Allen Andrew S, Satten Glen A
Department of Bioinformatics and Biostatistics, Duke University, North Carolina, USA.
Hum Hered. 2007;64(1):35-44. doi: 10.1159/000101421. Epub 2007 Apr 27.
Haplotype sharing statistics have been introduced in an ad-hoc way, often relying heavily on permutation testing. As a result, applying these approaches to whole genome association studies or to evaluate their properties in extensive simulation experiments is problematic. Further, permutation testing may be inappropriate in the presence of phase ambiguity and population stratification.
To present a simple framework for a class of haplotype sharing statistics useful for association mapping in case-parent trio data. This framework allows derivation of novel haplotype sharing tests as well as simple variance estimators and asymptotic distributions for haplotype sharing tests.
We validated that our approach is appropriately sized using simulated data, and illustrate the methodology by analyzing a Crohn's disease dataset. We find that haplotype-based analyses are much more powerful than single-locus analyses for these data.
单倍型共享统计量是以一种特别的方式引入的,通常严重依赖于置换检验。因此,将这些方法应用于全基因组关联研究或在广泛的模拟实验中评估其性质存在问题。此外,在存在相位模糊和群体分层的情况下,置换检验可能不合适。
为一类适用于病例-双亲三联体数据关联映射的单倍型共享统计量提出一个简单框架。该框架允许推导新的单倍型共享检验以及单倍型共享检验的简单方差估计量和渐近分布。
我们使用模拟数据验证了我们的方法具有合适的规模,并通过分析一个克罗恩病数据集来说明该方法。我们发现,对于这些数据,基于单倍型的分析比单基因座分析更具效力。