Get principal component information to a tibble using PCA
get_reduced_dimensions_PCA_bulk(
.data,
.element = NULL,
.feature = NULL,
.value = NULL,
.dims = 2,
top = Inf,
of_elements = TRUE,
transform = NULL,
scale = FALSE,
...
)
A tibble
A column symbol. The column that is used to calculate distance (i.e., normally elements)
A column symbol. The column that is represents entities to cluster (i.e., normally genes)
A column symbol with the value the clustering is based on (e.g., `count`)
A integer vector corresponding to principal components of interest (e.g., 1:6)
An integer. How many top genes to select
A boolean
A function to use to tranforma the data internalli (e.g., log1p)
A boolean
Further parameters passed to the function prcomp
A tibble with additional columns