This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Fine-scale linkage disequilibirum (LD) mapping using high-density marker maps is widely recognized as having the potential to play an important role in the identification of disease genes. We developed a new method for fine-mapping a disease susceptibility locus using a case-control design. The new method, termed 'weighted average' (WA) statistic, averages the Cochran-Armitage (CA) trend test statistic and the difference between the Hardy Weinberg disequilibrium test statistics (the HWD trend) for cases and controls. The main features of the WA statistic are that it mitigates against the weaknesses, and maintains the strong points, of both the CA trend test and the HWD trend test. To allow for the extra variance induced by population substructure and cryptic relatedness, the WA statistic can be adjusted using genomic control. Based on the results of a simulation study, when there is no population substructure the WA test statistic shows good performance under a variety of genetic disease models. When there is population structure, the adjusted WA statistic maintains the correct probability of Type I error. Under all genetic disease models investigated, the adjusted WA statistic has better power than the adjusted CA trend test, the HWD trend test or the product of the adjusted CA trend test and the HWD trend test statistics. This work has now been published.
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