Systematic information integration of multiple related microarray studies has become an important issue as the technology has become significant mature and more prevalent in public health relevance over the past decade. The aggregated information provides more robust and accurate biomarker detection. So far, published meta-analysis methods for this purpose mostly consider two-class comparison. Methods for combining multiclass studies and expression pattern concordance are rarely explored. We first consider a natural extension of combining p-values from the traditional ANOVA model. Since p-values from ANOVA do not guarantee to reflect the concordant expression pattern information across studies, we propose a multi-class correlation measure (MCC) to specifically look for biomarkers of concordant inter-class patterns across a pair of studies. For both approaches, we focus on identifying biomarkers differentially expressed in all studies (i.e. ANOVA-maxP and min-MCC). The min-MCC method is further extended to identify biomarkers differentially expressed in partial studies using an optimally-weighted technique (OW-min-MCC). All methods are evaluated by simulation studies and by three meta-analysis applications to multi-tissue mouse metabolism data sets, multi-condition mouse trauma data sets and multi-malignant-condition human prostate cancer data sets. The results show complementary strength of ANOVA-based and MCC-based approaches for different biological purposes. For detecting biomarkers with concordant inter-class patterns across studies, min-MCC has better power and performance. If biomarkers with discordant inter-class patterns across studies are expected and are of biological interests, ANOVA-maxP better serves this purpose.
| Identifer | oai:union.ndltd.org:PITT/oai:PITTETD:etd-07272009-153919 |
| Date | 29 September 2009 |
| Creators | LU, SHU-YA |
| Contributors | George C. Tseng, Lisa Weissfeld, (Joyce) Chung-Chou H., Gong Tang |
| Publisher | University of Pittsburgh |
| Source Sets | University of Pittsburgh |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.library.pitt.edu/ETD/available/etd-07272009-153919/ |
| Rights | unrestricted, I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to University of Pittsburgh or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. |
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