Integrate GWAS, eQTL, and mQTL Data to Identify Alzheimer's Disease-Related Genes.

ABSTRACT: It is estimated that the impact of related genes on the risk of Alzheimer's disease (AD) is nearly 70%. Identifying candidate causal genes can help treatment and diagnosis. The maturity of sequencing technology and the reduction of cost make genome-wide association study (GWAS) become an important means to find disease-related mutation sites. Because of linkage disequilibrium (LD), neither the gene regulated by SNP nor the specific SNP can be determined. Because GWAS is affected by sample size and interaction, we introduced empirical Bayes (EB) to make a meta-analysis of GWAS to greatly eliminate the bias caused by sample and the interaction of SNP. In addition, most SNPs are in the noncoding region, so it is not clear how they relate to phenotype. In this paper, expression quantitative tr

SUBMITTER: Zhao T 

PROVIDER: S-EPMC6824203 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature