bpContrastiveCov: Parallelized Contrastive Covariance Matrices
In PhilBoileau/scPCA: Sparse Contrastive Principal Component Analysis

bpContrastiveCov

R Documentation

Parallelized Contrastive Covariance Matrices

Compute the list of contrastive covariance matrices in parallel using bplapply.

bpContrastiveCov(
  target,
  background,
  contrasts,
  center,
  scale,
  scaled_matrix = FALSE
)

`target`	The target (experimental) data set, in a standard format such as a `data.frame` or `matrix`.
`background`	The background data set, in a standard format such as a `data.frame` or `matrix`.
`contrasts`	A `numeric` vector of the contrastive parameters.
`center`	A `logical` indicating whether the target and background data sets should be centered to mean zero.
`scale`	A `logical` indicating whether the target and background data sets should be scaled to unit variance.
`scaled_matrix`	A `logical` indicating whether to output a `ScaledMatrix` object. The centering and scaling procedure is delayed until later, permitting more efficient matrix multiplication and row or column sums downstream. However, this comes at the at the cost of numerical precision. Defaults to `FALSE`.