Modified versions of the lag() and summary() functions: glag() and gsummary(). The prefix 'g' is a reminder of who to blame if things do not work as they should.

It is not very easy to define segments for y-axis in a 'ggplot2' plot. gg.gap() function in this package can carry it out.

Providing publication-ready graphs for Multiple sequence alignment. Moreover, it provides a unique solution for visualizing the multiple sequence alignment without the need to do the alignment in each run which is a big limitation in other available packages.

'D&D' alignment charts show 9 boxes with values for good
    through evil and values for chaotic through lawful. This package
    easily creates these alignment charts from user-provided image paths
    and alignment values.

Extra geoms and scales for 'ggplot2', including geom_cloud(),
  a Normal density cloud replacement for errorbars;
  transforms ssqrt_trans and pseudolog10_trans, which are loglike but 
  appropriate for negative data; interp_trans() and warp_trans() which
  provide scale transforms based on interpolation;
  and an infix compose operator for scale transforms.

Alluvial plots use variable-width ribbons and stacked bar plots to
    represent multi-dimensional or repeated-measures data with categorical or
    ordinal variables; see Riehmann, Hanfler, and Froehlich (2005)
    <doi:10.1109/INFVIS.2005.1532152> and Rosvall and Bergstrom (2010)
    <doi:10.1371/journal.pone.0008694>.
    Alluvial plots are statistical graphics in the sense of Wilkinson (2006)
    <doi:10.1007/0-387-28695-0>; they share elements with Sankey diagrams and
    parallel sets plots but are uniquely determined from the data and a small
    set of parameters. This package extends Wickham's (2010)
    <doi:10.1198/jcgs.2009.07098> layered grammar of graphics to generate
    alluvial plots from tidy data.

The R package 'ggplot2' is a plotting system based on the grammar of graphics.
    'GGally' extends 'ggplot2' by adding several functions
    to reduce the complexity of combining geometric objects with transformed data.
    Some of these functions include a pairwise plot matrix, a two group pairwise plot
    matrix, a parallel coordinates plot, a survival plot, and several functions to
    plot networks.