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  • Title: Simulating association studies: a data-based resampling method for candidate regions or whole genome scans.
    Author: Wright FA, Huang H, Guan X, Gamiel K, Jeffries C, Barry WT, de Villena FP, Sullivan PF, Wilhelmsen KC, Zou F.
    Journal: Bioinformatics; 2007 Oct 01; 23(19):2581-8. PubMed ID: 17785348.
    Abstract:
    MOTIVATION: Reductions in genotyping costs have heightened interest in performing whole genome association scans and in the fine mapping of candidate regions. Improvements in study design and analytic techniques will require the simulation of datasets with realistic patterns of linkage disequilibrium and allele frequencies for typed SNPs. METHODS: We describe a general approach to simulate genotyped datasets for standard case-control or affected child trio data, by resampling from existing phased datasets. The approach allows for considerable flexibility in disease models, potentially involving a large number of interacting loci. The method is most applicable for diseases caused by common variants that have not been under strong selection, a class specifically targeted by the International HapMap project. RESULTS: Using the three population Phase I/II HapMap data as a testbed for our approach, we have implemented the approach in HAP-SAMPLE, a web-based simulation tool.
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