Provides methods to analyze cluster alternatives based on multi-objective optimization of cluster validation indices. For details see Kraus et al. (2011) <doi:10.1007/s00180-011-0244-6>.

A statistical framework and analysis tool for open chromatin 
  analysis designed specifically for single cell ATAC-seq (Assay for 
  Transposase-Accessible Chromatin) data, after cell type/cluster 
  identification. These novel modules remove unwanted technical variation, 
  identify open chromatin, robustly models repeated measures in single cell 
  data, implement advanced statistical frameworks to model zero-inflation for 
  differential and co-accessibility analyses, and integrate with existing 
  databases and modules for downstream analyses to reveal biological insights. 
  MOCHA provides a statistical foundation for complex downstream analysis to 
  help advance the potential of single cell ATAC-seq for applied studies. 
  Methods for zero-inflated statistics are as described in: 
  Ghazanfar, S., Lin, Y., Su, X. et al. (2020) <doi:10.1038/s41592-020-0885-x>.
  Pimentel, Ronald Silva, "Kendall's Tau and Spearman's Rho for Zero-Inflated 
  Data" (2009) <https://scholarworks.wmich.edu/dissertations/721/>.

The two main functionalities of this package are creating
    mock objects (functions) and selectively intercepting calls to a given
    function that originate in some other function. It can be used with
    any testing framework available for R. Mock objects can be injected
    with either this package's own stub() function or a similar
    with_mock() facility present in the 'testthat' package.

Provides a means to mock a package function, i.e.,
    temporarily substitute it for testing. Designed as a drop-in
    replacement for the now deprecated 'testthat::with_mock()' and
    'testthat::local_mock()'.

With the deprecation of mocking capabilities shipped with
    'testthat' as of 'edition 3' it is left to third-party packages to replace
    this functionality, which in some test-scenarios is essential in order to
    run unit tests in limited environments (such as no Internet connection).
    Mocking in this setting means temporarily substituting a function with a
    stub that acts in some sense like the original function (for example by
    serving a HTTP response that has been cached as a file). The only exported
    function 'with_mock()' is modeled after the eponymous 'testthat' function
    with the intention of providing a drop-in replacement.