1.15.1版本的变化(2023-06-19)——解决useNames问题colSds(),导致测试抛出警告。版本变化1.9.1(2022-01-19)-更新版权年更新引用信息的变化版本1.7.3(2021-10-07)-消除更多的测试试图验证并行输出串行同行完全吻合。版本是1.7.2变化(2021-09-15)-删除测试检查顺序和并行调用scPCA()产生相同的输出,当BiocParallel SerialParam使用的是()。这是因为新BiocParallel随机数生成的版本1.28。1.5.3(2021-03-14)-更正更新版本的变化在装饰图案绘制问题:比较的和scPCA载荷。——添加pkgdown网站。——移动ScaledMatrix“进口”部分的描述。1.5.2版本的变化(2020-12-21)-添加LTLA / ScaledMatrix“遥控器”部分的描述。1.5.1版本的变化(2020-12-17)- scPCA()和其他内部函数现在可能利用ScaledMatrix对象类。这使得计算效率对比在分析大型数据集的协方差矩阵估计。 - 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