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

knitr::opts_chunk$set(
    collapse = TRUE,
    comment = "#>",
    fig.path = "man/figures/README-",
    out.width = "100%"
)

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)

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 r BiocStyle::CRANpkg('usethis'), r BiocStyle::CRANpkg('remotes'), and r BiocStyle::CRANpkg('rcmdcheck') customized to use Bioconductor's docker containers and r BiocStyle::Biocpkg('BiocCheck').
Code coverage assessment is possible thanks to codecov and r BiocStyle::CRANpkg('covr').
The documentation website is automatically updated thanks to r BiocStyle::CRANpkg('pkgdown').
The code is styled automatically thanks to r BiocStyle::CRANpkg('styler').
The documentation is formatted thanks to r BiocStyle::CRANpkg('devtools') and r BiocStyle::CRANpkg('roxygen2').