Adaptively Weighted Meta-analysis in -omics Applications
- 2016-05-09 (Mon.), 10:30 AM
- 中研院-統計所 2F 交誼廳
- 茶 會:上午10:10統計所二樓交誼廳
- Prof. George C. Tseng
- Departments of Biostatistics, University of Pittsburgh
Abstract
In this talk, I will present an adaptively weighted Fisher's method that was developed to account for gene-specific heterogeneous differential expression (DE) signal across studies in transcriptomic meta-analysis. We will show that the method is asymptotically Bahadur optimal and the adaptive weights provide improved interpretation and further biological investigation in omics applications. A fast algorithm has been developed for accurate p-value calculation that is useful for multiple comparison of thousands of genes (or millions of SNPs). Bootstrap technique is used to assess a confidence score for the weights. Simulations and applications of prostate cancer, lung cancer and mouse metabolism data will be presented.