The extensive range of functions provided by this package makes it possible to draw highly versatile sequence logos. Features include, but not limited to, modifying colour schemes and fonts used to draw the logo, generating multiple logo plots, and aiding the visualisation with annotations. Sequence logos can easily be combined with other plots 'ggplot2' plots.

A set of wrapper functions that mainly re-produces most of the 
  sequence plots rendered with TraMineR::seqplot(). Whereas 'TraMineR' uses base 
  R to produce the plots this library draws on 'ggplot2'. 
  The plots are produced on the basis of a sequence object defined  
  with TraMineR::seqdef(). The package automates the reshaping and plotting 
  of sequence data. Resulting plots are of class 'ggplot', i.e. components 
  can be added and tweaked using '+' and regular 'ggplot2' functions.

A collection of Geoms for R's 'ggplot2' library. geom_shadowpath(), geom_shadowline(), 
    geom_shadowstep() and geom_shadowpoint() functions draw a shadow below lines to make busy plots more 
    aesthetically pleasing. geom_glowpath(), geom_glowline(), geom_glowstep() and geom_glowpoint() add a 
    neon glow around lines to get a steampunk style.

The grammar of graphics as shown in 'ggplot2' has provided
  an expressive API for users to build plots. 'ggside' extends 'ggplot2' 
  by allowing users to add graphical information about one of the main panel's
  axis using a familiar 'ggplot2' style API with tidy data. This package is
  particularly useful for visualizing metadata on a discrete axis, or summary
  graphics on a continuous axis such as a boxplot or a density distribution.

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.