bpContrastiveCov {scPCA} | R Documentation |
Parallelized Contrastive Covariance Matrices
Description
Compute the list of contrastive covariance matrices in parallel
using bplapply
.
Usage
bpContrastiveCov(
target,
background,
contrasts,
center,
scale,
scaled_matrix = FALSE
)
Arguments
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 .
|
Value
A list of contrastive covariance matrices. Each element has an
associated contrastive parameter in the contrasts
vector.
[Package
scPCA version 1.8.0
Index]