Get-started-with-R-for-Biologists

• Introduction
• RStudio
• Basics
• Tidyverse
• Data Science
• Applications
• Other

Introduction

This repository contains resources on getting started with R for biologists. R is a language and environment for statistical computing and graphics. It is widely used for a variety of statistical analysis (i.e., linear and nonlinear modeling, classical statistical tests, clustering, etc.). R is freely available and has a large collection of developed packages of different tools. One such is the Tidyverse, which is a collection of data science tools.

RStudio

• Introduction to R and Rstudio: Harvard Bioinformatics
• Introduction to R and RStudio: Alex Lemonade Stand
• Introduction to R and RStudio: Yale CRC
• Introduction to R and RStudio
• 23 RStudio Tips, Tricks, and Shortcuts
• My favorite RStudio tips and tricks

Basics

• R Syntax and Data Structures
• Functions in R
• Data wrangling: vectors and factors
• Exploratory data analysis
• Exploratory data analysis in R

Tidyverse

• Data Wrangling with Tidyverse
• Tidy data
• Data Visualization with ggplot2

Data Science

• Principal Component Analysis
• Non-negative Matrix Factorization
• K-means clustering
• Common statistical tests are linear models (or: how to teach stats)
• cBioPortal

Applications

• RNA-seq
• scRNA-seq

Cheatsheets

• Base R
• RStudio IDE
• ggplot2
• Stats

Other

• Learning Bioinformatics At Home Some resources gathered by the Harvard Informatics group and other contributors to help people learn bioinformatics tools (basic and specialized) at home.
• https://bookdown.org List of books written with bookdown for learning R.
• R Bootcamp
• Learning Statistics with R
• Efficient R programming
• An Introduction to Statistical Learning with Applications in R
• Another Book on Data Science
• Data Analysis and Prediction Algorithms with R
• CFDE