Perform Analysis and Create Visualizations of Proteins

Read Protein Data Bank (PDB) files, performs its analysis, and presents the result using different visualization types including 3D. The package also has additional capability for handling Virus Report data from the National Center for Biotechnology Information (NCBI) database. Nature Structural Biology 10, 980 (2003) . US National Library of Medicine (2021) < https://www.ncbi.nlm.nih.gov/datasets/docs/reference-docs/data-reports/virus/>.


protein8k

V0.0.1

Author: Simon Liles

Maintainer: Simon Liles, [email protected]

This is a package that can be used for the visual analysis of proteins.

This package is still in early Alpha. Expect significant and continuous changes for a while.

This README will also be updated with more information as the package evolves.

Download and Installation

The easiest way to download and install this package is through CRAN. Simply run the following command in your R Console.

install.packages("protein8k")

To download and install the development version into your R session is to use the devtool function install_github(). The development version is not recommended for most users because it may contain bugs.

You can copy and paste this code into your console and it should work. If there are any issues, please contact the package maintainer.

devtools::install_github("SimonLiles/protein8k")

If you want vignettes included from the GitHub install, use this code.

devtools::install_github("SimonLiles/protein8k", build_vignettes = TRUE)

Bugs

If you encounter any issues, please contact the package maintainer.

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("protein8k")

0.0.2 by Simon Liles, 9 months ago


Browse source code at https://github.com/cran/protein8k


Authors: Simon Liles [aut, cre]


Documentation:   PDF Manual  


CC0 license


Imports lattice, methods, magick, dplyr, grid, gridExtra, ggplot2, rjson, rlang, shiny

Suggests knitr, rmarkdown


See at CRAN