Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, Washington 98195, USA.
Genet Epidemiol. 2009;33 Suppl 1(Suppl 1):S81-7. doi: 10.1002/gepi.20477.
Group 12 evaluated approaches to incorporate outside information or otherwise optimize traditional linkage and association analyses. The abundance of available data allowed exploration of identity-by-descent (IBD) estimation, score statistics, formal combination of linkage and association testing, significance estimation, and replication. We observed that IBD estimation can be optimized with a subset of marker data while estimation of inheritance vectors can provide both IBD estimates and a measure of their uncertainty. Score statistics incorporating covariates or combining association and linkage information performed at least as well as standard approaches while requiring less computation time. The formal combination of linkage and association methods may be fruitful, although the nature of the simulated data limited our conclusions. Estimation of significance may be improved through simulation, correction for cryptic relatedness, and the inclusion of prior information. Replication using real data provided consistent results, though the same was not true of simulated data replicates. Overall, we found that increasing the amount of available data limits analyses due to computational constraints and motivates the need to improve methods for the identification of complex-trait genes.
第 12 组评估了将外部信息纳入或优化传统连锁和关联分析的方法。可用数据的丰富性允许探索血缘关系(IBD)估计、评分统计、连锁和关联测试的正式组合、显著性估计和复制。我们观察到,IBD 估计可以通过标记数据的子集进行优化,而遗传向量的估计可以提供 IBD 估计及其不确定性的度量。包含协变量的评分统计或结合关联和连锁信息的方法至少与标准方法一样有效,同时需要更少的计算时间。连锁和关联方法的正式组合可能是富有成效的,尽管模拟数据的性质限制了我们的结论。通过模拟、纠正隐性亲缘关系和纳入先验信息可以提高显著性估计。使用真实数据进行复制提供了一致的结果,尽管模拟数据的复制品并非如此。总的来说,我们发现,可用数据量的增加由于计算限制而限制了分析,并促使需要改进用于识别复杂性状基因的方法。