CHANGES IN VERSION ccImpute 1.6.1
-----------------------------------
+ Performance Optimizations:
    o Significantly enhanced calculation speed for Pearson and Spearman 
      correlation matrices, including weighted versions.
    o Leveraged the Irlba package for efficient truncated Singular Value 
      Decomposition (SVD) computation.
    o Optimized imputation by limiting the number of singular components while 
      maintaining accuracy of downstream analysis, with adjustable maximum 
      limits based on dataset size.
    o Optimized the identification of dropout events.
    o Introduced a fast dropout calculation method based on non-zero expression
      value means, preserving imputation performance, and great improving 
      runtime speed.
    o Replaced SIMLR with Tracy-Widom Bound for estimating k when not provided,
      resulting in faster calculations and improved empirical performance.
+ Expanded Functionality:
    o Added support for sparse matrices in dgCmatrix format, improving memory 
      efficiency.
+ Documentation Enhancements:
    o Expanded the vignette with detailed guidance and practical examples for
      maximizing the package's value and computational speed.
    o Included comparative benchmarking against previous releases in the
      vignette, demonstrating the performance improvements.
+ Overall Impact:
    o The ccImpute package is now substantially faster and more efficient.
    o Users can expect a smoother experience with improved documentation and
      expanded functionality.
     
CHANGES IN VERSION ccImpute 0.99.0:
-----------------------------------
    o The first version 0.99.0 is submitted to Bioconductor