- Summary:
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Genome-wide association studies (GWAS) provide a powerful approach to identify the disease susceptibility regions in complex traits. Researchers further analyze these regions with biological experiments to discover the causal variants. However, often times these regions contain many polymorphisms and biological validation on all of them may be infeasible. We introduce a framework that identifies all the disease associated polymorphisms cost effectively by additional genotyping.
The full details are described in Increasing power of genome-wide association studies by collecting additional single-nucleotide polymorphisms.
- Data:
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All the data and the GWAS simulation files can be downloaded from the following link: simulationData.tar.gz (4.1Gb).
The "bglFiles" directory contains the minor allele frequency and position information of all the SNPs in the ENCODE regions in all populations.
The "pairwisecorrelations" directory contains the pairwise correlation between the SNPs in each population and ENCODE region.
The "simulationFiles" directory contains the simulated statistic values for all the SNPs when each SNP is causal.