Doctor of Philosophy / Department of Statistics / Haiyan Wang / High throughput screening technologies have generated a huge amount of
biological data in the last ten years. With the easy availability of
array technology, researchers started to investigate biological
mechanisms using experiments with more sophisticated designs that pose novel challenges to
statistical analysis. We provide theory for robust statistical tests in three flexible
models. In the first model, we consider the hypothesis testing
problems when there are a large number of variables observed
repeatedly over time. A potential application is in tumor genomics
where an
array comparative genome hybridization (aCGH) study will be used to
detect progressive DNA copy number changes in tumor development. In
the second model, we consider hypothesis testing theory in a
longitudinal microarray study when there are multiple treatments or experimental conditions.
The tests developed can be used to
detect treatment effects for a large group of genes and discover genes that respond to treatment over
time. In the third model, we address a hypothesis testing problem that could
arise when array data from different sources are to be integrated. We
perform statistical tests by assuming a nested design. In all
models, robust test statistics were constructed based on moment methods allowing unbalanced design and arbitrary heteroscedasticity. The limiting
distributions were derived under the nonclassical setting when the number of probes is large. The
test statistics are not targeted at a single probe. Instead, we are
interested in testing for a selected set of probes simultaneously.
Simulation studies were carried out to compare the proposed methods with
some traditional tests using linear mixed-effects
models and generalized estimating equations. Interesting results obtained with the proposed theory in two
cancer genomic studies suggest that the new methods are promising for a wide range of biological applications with longitudinal arrays.
| Identifer | oai:union.ndltd.org:KSU/oai:krex.k-state.edu:2097/1105 |
| Date | January 1900 |
| Creators | Zhang, Ke |
| Publisher | Kansas State University |
| Source Sets | K-State Research Exchange |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
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