Lewis Cathryn M, Levinson Douglas F
Department of Medical and Molecular Genetics, King's College London School of Medicine at Guy's, King's College and St. Thomas' Hospitals, Guy's Hospital, London, UK.
Genet Epidemiol. 2006 May;30(4):348-55. doi: 10.1002/gepi.20149.
The Genome Search Meta-Analysis (GSMA) method is widely used to detect linkage by pooling results of previously published genome-wide linkage studies. The GSMA uses a non-parametric summed rank statistic in 30 cM bins of the genome. Zintzaras and Ioannidis ([2005] Genet. Epidemiol. 28:123-137) developed a method of testing for heterogeneity of evidence for linkage in the GSMA, with three heterogeneity statistics (Q, Ha, B). They implement two testing procedures, restricted versus unrestricted for the summed rank within the bin. We show here that the rank-unrestricted test provides a conservative test for high heterogeneity and liberal test for low heterogeneity in linked regions. The rank-restricted test should therefore be used, despite the extensive simulations needed. In a simulation study, we show that the power to detect heterogeneity is low. For 20 studies of affected sib pairs, simulated assuming linkage in all studies to a gene with sibling relative risk of 1.3, the power to detect low heterogeneity using the Q statistic was 14%. With linkage present in 50% of the studies (to a gene with sibling relative risk of 1.4), the Q heterogeneity statistic had power of 29% to detect high heterogeneity. The power to detect linkage using the summed rank was high in both of these situations, at 98% and 79%, respectively. Although testing for heterogeneity in the GSMA is of interest, the currently available method provides little additional information to that provided by the summed rank statistic.
基因组搜索荟萃分析（GSMA）方法被广泛用于通过汇总先前发表的全基因组连锁研究结果来检测连锁。GSMA在基因组的30 cM区间使用非参数求和秩统计量。Zintzaras和Ioannidis（[2005]《遗传流行病学》28:123 - 137）开发了一种在GSMA中检验连锁证据异质性的方法，有三个异质性统计量（Q、Ha、B）。他们实施了两种检验程序，对区间内的求和秩进行受限与非受限检验。我们在此表明，秩非受限检验对于连锁区域中的高异质性提供了保守检验，而对于低异质性提供了宽松检验。因此，尽管需要大量模拟，仍应使用秩受限检验。在一项模拟研究中，我们表明检测异质性的效能较低。对于20项受累同胞对研究，假设所有研究都与一个同胞相对风险为1.3的基因连锁进行模拟，使用Q统计量检测低异质性的效能为14%。当50%的研究存在连锁（与一个同胞相对风险为1.4的基因）时，Q异质性统计量检测高异质性的效能为29%。在这两种情况下，使用求和秩检测连锁的效能都很高，分别为98%和79%。尽管在GSMA中检验异质性很有意义，但目前可用的方法相比求和秩统计量提供的信息几乎没有增加。
