4 October 2019 - 1-4pm
Room 355, Arts West, Professors Walk, University of Melbourne
Workshops
RNA-Seq Differential Gene Expression Analysis using Galaxy and the GVL
In this tutorial we cover the concepts of RNA-seq differential gene expression (DGE) analysis using a simulated dataset from the common fruit fly, Drosophila melanogaster.
The tutorial is designed to introduce the tools, datatypes and workflows of an RNA-seq DGE analysis. In practice, real datasets would be much larger and contain sequencing and alignment errors that make analysis more difficult.
In this tutorial we will:
- introduce the types of files typically used in RNA-seq analysis
- align RNA-seq reads with an aligner (HISAT2)
- visualise RNA-seq alignment data with IGV
- use a number of different methods to find differentially expressed genes
- understand the importance of replicates for differential expression analysis
- QC (quality control) of the raw sequence data
- Trimming the reads for quality and for adaptor sequences
- QC of the RNA-seq alignment data
- understand the basic workflow of alignment, quantification, and testing, for RNA-seq differential expression analysis
- process raw RNA sequence data into a list of differentially expressed genes
- understand the relationship between the number of biological replicates in an experiment and the statistical power available to detect differentially expressed genes
LAST RUN: March 22, 2018