R is a free, open-source language and environment for statistics, data analysis and graphics. It is the de facto standard for statistical computing in research, with thousands of packages (including Bioconductor for bioinformatics) covering almost any analysis you’ll need.
R project ↗ | Download R from CRAN ↗
Why use R
- Free and reproducible — scripts document every step of your analysis.
- Comprehensive — from basic tests to mixed models, survival analysis and machine learning.
- Great graphics — publication-quality figures with ggplot2.
- Bioinformatics — Bioconductor for RNA-seq, microarrays, sequence analysis and more.
Getting started
- Install R from CRAN (Windows, macOS or Linux).
- Install RStudio / Posit Desktop for a friendlier editor and console.
- Install packages with
install.packages("ggplot2"), or Bioconductor packages viaBiocManager.
R vs point-and-click tools
If you want reproducibility, automation and full statistical flexibility, R is the best choice. If you prefer a graphical interface for routine tests and figures, GraphPad Prism is a common alternative; many labs use both.
Frequently asked questions
Is R free?
Yes, R is free and open-source, available for Windows, macOS and Linux from CRAN.
Do I need RStudio?
No, but RStudio (Posit) makes writing and running R much easier, especially when starting out.
Can R do bioinformatics?
Yes — the Bioconductor project provides hundreds of packages for genomics and other biological data.
