List of R software and tools

Short description: R software and development tools

This is a list of software and programming tools for the R programming language, including IDEs, package managers, libraries, debugging tools, numerical and scientific computing tools, and related projects.

Integrated development environments (IDEs) and editors

• Emacs Speaks Statistics (ESS) — Emacs interface for R and other statistical software
• Jupyter — supports R through IRkernel
• RKWard — KDE/Qt-based IDE and GUI for R
• RStudio — popular cross-platform IDE for R
• StatET — Eclipse-based IDE
• Visual Studio Code — supports R via extensions (R Tools for Visual Studio)

Graphical user interfaces

• Deducer — GUI front-end and data analysis package
• jamovi — GUI statistical environment built on R for data analysis and performing statistical tests
• Java GUI for R — cross-platform R console, script editor, and spreadsheet/data view.
• Rattle GUI — data mining GUI for R
• R Commander (Rcmdr) — basic GUI for statistics in R, often used for teaching and introductory work.

Implementations of R

• CXXR — experimental R engine with modernized C++ codebase
• FastR — R language implementation on the GraalVM
• GNU R — main implementation of R, maintained by the R Core Team, and distributed as part of the GNU Project.
• pqR — “pretty quick R”
• Renjin — JVM-based interpreter for R

R packages

• Bioconductor — repository for bioinformatics and computational biology R packages
• CRAN — Comprehensive R Archive Network, primary repository for R packages.
• devtools — simplifies R package development
• Knitr — integration of R code into LaTeX, LyX, HTML, Markdown, AsciiDoc, and reStructuredText documents.
• Packrat — dependency management system
• renv — project-specific package management system
• R CMD build / R CMD check — R package build and validation tools
• Tidyverse — Ggplot2, dplyr, and other packages.

Mathematical and numerical libraries

• lme4 — linear mixed-effects models
• Matrix — sparse and dense matrix computations
• mgcv — generalized additive models
• nlme — nonlinear mixed-effects models
• numDeriv — numerical derivatives
• optim — built-in optimization functions
• optimx – provides a replacement and extension of the optim
• Rmpfr — multiple-precision floating-point arithmetic

Scientific and statistical libraries

• dplyr — data manipulation toolkit
• edgeR — differential expression analysis of RNA-seq data
• forecast — time series forecasting
• ggplot2 — data visualization based on the grammar of graphics
• phyloseq — analysis of microbiome census data
• shiny — interactive web applications
• survival — survival analysis
• tidyr — tidy data reshaping

Debugging and performance tools

• bench – accurately benchmark and analyze execution times
• lineprof — line-by-line profiling tool
• microbenchmark — benchmarking
• profvis — interactive R profiler
• Rcpp — integration of R and C++ for performance
• Rprof — built-in R profiler

Parallel and high-performance computing

• BiocParallel — parallel evaluation framework for R, used across Bioconductor packages.
• doParallel – provides a parallel backend for the foreach package, enabling easy parallel execution of R code.
• foreach — looping construct for parallel execution
• future — unified parallel and distributed computing
• parallel — built-in R package for parallel processing
• Rmpi — R interface to the Message Passing Interface
• snow — simple network of workstations

Machine learning and AI libraries

• caret — training and tuning for machine learning models
• keras — R interface to Keras deep learning
• mlbench — collection of artificial and real-world benchmark datasets for evaluating machine learning algorithms
• mlr — machine learning
• mlr3 — modern successor to mlr
• randomForest — ensemble learning using random forests
• tidymodels — collection of R packages for machine learning and modeling, designed with tidyverse principles.
• torch — R interface to PyTorch
• xgboost — gradient boosting framework with R bindings

Documentation and code analysis tools

• covr — test coverage
• lintr — static code analysis
• roxygen2 — documentation generation for R packages
• styler — code formatter for R scripts and packages

Testing frameworks

• checkmate — fast argument checks and assertions for R functions
• RUnit — implementing a standard Unit Testing framework
• testthat — unit testing framework
• tinytest — lightweight unit testing framework

See also

• Data science
• gretl — open-source software for econometrics that can integrate with R
• List of numerical libraries
• Lists of programming software development tools by language
• Statistical software

External links

• awesome-R – GitHub list of R software
• The Comprehensive R Archive Network (CRAN)
• Bioconductor project
• RStudio / Posit IDE
• Jupyter Project