MA570: Introduction to Genomics
Lecture times and practical sessions TBC
Semester: II
Course overview
This module will give students skills associated with high-throughput processing, investigation and interpreting
the output of genomics data using bioinformatic tools.
Taught in Semester II. Examined in Semester II.
Workload: 24 hours (12 lecture hours, 12 computer lab hours).
Module Learning Outcomes
On successful completion of this module you should be able to:
1. Discuss key historical developments in genomics research.
2. Access and apply core programming interfaces for bioinformatic analyses.
3. Discover differential expression in gene transcript sequencing data.
4. Compare new high-throughput sequencing experiments to other published results.
5. Evaluate functional genomics experimental datasets.
Indicative Content
1. Introduction to Linux & the R Statistical Computing Environment
2. Review of statistics
3. Microarrays: Experimental design and analysis issues
4. Analysis of microarray data using BioConductor, including
a. Pre-processing & quality control
b. Differential expression and geneset enrichment analyses
c. Case studies
5. MPS (massively parallel sequencing) technologies and their applications
Variant screening and discovery
6. RNA-seq: Gene expression analysis using next-generation sequencing, including
a. Quality control using the fastq pipeline
b. Mapping short-reads to reference genomes
c. Gene expression metrics and caveats
d. Case studies
7. Chromatin ImmunoPrecipitation and next-generation sequencing (ChIP-seq), including
a. Design and analysis of ChIP-seq experiments
b. Peak-finding
c. Case studies (including the Encode project)
Module Resources
 Avril Coghlan. “A Little Book of R For Bioinformatics”. Release 0.1.
 DW Mount. “Bioinformatics; sequence and genome analysis”, CSHL Press
 AD Baxevanis & BFF Oullette “Bioinformatics – A practical guide to the analysis of genes and
proteins”, Wiley
 AM Lesk “Introduction to Bioinformatics”, Oxford
 David A Morrison www.rjr-productions.org/Networks/Contents.html “Introduction to phylogenetic
networks”
 Zvelebil M, Baum JO. “Understanding Bioinformatics”
Module Delivery
The module will be delivered as a series of a weekly 1 hour lecture (12x1=12 hours) and a 1 hour practical
(12x1=12 hours). The series of 12 labs will focus on a series of project steps on examining the results of
genomics experiments. Learning will be supported by Blackboard resources, including bioinformatics tools,
websites and genomics data, as well as through the School of Maths computer server and analysis tools. Student
assignments for continuous assessment will be completed individually, requiring 3 hours a week of independent
learning (12x3=36 hours). Study and reading will require an additional 60 hours of effort.
Module Assessment
Assessment will be entirely by continuous assessment, comprising of weekly practical assignments (50%) and
completion of a project related to PhD work or MSc placement (50%).