NEWS

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scPCA 1.15.1 (2023-06-19)

• Address useNames issue in colSds() that caused tests to throw warnings.

scPCA 1.9.1 (2022-01-19)

• Updating copyright years
• Updating citation information

scPCA 1.7.3 (2021-10-07)

• Removing more tests attempting to verify that parallelized outputs perfectly match their serial counterparts.

scPCA 1.7.2 (2021-09-15)

• Removing tests checking that sequential and parallel calls to scPCA() produce identical outputs when BiocParallel's SerialParam() is used. This due to new handing of random number generation in BiocParallel version 1.28.

scPCA 1.5.3 (2021-03-14)

• Updating plotting issue in vignette: comparison of cPCA and scPCA loadings.
• Adding pkgdown site.
• Moving ScaledMatrix to "imports" section of DESCRIPTION.

scPCA 1.5.2 (2020-12-21)

• Adding LTLA/ScaledMatrix to "Remotes" section of DESCRIPTION.

scPCA 1.5.1 (2020-12-17)

• 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.

scPCA 1.3.10 (2020-10-16)

• Implementing suggested improvements from Aaron Lun.

scPCA 1.3.9 (2020-10-12)

• scPCA() now accepts DelayedMatrix objects as target and background datasets.

scPCA 1.3.8 (2020-09-01)

• Minor bug fixes

scPCA 1.3.6 (2020-08-30)

• Fixed issue where n_centers was required when only one penalty and contrast term were provided
• Users can now pass factors and character vectors to the clusters argument.

scPCA 1.3.5 (2020-08-18)

• Fixed citations in docs
• Provided more detailed warning when RSpectra::eigs_sym() fails to converge
• Included arguments in scPCA() to control RSpectra::eigs_sym() convergence: error tolerance and max number of iterations

scPCA 1.3.4 (2020-08-12)

• Replaced calls to 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.
• Replaced calls to stats::cov() by coop::covar() to speed up computation of large sample covariance matrices.
• In future updates, we'd like to explore using the DelayedArray framework to support the analysis of larger datasets.

scPCA 1.3.3 (2020-08-08)

• The n_centers argument no longer matters when When the contrasts argument is of length 1 and the penalty term is set to 0.
• Users can now pass in their own cluster labels

scPCA 1.3.2 (2020-08-05)

• Updated scPCA() function documentation
• Corrected spelling mistakes

scPCA 1.1.15 (2020-06-02)

• Fixing Travis CI settings

scPCA 1.1.14 (2020-04-26)

• Fixing broken link in an internal function documentation page.

scPCA 1.1.12 (2020-04-21)

• Updated citations
• Fixed typos in documentation

scPCA 1.1.11 (2020-02-02)

• Added more SPCA algorithm options
  • SPCA via variable projection
  • Randomized SPCA via variable projection
• New vignette section comparing performance of SPCA algorithms
• Improvements to code coverage

scPCA 1.1.5 (2020-01-18)

• Fixed issue with matrix normalization
• Misc. bug fixes
• Improvements to code coverage

scPCA 1.1.2 (2020-01-08)

• Added hierarchical clustering options for clustering based cross-validation

scPCA 0.99.0 (2019-09-13)

• Submitted to Bioconductor