(1)Multidimensional data resources with gene prioritization system, (2)Pathway-based analysis for depression

計畫名稱:(1)Multidimensional data resources with gene prioritization system, (2)Pathway-based analysis for depression

所屬單位:公衛系

研究團隊:郭柏秀實驗室

計畫主持人:郭柏秀

研究人員:高崇峰

資源需求:R, plink, SAS

使用期間:2010/07~

研究主題:
(1)Multidimensional data resources with gene prioritization system, (2)Pathway-based analysis for depression

研究內容概述:
1) Topic 1: This study collected susceptible genes for depression from 7 databases (i.e. 7 platforms): association study, linkage can, gene expression, regulatory pathway, and literature research. Both human and animal models were included in our data resources. These genes were initially assigned scores by category-specific scoring method. We then used a two-step approach to find an optimal weight matrix. Finally, those susceptible genes were prioritized by their combined scores using the optimal weight matrix. We evaluated prioritized genes by the GWAS and gene expression pattern in human tissues. 2) Topic 2: This study used the Gene Set Enrichment Analysis (GSEA) to perform pathway- based analysis for depression. We mapped a SNP to a gene if it was located within the gene or 20kb immediately upstream or downstream of the gene. The most significant SNP of the gene was chosen to represent the association of the gene. We discarded pathways if it contained less than 4 or more than 256 genes in order to avoid stochastic bias or testing too general biological process. After the SNP-gene and gene-pathway mapping process, we have 217,637 SNPs mapped to 15,735 protein-coding genes, which were involved in 188 biological pathways. A 10,000 permutation were conducted to calculate the empirical p-value via enrichment scores.

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