Enrich your 'ggplots' with group-wise comparisons.
    This package provides an easy way to indicate if two groups are
    significantly different. Commonly this is shown by a bracket on top
    connecting the groups of interest which itself is annotated with the
    level of significance (NS, *, **, ***).  The package provides a single
    layer (geom_signif()) that takes the groups for comparison and the
    test (t.test(), wilcox.text() etc.) as arguments and adds the
    annotation to the plot.

knitr, rmarkdown, testthat, vdiffr (>= 1.0.2)

Constantin Ahlmann-Eltze [aut, cre, ctb]
    (<https://orcid.org/0000-0002-3762-068X>, @const_ae),
  Indrajeet Patil [aut, ctb] (<https://orcid.org/0000-0003-1995-6531>,
    @patilindrajeets)

Functions which provide a range of axis labeling algorithms.

Exploratory analysis for two-color spotted microarray data

Yee Hwa (Jean) Yang <jeany@maths.usyd.edu.au> with contributions
        from Agnes Paquet and Sandrine Dudoit.

Yee Hwa (Jean) Yang <jean@biostat.ucsf.edu>

Class definitions for two-color spotted microarray data.
        Fuctions for data input, diagnostic plots, normalization and
        quality checking.

maClasses.R maGet.R maSet.R maPrint.R maSubset.R maBind.R
maComp.R maDots.R maInput.R maNorm.R maOutput.R maWidget.R
maPlots.R maAnnotate.R maRankGenes.R maSMA.R maSearch.R
maWrap.R

Tools for Splitting, Applying and Combining Data

person("Hadley", "Wickham", , "hadley@rstudio.com", role = c("aut", "cre"))

A set of tools that solves a common set of problems: you need
    to break a big problem down into manageable pieces, operate on each
    piece and then put all the pieces back together.  For example, you
    might want to fit a model to each spatial location or time point in
    your study, summarise data by panels or collapse high-dimensional
    arrays to simpler summary statistics. The development of 'plyr' has
    been generously supported by 'Becton Dickinson'.

abind, covr, doParallel, foreach, iterators, itertools,
tcltk, testthat