Approximate SVD is performed using the implementation from irlba
, randomized SVD is performed using the implementation from rsvd
.
randomized_svd(object, exprs_values, n_dims, features = NULL, skip = NULL, seed = NULL, ...) approximate_svd(object, exprs_values, n_dims, features = NULL, skip = NULL, seed = NULL, ...)
object | A SingleCellExperiment object. |
---|---|
exprs_values | String indicating which assay contains the data that should be used to perform SVD. |
n_dims | The number of approximate singular values to calculate. |
features | A character vector (of feature names), a logical vector or numeric vector (of indices) specifying the features to use for SVD. The default of NULL will use all features. |
skip | A numeric vector indicating which singular values to set to zero (and remove). |
seed | A numeric seed to initialize the random number generator. |
... |
A matrix of dimension ncol(object)
x dims(object) - length(skip)
.