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RNA-Seq Data Analysis


This RNA-Seq workshop aims to get you started with your own RNA-seq analysis and assumes you are already familiar with the basics of bash and R.


Lesson Overview
1. Background General overview of a RNA-Seq workflow
2. Quality Assessment Assess the quality of data, How to use FastQC and MultiQC
3. Trimming and Filtering How to remove adapter sequences
4. Mapping and Count Align/Map reads back to genome and number of reads from each sample that originated from that gene.
5. Differential Expression Analysis Differential expression analysis with R
6. Over-representation analysis Determine whether known biological functions or processes are over-represented (= enriched) in an experimentally-derived gene list
Supplementary 1 - A Guide to RNA-Seq
Supplementary 2 - Lecture notes : DE analysis
Supplementary 3 - Lecture notes : Annotation Data & Gene Set Analysis

Attribution notice

  • The material used to prepare for the workshop was extracted from Professor.Mik Black's lectures for STAT435 - Data Analysis for Bioinformatics (University of Otago, Dunedin, New Zealand).

  • Some code used in this workshop has been extracted from a collection of presentations, workshops and lectures by Prof. Thomas Girke, Institute for Integrative Genome Biology, UC Riverside: Link_1 and Link_2