog transforms already equalise per-feature variance, so further scaling mostly up-weights noisy, near-constant features rather than revealing structure. Set to TRUE for matrices without a variance-stabilising transform, where features can otherwise dominate the PCA purely by having larger scale. (Unrelated to interactive_heatmap's scale argument, which selects row/column/none display scaling.)

pca Output of the prcomp function

runPCA(mymatrix)
#> Error in runPCA(mymatrix): could not find function "runPCA"