Mouzaki, Daphne (2005) Statistical analysis of microarrays. Masters thesis, Durham University.
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 (,,) nonparametric empirical statistical analysis and Newton's and Kendziorski'ร () parametric empirical statistical analysis on microarray data. Both methods estimate Efron's (,,) local false discovery rate, which identifies interesting genes and provides information about the power of the experiment.
|Item Type:||Thesis (Masters)|
|Award:||Master of Science|
|Faculty and Department:||Faculty of Science > Mathematical Sciences, Department of|
|Copyright:||Copyright of this thesis is held by the author|
|Deposited On:||09 Sep 2011 09:53|