A hands-on bioinformatics learning tutorial

Main Content:

• Environment setup
• Prerequisite knowledge explanation
• Lab and Homework implementation from the Harvard Stat 115/215 course

I have incorporated my own understanding and modifications, and reproduced the analyses using Python and R. All analyses in this tutorial can be executed on an ordinary laptop (no server needed).

Each tutorial is organized as a directory, with readme.md as the main documentation. Most tutorials are accompanied by an equivalent Jupyter Notebook (.ipynb).

Examples in this tutorial are implemented in both Python and R.

Main Reference Course:

Introduction to Bioinformatics and Computational Biology (Harvard Stat 115/215)

• Original Course: https://liulab-dfci.github.io/bioinfo-combio/
• Teaching Materials: https://liulab-dfci.github.io/teaching
• Course Homework: https://github.com/7insong/stat115_hw

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Table of Contents

• Prerequisite 1 R with Anaconda and Jupyter

• Prerequisite 2 R Basics

• Prerequisite 3 Deploying Linux and Development Environment on Windows

• Chapter 1 RNA-Seq Data Processing and Analysis: Alignment, Quality Control, and Quantification

  • Section 1-1 STAR alignment

  • Section 1-2 RNA-Seq quality control

  • Section 1-3 RNA-Seq quantification

  • Section 1-4 Compare RSEM vs Salmon