Run PCA — run_pca • phenomix

Run Principal Components Analysis (PCA).

run_pca(
  mat,
  transpose = TRUE,
  center = TRUE,
  scale. = FALSE,
  rank. = NULL,
  ...
)

Arguments

mat	Matrix to run PCA on.
transpose	Whether to transpose the matrix first.
center	a logical value indicating whether the variables should be shifted to be zero centered. Alternately, a vector of length equal the number of columns of `x` can be supplied. The value is passed to `scale`.
scale.	a logical value indicating whether the variables should be scaled to have unit variance before the analysis takes place. The default is `FALSE` for consistency with S, but in general scaling is advisable. Alternatively, a vector of length equal the number of columns of `x` can be supplied. The value is passed to `scale`.
rank.	optionally, a number specifying the maximal rank, i.e., maximal number of principal components to be used. Can be set as alternative or in addition to `tol`, useful notably when the desired rank is considerably smaller than the dimensions of the matrix.
...	Additional parameters passed to prcomp.