Introduction to microarray data analysis

Course provider:
The University of Manchester

Course contact:
Heather Vincent (heather.vincent@manchester.ac.uk)

Summary:
The place of microarray data analysis 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, this course focuses on microarray analysis in the context of modelling for a systems approach to biology. Course participants will work through practical examples using maxdview, a visualisation environment for microarray data from The University of Manchester, and/or Bioconductor.

The course is designed to be taken either as a stand-alone course for those already working with microarrays, 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:

Microarrays and experimental design

Data capture and preliminary checks

Data analysis

2-channel data

Gene Class Tests

Further details:
The assessment methods are shown below.

There will be an assessed tutorial exercise for each section of the course. These exercises will be brief: they are included as one means of maintaining a dialogue between all those participating in the course.

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 PC running a recent version of Microsoft Windows, preferably Windows XP or Windows 2000. You will also need Java version 1.2.2 or higher.
Anyone planning to use Bioconductor for the practical exercises may 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. You might also find an introductory R Tutorial useful.

References:
Statistical and Data Handling Skills in Biology, Roland Ennos (Pearson)
Recomended for those who need revision in statistics
Microarray Bioinformatics, Dov Stekel (Cambridge University Press)
Statistics for Microarrays, Ernst Witt and John McClure (Wiley)
An online textbook, and recommendations for additional reading and listening, are provided within the course. This 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)

Course provider:	The University of Manchester
Course contact:	Heather Vincent (heather.vincent@manchester.ac.uk)
Summary:	The place of microarray data analysis 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, this course focuses on microarray analysis in the context of modelling for a systems approach to biology. Course participants will work through practical examples using maxdview, a visualisation environment for microarray data from The University of Manchester, and/or Bioconductor. The course is designed to be taken either as a stand-alone course for those already working with microarrays, 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: Microarrays and experimental design Data capture and preliminary checks Data analysis 2-channel data Gene Class Tests
Further details:	The assessment methods are shown below. There will be an assessed tutorial exercise for each section of the course. These exercises will be brief: they are included as one means of maintaining a dialogue between all those participating in the course. 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 PC running a recent version of Microsoft Windows, preferably Windows XP or Windows 2000. You will also need Java version 1.2.2 or higher. Anyone planning to use Bioconductor for the practical exercises may 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. You might also find an introductory R Tutorial useful.
References:	Statistical and Data Handling Skills in Biology, Roland Ennos (Pearson) Recomended for those who need revision in statistics Microarray Bioinformatics, Dov Stekel (Cambridge University Press) Statistics for Microarrays, Ernst Witt and John McClure (Wiley) An online textbook, and recommendations for additional reading and listening, are provided within the course. This 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)

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Updated 14 January 2010 by Heather Vincent