Gene-expression data profile are widely used in all kinds of biomedical studies especially in cancer research. This dissertation work focus on solving the problem of how to combine
datasets arising from different studies. Of particular interest is how to remove platform effect alone. The matched sample based cross-platform normalization method we developed are
designed to tackle data merging problem in two scenarios: The first is affy-agilent cross-platform normalization which are belong to classic microarray gene expression profile. The second
is the integration of microarray data with Next Generation Sequencing genome data. We use several general validation measures to assess and compare with the popular Distance-weighted
discrimination method. With the public web-based tool NCI-60 CellMiner and The Cancer Genome Atlas data portal supported, our proposed method outperformed DWD in both cross-platform
scenarios. It can be further assessed by the ability of exploring biological features in the studies of cancer type discrimination. We applied our method onto two classification problem:
One is Breast cancer tumor/normal status classification on microarray and next generation sequencing datasets; The other is Breast cancer patients chemotherapy response classification on
GPL96 and GPL570 microarray datasets. Both problems show the classification power are increased after our matched sample based cross-platform normalization method. / A Dissertation submitted to the Department of Statistics in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Fall Semester 2015. / September 1, 2015. / Includes bibliographical references. / Jinfeng Zhang, Professor Directing Dissertation; Qing-Xiang (Amy) Sang, University Representative; Wei Wu, Committee Member; Xufeng Niu, Committee
Member.
| Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_291335 |
| Contributors | Shao, Jiang (authoraut), Zhang, Jinfeng (professor directing dissertation), Sang, Qing-Xiang Amy (university representative), Wu, Wei (committee member), Niu, Xufeng (committee member), Florida State University (degree granting institution), College of Arts and Sciences (degree granting college), Department of Statistics (degree granting department) |
| Publisher | Florida State University |
| Source Sets | Florida State University |
| Language | English, English |
| Detected Language | English |
| Type | Text, text |
| Format | 1 online resource (82 pages), computer, application/pdf |
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