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Briefings in Bioinformatics Advance Access published online on February 3, 2006
Briefings in Bioinformatics, doi:10.1093/bib/bbk003
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© The Author 2006. Published by Oxford University Press. For Permissions, please email: journals.permissions@oxfordjournals.org
Received July 22, 2005
Accepted November 23, 2005

Original Article

Propagating uncertainty in microarray data analysis

Magnus Rattray *, Xuejun Liu, Guido Sanguinetti, Marta Milo, and Neil D. Lawrence

* To whom correspondence should be addressed.
Magnus Rattray, E-mail: magnus.rattary{at}manchester.ac.uk


  Abstract

Microarray technology is associated with many sources of experimental uncertainty. In this review we discuss a number of approaches for dealing with this uncertainty in the processing of data from microarray experiments. We focus here on the analysis of high-density oligonucleotide arrays, such as the popular Affymetrix GeneChip® array, which contain multiple probes for each target. This set of probes can be used to determine an estimate for the target concentration and can also be used to determine the experimental uncertainty associated with this measurement. This measurement uncertainty can then be propagated through the downstream analysis using probabilistic methods. We give examples showing how these credibility intervals can be used to help identify differential expression, to combine information from replicated experiments and to improve the performance of principal component analysis.

Keywords: microarray; Affymetrix GeneChip®; probabilistic model; gene expression; bayesian inference; principal component analysis.

Magnus Rattray gained his PhD in 1996 from the Department of Computer Science at the University of Manchester, where he is now Senior Lecturer. He works on the theory and application of statistical learning and probabilistic modelling, with current applications in phylogenetics, microarray data analysis and comparative genomics.

Xuejun Liu gained her MSc in Computer Science from Nanjing University of Aeronautics and Astronautics in 2002. She is now studying for a PhD in the School of Computer Science at the University of Manchester. Her research is on the application of probabilistic models for microarray data analysis.

Guido Sanguinetti gained a DPhil in Mathematics from Wadham College, Oxford in 2003. He is currently a research associate at the Department of Computer Science at the University of Sheffield and his research focuses on probabilistic modelling and on the propagation of uncertainty through microarray analysis.

Marta Milo gained her PhD in 2000 from the University of Naples ‘Federico II’. Dr Milo is currently a Wellcome Trust Research Fellow jointly in the Department of Biomedical Science and the Department of Computer Science at the University of Sheffield. Her main interests are understating regulatory gene networks in mammalian biological systems by merging microarray data analysis with biological data.

Neil Lawrence gained his PhD in 2000 from the Computer Laboratory at the University of Cambridge. Dr Lawrence is currently a Senior Lecturer in the Department of Computer Science at the University of Sheffield. His main interest is machine learning algorithms based on probabilistic models and their application in speech, graphics, vision and bioinformatics.


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