Secondary Data Analysis Paper

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RATIONALE: Genes that play significant roles in determining the onset of LOAD may also be expressed in brain tissue of individuals with EOAD. Therefore to identify these sets of genes, we examined data in the EOAD using data-mining approach. Our initial secondary data analysis indicates that there are approximately 69 genes that are either significantly upregulated or downregulated (adjusted p value of <0.05 and 2 fold change) will be entered into the DAVID Functional Annotation interface and submitted as a gene list selecting species (Huang da et al. 2009b, Huang da et al. 2009a). Gene Ontology (GO) charts will be generated using the parameters: count 2, EASE 0.1; Benjamini correction, Number of records = 1000. Because the GEO2R tool will list up to 250 differentially expressed genes, it will be difficult to manually identify the genes that are common in each of the datasets.…show more content…
By comparing the datasets in two brain regions, we will be able to determine differences in gene expression patterns in these two brain regions affected by AD pathology. Further, we will also compare hippocampal LOAD and EOAD datasets to determine any genes/proteins/pathways that are common to both forms of AD. In the normal aging brain dataset (GSE1572), we will identify whether there are genes expressed at age 40 that are common to the LOAD and EOAD

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