Bayesian variable selection for the analysis of AD

 
   Lead Investigator:    Richard Young
   Institution      :    University of Nevada Las Vegas
   E-Mail           :    Ryoung@unlv.edu
   Proposal ID      :    1584



   Proposal Description:
   Using new stats method we are looking at find new SNP in GWAS data set. We are also using ADNI - which is already processed.    Detecting single nucleotide polymorphisms (SNPs) in genomic data using GWAS is a well-established method, however, because of the number of statistical corrections required (Bonferroni correction, Holm-Bonferroni method, or other alpha adjustment method) significantly reduce the discovery rate (genes that make it cross p-value) because of the aggressive correction amount required for multiple comparisons. An alternative statistical approach can help discover new snp based on the Bayesian variable selection for high dimensional number sets.      My AIM with this dataset is to utilizes the data and compare it with other existing dataset to understand new SNP changes in genes and provide increased statistical accuracy.