Bioinformatics for transcriptomics, including RNA-seq

This is just one course from the University of Manchester's online Masters programme in computational biology. To find out more about the programme, please visit our homepage.
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Next start date : Spring 2014

People landing here might also be interested in my new course in Advanced Sequence Analysis. This course will include the integration of RNA-seq and ChIP-seq.

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Course provider:
 University of Manchester
Contact:
 Heather Vincent (heather.vincent@manchester.ac.uk)
Summary:
 The new methods for transcriptomics are bringing new challenges in bioinformatics. This course covers microarray data analysis in depth, and also introduces the areas where new work is needed for next generation sequence (RNA-seq) analysis.

The place of transcriptomics in current research in the life sciences in outlined in the talk 'Microarrays: their design and use. (Tomlinson, C.R. (2009)). As in the introductory talk, the practical focus of 'Bioinformatics for transcriptomics' is in the context of modelling for a systems approach to biology. Participants work through practical examples of Affymetrix and Illumina data using Bioconductor.

This unit is designed to be taken either as a stand-alone course for professional development, or as a final module for those working towards a formal qualification in bioinformatics or systems biology. In the context of a full programme, the module links to the earlier module Bioinformatics for Systems Biology.

Syllabus:
 The course is divided into five main sections:

  1. Microarrays and experimental design
  2. Data capture and preliminary checks
  3. Microarray data analysis
  4. Other methods for transcriptome data capture
  5. Gene Class Tests
Further details:
 The assessment methods are shown below.

  1. There will be an assessed tutorial exercise for each of the above sections. These exercises will be brief: they are included as one means of maintaining a dialogue between all those the participants.
  2. There will be two further written assessments.  At the discretion of the examiners, you may also be required to attend a viva voce examination.
Technical requirements:
 This module is delivered entirely via the internet, so a reliable internet commection is essential. You will need access to a computer with at least 2Gb of RAM.

You might like to install and practise using R before the start of the course. R can be downloaded from one of the mirrors listed on the R Project site. There is also a link from the R site to the Bioconductor project. The introductory R Tutorial will be useful.

References:
 Microarray Bioinformatics, Dov Stekel (Cambridge University Press)

Statistics for Microarrays, Ernst Witt and John McClure (Wiley)

Statistical and Data Handling Skills in Biology, Roland Ennos (Pearson)
Recomended for those who need revision in statistics

R in Action, Robert Kabacoff, (Manning Publications)

An online textbook, and recommendations for additional reading and listening, are provided within the Virtual Learning Environment. The additional listening will include full access to :

Tomlinson, C.R. (2009), "Microarrays: their design and use", in Tomlinson, C. (ed.), Microarrays: Their design and use, The Biomedical & Life Sciences Collection, Henry Stewart Talks Ltd, London (online at http://hstalks.com/bio)

Distance learning in computational biology Courses in computational biology

Updated 16 June 2013 by Heather Vincent