List of R software and 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

Graphical user interfaces

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”
  • RenjinJVM-based interpreter for R

R packages

Mathematical and numerical libraries

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
  • xgboostgradient boosting framework with R bindings

Documentation and code analysis tools

Testing frameworks