Mouzaki, Daphne (2005) Statistical analysis of microarrays. Masters thesis, Durham University.
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Abstract
Microarray statistical analysis involves thousands of hypothesis tests to consider at the same time. Empirical Bayes methods which are well-suited for large scale inference problems seem to be the most appropriate approach for microarray data. In this thesis we describe and compare Efron's ([3],[1],[4]) nonparametric empirical statistical analysis and Newton's and Kendziorski'ร ([12]) parametric empirical statistical analysis on microarray data. Both methods estimate Efron's ([3],[1],[4]) local false discovery rate, which identifies interesting genes and provides information about the power of the experiment.
Item Type: | Thesis (Masters) |
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Award: | Master of Science |
Faculty and Department: | Faculty of Science > Mathematical Sciences, Department of |
Thesis Date: | 2005 |
Copyright: | Copyright of this thesis is held by the author |
Deposited On: | 09 Sep 2011 09:53 |