Day 4 - RNA-Seq Analysis

Keywords

Exploratory-analysis, Differential-expression, Statistical-model, Annotation

Authors

• Jenny Drnevich @jenny
• Radhika Khetani @radhika
• Jessica Kirkpatrick krkptrc2@illinois.edu

Type

• Both

Description

Day 4 focuses on the final steps after production of significant gene lists, including gene clustering, visualization, and annotation.

Aims

This day covers different aspects of "data mining" including basic heatmaps, Weighted Gene Co-expression Network Analysis and Annotation. Gene annotation includes a description of the types of gene annotation, where they can be found for particular species, how to import the annotation and append it to a gene list, and how to do over-representation testing of Gene Ontology and Pathway annotation terms.

Prerequisites

• Basic knowledge of R
• All the information in Day 1 and Day 2 and Day 3, but not the practical outputs

Target audience

Graduates students/post docs/beginning faculty

Learning objectives

• Be able to create a basic heatmap for a list of differentially expressed genes
• Be able to describe the basic theory of a Weighted Gene Co-expression Network Analysis
• Be able to describe the levels of gene annotation, what Gene Ontology terms are and how to test for over-representation
• Be able to follow and modify R scripts for heatmap generation, WGCNA and various facets of annotation.

Materials

• Lecture on heatmaps
• Lecture on WGCNA
• Lecture on Annotation

Data

• All data needed to run Day 4 practicals

Timing

6 hours contact time; practicals intersperced with lectures; can fit into 1 day + lunch and breaks, but usually participants do not go through all of annotation practical.

Content stability

Should be stable

Technical requirements

• R >= 3.1.3 on any OS plus Bioconductor packages edgeR, limma, affycoretools and WGCNA

Literature references