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GWAS with AHP based SNP prioritization approach to identify SNP biomarkers for Alzheimer's disease

机译:GWAS与基于AHP的SNP优先排序方法一起确定阿尔茨海默氏病的SNP生物标志物

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Genome wide association studies (GWAS) aim to identify genomic variance associated with certain disease conditions. Major bottleneck of standard GWAS approaches are the prioritization and subset selection after the statistically significant SNPs are determined. Our group has recently developed an analysis pipeline, where p-value and combined p value statistics are integrated with the novel AHP based SNP prioritization algorithm for the detailed analysis of associated SNPs considering statistical significance and biological relevance. Following this pipeline, we have done the GWAS of Alzheimer's Disease (AD) on ADNI SNP genotyping data set where 148 AD cases and 182 controls are investigated. Among the top 100 SNPs 18 of them mapped to AD linked genes. Additionally further analysis of the gene and pathway results suggested new associations, providing basis for new hypothesis for the AD Biomarker research.
机译:全基因组关联研究(GWAS)旨在鉴定与某些疾病状况相关的基因组变异。标准GWAS方法的主要瓶颈是确定了具有统计意义的SNP之后的优先级划分和子集选择。我们小组最近开发了一种分析流程,其中将p值和组合的p值统计数据与基于AHP的新型SNP优先级排序算法集成在一起,以考虑统计意义和生物学相关性对相关SNP进行详细分析。按照这一流程,我们在ADNI SNP基因型数据集上完成了阿尔茨海默氏病(AD)的GWAS,其中研究了148个AD病例和182个对照。在前100个SNP中,有18个映射到AD连锁基因。另外,对基因和途径结果的进一步分析提示了新的关联,为AD Biomarker研究的新假设提供了基础。

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