| Summary: | 碩士 === 國立成功大學 === 生物資訊研究所 === 98 === Major depressive disorder (MDD) is a complex and multifactorial trait with the interplay between genetic and nongenetic risk factors. So far, there have been many datasets and individual studies with massive information from multiple resources of genetic findings, including results in association studies, linkage scans, and gene expression studies for depression. This provides us an opportunity to conduct a prioritization system to utilize and combine multidimensional data to create an evidence-based gene set for depression. First, we collect susceptible genes for depression from five platforms: association study, linkage scan, gene expression, regulatory pathway, and literature search. Data resources included studies in both human and animal model. These genes are initially assigned scores by category-specific scoring method. Then, we use a two step approach to find an optimal weight matrix. Finally, susceptible genes are prioritized by their combined scores using the optimal weight matrix. We evaluate prioritized genes by an independent genome-wide association study and gene expression pattern in human tissues. Our results revealed that prioritized genes generated by such approach are promising for further biological experiment or replication.
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