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Zhang, S. R. (2018). A Matched-Sample-Based Normalization Method: Cross-Platform Microarray and NGS Data Integration. Retrieved from http://purl.flvc.org/fsu/fd/2018_Fall_Zhang_fsu_0071E_14868
Utilizing high throughput gene expression data stored in public archives not only saves research time and cost but also enhances the power of its statistical support. However, gene expression profiling data can be obtained from many different technical platforms. Same gene expressions quantified by different platforms have different distributional properties, which makes the data integration across multiple platforms challenging. Several cross-platform normalization methods developed and tried to remove the differences caused by the platform discrepancy but they also remove the important biological signals as well. Zhang and Jiang (2015) introduced a new method focusing on eliminating platform effect among systematic effects by employing matched samples which are measured by different platforms for getting a benchmark model. Since the matched sample have no biological difference, their approach is robust to get rid of solely the platform effect. They showed that the new method performs better than Distance Weighted Discrimination (DWD) method. This paper is a follow-up study of their work and we attempt to improve the new method by incorporating Fast Linear Mixed Regression (FLMER) model. The result indicates that the FLMER model works better than the original proposed model, OLS (Ordinary Least Squares) model in after-normalization concordance comparison and Differential Expression(DE) analysis. Also, we compare our methods to other existing cross-platform normalization methods not only DWD but also Empirical Bayes methods, XPN and GQ methods. The results showed that the proposed method performs much better than other cross-platform normalization methods for removing platform differences and keeping the biological information.
A Dissertation submitted to the Department of Statistics in partial fulfillment of the requirements for the degree of Doctor of Philosophy.
Bibliography Note
Includes bibliographical references.
Advisory Committee
Jinfeng Zhang, Professor Directing Dissertation; Qing-Xiang Amy Sang, University Representative; Wei Wu, Committee Member; Xu-Feng Niu, Committee Member.
Publisher
Florida State University
Identifier
2018_Fall_Zhang_fsu_0071E_14868
Zhang, S. R. (2018). A Matched-Sample-Based Normalization Method: Cross-Platform Microarray and NGS Data Integration. Retrieved from http://purl.flvc.org/fsu/fd/2018_Fall_Zhang_fsu_0071E_14868