Changes in version 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.

                 Changes in version 1.5.2 (2020-12-21)                  

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

                 Changes in version 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.

                 Changes in version 1.3.10 (2020-10-16)                 

  - Implementing suggested improvements from Aaron Lun.

                 Changes in version 1.3.9 (2020-10-12)                  

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

                 Changes in version 1.3.8 (2020-09-01)                  

  - Minor bug fixes

                 Changes in version 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.

                 Changes in version 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

                 Changes in version 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.

                 Changes in version 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

                 Changes in version 1.3.2 (2020-08-05)                  

  - Updated scPCA() function documentation
  - Corrected spelling mistakes

                 Changes in version 1.1.15 (2020-06-02)                 

  - Fixing Travis CI settings

                 Changes in version 1.1.14 (2020-04-26)                 

  - Fixing broken link in an internal function documentation page.

                 Changes in version 1.1.12 (2020-04-21)                 

  - Updated citations
  - Fixed typos in documentation

                 Changes in version 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

                 Changes in version 1.1.5 (2020-01-18)                  

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

                 Changes in version 1.1.2 (2020-01-08)                  

  - Added hierarchical clustering options for clustering based
    cross-validation

                 Changes in version 0.99.0 (2019-09-13)                 

  - Submitted to Bioconductor