README.md

In LieberInstitute/shinycsv: Explore a table interactively in a shiny application

shinycsv

This package allows interactive explorations of CSV files, data.frame objects stored in a Rdata file (only one data.frame stored), or other types of table files. You can view this shiny app deployed at libd.shinyapps.io/shinycsv. If you are interested in the showcase mode, then check out libd.shinyapps.io/shinycsv-showcase.

The vignette for this package is available at LieberInstitute/shinycsv.

Installation instructions

Get the latest stable R release from CRAN. Then install shinycsv from GitHub with:

BiocManager::install("LieberInstitute/shinycsv")

Citation

Below is the citation output from using citation('shinycsv') in R. Please run this yourself to check for any updates on how to cite shinycsv.

print(citation("shinycsv"), bibtex = TRUE)
#> To cite package 'shinycsv' in publications use:
#> 
#>   Collado-Torres L, Semick S, Jaffe AE (2020). _shinycsv: Explore a
#>   table interactively in a shiny application_. R package version
#>   0.99.9, <https://github.com/LieberInstitute/shinycsv>.
#> 
#> A BibTeX entry for LaTeX users is
#> 
#>   @Manual{,
#>     title = {shinycsv: Explore a table interactively in a shiny application},
#>     author = {Leonardo Collado-Torres and Stephen Semick and Andrew E. Jaffe},
#>     year = {2020},
#>     note = {R package version 0.99.9},
#>     url = {https://github.com/LieberInstitute/shinycsv},
#>   }

Please note that the shinycsv was only made possible thanks to many other R and bioinformatics software authors, which are cited either in the vignettes and/or the paper(s) describing this package.

Code of Conduct

Please note that the shinycsv project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

Development tools

• Continuous code testing is possible thanks to GitHub actions through usethis, remotes, and rcmdcheck customized to use Bioconductor’s docker containers and BiocCheck.
• Code coverage assessment is possible thanks to codecov and covr.
• The documentation website is automatically updated thanks to pkgdown.
• The code is styled automatically thanks to styler.
• The documentation is formatted thanks to devtools and roxygen2.

For more details, check the dev directory.

This package was developed using biocthis.

LieberInstitute/shinycsv documentation built on May 8, 2023, 7:27 p.m.