Reproducibility is essential to the progress of research, yet achieving it remains elusive even in computational fields. Continuous Integration (CI) platforms offer a powerful way to launch automated workflows to check and document code, but often require considerable time, effort, and technical expertise to setup. We therefore developed the rworkflows suite to make robust CI workflows easy and freely accessible to all R package developers. rworkflows consists of 1) a CRAN/Bioconductor-compatible R package template, 2) an R package to quickly implement a standardised workflow, and 3) a centrally maintained GitHub Action.
|Depends:||R (≥ 4.1)|
|Imports:||stats, here, yaml, utils, desc, badger, renv, tools, methods, BiocManager, data.table|
|Suggests:||markdown, rmarkdown, remotes, knitr, covr, testthat (≥ 3.0.0), htmltools, jsonlite, BiocStyle, BiocPkgTools, biocViews, reticulate, rvest|
|Author:||Brian Schilder [aut, cre], Alan Murphy [aut, ctb], Nathan Skene [aut]|
|Maintainer:||Brian Schilder <brian_schilder at alumni.brown.edu>|
|Citation:||rworkflows citation info|
|CRAN checks:||rworkflows results|
|Windows binaries:||r-devel: rworkflows_1.0.0.zip, r-release: rworkflows_1.0.0.zip, r-oldrel: rworkflows_1.0.0.zip|
|macOS binaries:||r-release (arm64): rworkflows_1.0.0.tgz, r-oldrel (arm64): rworkflows_1.0.0.tgz, r-release (x86_64): rworkflows_1.0.0.tgz, r-oldrel (x86_64): rworkflows_0.99.5.tgz|
|Old sources:||rworkflows archive|
|Reverse suggests:||EWCE, orthogene|
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