Computes standard error and confidence interval of various descriptive statistics under 
        various designs and sampling schemes. The main function, superb(), return a plot. It can 
        also be used to obtain a dataframe with the statistics and their precision intervals 
        so that other plotting environments (e.g., Excel)
        can be used. See Cousineau and colleagues (2021) <doi:10.1177/25152459211035109> 
        or Cousineau (2017) <doi:10.5709/acp-0214-z> for a review as well as Cousineau (2005)
        <doi:10.20982/tqmp.01.1.p042>, Morey (2008) <doi:10.20982/tqmp.04.2.p061>, Baguley (2012)
        <doi:10.3758/s13428-011-0123-7>, Cousineau & Laurencelle (2016) <doi:10.1037/met0000055>,
        Cousineau & O'Brien (2014) <doi:10.3758/s13428-013-0441-z>, Calderini & Harding 
        <doi:10.20982/tqmp.15.1.p001> for specific references.
        The documentation is available at <https://dcousin3.github.io/superb/> .

Biclusters are submatrices in the data matrix which
        satisfy certain conditions of homogeneity. Package contains
        functions for generating robust biclusters with respect to the
        initialization parameters for a given bicluster solution
        contained in a bicluster set in data, the procedure is also
        known as ensemble biclustering. The set of biclusters is
        evaluated based on the similarity of its elements (the
        overlap), and afterwards the hierarchical tree is constructed
        to obtain cut-off points for the classes of robust biclusters.
        The result is a number of robust (or super) biclusters with
        none or low overlap.

Aggregates large single-cell data into metacell dataset by merging together gene expression of very similar cells. 'SuperCell' uses 'velocyto.R' <doi:10.1038/s41586-018-0414-6> <https://github.com/velocyto-team/velocyto.R> for RNA velocity. We also recommend installing 'scater' Bioconductor package <doi:10.18129/B9.bioc.scater> <https://bioconductor.org/packages/release/bioc/html/scater.html>.