scPCA()
function documentationn_centers
argument no longer matters when When the contrasts argument is of length 1 and the penalty term is set to 0.base::eigen()
by RSpectra::eigs_sym()
to speed up eigendecompositions of contrastive covariance matrices. cPCA is now performed much more quickly when only wishing to compute a handful of leading contrastive principal components.stats::cov()
by coop::covar()
to speed up computation of large sample covariance matrices.DelayedArray
framework to support the analysis of larger datasets.RSpectra::eigs_sym()
fails to convergescPCA()
to control RSpectra::eigs_sym()
convergence: error tolerance and max number of iterationsn_centers
was required when only one penalty and contrast term were providedscPCA()
now accepts DelayedMatrix
objects as target and background datasets.scPCA()
and other internal functions may now take advantage of the
ScaledMatrix
object class. This allows more computationally efficient
contrastive covariance matrix estimation when analyzing large datasets.safeColScale()
now used MatrixGenerics
to handle feature standardization.LTLA/ScaledMatrix
to "Remotes" section of DESCRIPTION
.pkgdown
site.ScaledMatrix
to "imports" section of DESCRIPTION
.scPCA()
produce identical outputs when BiocParallel
's SerialParam()
is used. This
due to new handing of random number generation in BiocParallel
version 1.28.useNames
issue in colSds()
that caused tests to throw warnings.Add the following code to your website.
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