Instead of nesting function calls, annotate and transform 
    functions using "#." comments.

A 'tufte'-alike style for 'rmarkdown'.
 A modern take on the 'Tufte' design for pdf and html vignettes,
 building on the 'tufte' package with additional contributions
 from the 'knitr' and 'ggtufte' package, and also acknowledging
 the key influence of 'envisioned css'.

Generate a palette of tints, shades or both from a single colour.

Palettes generated from Tintin covers. There is one palette per
  cover, with a total of 24 palettes of 5 colours each. Includes functions to
  interpolate colors in order to create more colors based on the provided
  palettes.The data is based on Cyr, et al. (2004) <doi:10.1503/cmaj.1041405>
  and Wikipedia <https://en.wikipedia.org/wiki/The_Adventures_of_Tintin>.

The Gene Expression Omnibus (<https://www.ncbi.nlm.nih.gov/geo/>) and The Cancer Genome Atlas (<https://portal.gdc.cancer.gov/>) are widely used medical public databases. Our platform integrates routine analysis and visualization tools for expression data to provide concise and intuitive data analysis and presentation.

Adds some functions to help in your coding etiquette.
    'tinycodet' primarily focuses on 4 aspects.
    1) Safer decimal (in)equality testing,
    standard-evaluated alternatives to with() and aes(),
    and other functions for safer coding.
    2) A new package import system,
    that attempts to combine the benefits of using a package without attaching it,
    with the benefits of attaching a package.
    3) Extending the string manipulation capabilities of the 'stringi' R package.
    4) Reducing repetitive code.
    Besides linking to 'Rcpp', 'tinycodet' has only one other dependency, namely 'stringi'.

Assign, extract, or remove variable labels from R vectors.
  Lightweight and dependency-free.

Provides utilities to create and use lenses to simplify data
    manipulation. Lenses are composable getter/setter pairs that provide a
    functional approach to manipulating deeply nested data structures, e.g.,
    elements within list columns in data frames. The implementation is based on
    the earlier 'lenses' R package <https://github.com/cfhammill/lenses>,
    which was inspired by the Haskell 'lens' package by Kmett (2012)
    <https://github.com/ekmett/lens>, one of the most widely referenced
    implementations of lenses. For additional background and history on the
    theory of lenses, see the 'lens' package wiki:
    <https://github.com/ekmett/lens/wiki/History-of-Lenses>.