CRUK: Analysis of publicly available microarray data

Prerequisites

Although microarrays have been superseded by high-throughput sequencing technologies for gene expression profiling, years of experience gained from analysing microarray data has led to a variety of analysis techniques and datasets that can be exploited in other contexts. In this course, we will focus on retrieving and exploring microarray data from public repositories such as Gene Expression Omnibus (GEO).

Course materials can be found here.

This event is part of a series of training courses organized in collaboration with Dr. Mark Dunning at CRUK Cambridge Institute.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

• Graduate students, Postdocs and Staff members from the University of Cambridge, Affiliated Institutions and other external Institutions or individuals
• Please be aware that these courses are only free for University of Cambridge students. All other participants will be charged a registration fee in some form. Registration fees and further details regarding the charging policy are available here
• Further details regarding eligibility criteria are available here

• A very basic knowledge of UNIX would be an advantage, but nothing will be assumed and extremely little will be required
• Attendees should be comfortable with using the R statistical language to read and manipulate data, and produce simple graphs. Here is an R crash course that we suggest looking through before attending this course.

Number of sessions: 2

Bioinformatics, Data mining, Transcriptomics

After this course you should be able to:

• Import gene expression datasets from GEO into R
• Assess the quality of a dataset in a repository
• Identify, and correct for, batch effects
• Perform a standard DE analysis to get a ranked list of genes
• Use unsupervised methods to explore a dataset
• Interrogate particular genes of interest

During this course you will learn about:

• Exploratory data analysis techniques for high-throughput data
• Workflows for the analysis of Illumina and Affymetrix gene expression data
• Normalisation of gene expression data
• Differential expression (DE) analysis using linear-modelling techniques
• Importing data from GEO into R
• Principal Components Analysis and hierarchical clustering of gene expression data

Presentations and practicals

• Free for University of Cambridge students
• £ 50/day for all University of Cambridge staff, including postdocs, and participants from Affiliated Institutions. Please note that these charges are recovered by us at the Institutional level
• It remains the participant's responsibility to acquire prior approval from the relevant group leader, line manager or budget holder to attend the course. It is requested that people booking only do so with the agreement of the relevant party as costs will be charged back to your Lab Head or Group Supervisor.
• £ 50/day for all other academic participants from external Institutions and charitable organizations. These charges must be paid at registration
• £ 100/day for all Industry participants. These charges must be paid at registration
• Further details regarding the charging policy are available here

Two full day sessions

A number of times per year

• EMBL-EBI: Transcriptomics Data and Tools (ONLINE LIVE TRAINING)
• An Introduction to Solving Biological Problems with R