Unbiased estimation of odds ratios: combining genomewide association scans with replication studies.

Unbiased estimation of odds ratios: combining genomewide association scans with replication studies.
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DOI:
10.1002/gepi.20394
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发表时间:
2009-07
影响因子:
2.1
通讯作者:
Dudbridge, Frank
Dudbridge, Frank
中科院分区:
医学4区
文献类型:
--
作者:
Bowden, Jack;Dudbridge, Frank

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从基因组扫描估计的比值比或其他效应大小是向上偏置的,因为只有排名靠前的关联才被报告,而且只有当它们达到定义的显著性水平时。基于以这种方式选择的数据,不存在无偏估计,但常规进行的重复研究允许无偏估计效应量。仅基于复制数据的估计是低效的,因为原则上,初始扫描可以提供关于效应大小的信息。我们提出了一个无偏估计结合信息的初始扫描和复制的研究,这是更有效的,比只基于复制。具体来说,我们调整标准组合估计,以允许在初始扫描中通过秩和显著性进行选择。我们的方法明确地允许从扫描产生的多个关联,并且对于显著性阈值的错误指定是鲁棒的。我们需要复制数据,但认为,在大多数应用程序中,只有当协会已被复制的效果大小的估计是有用的。我们说明了我们的方法在最近完成的扫描,并通过模拟探索其效率。Genet.流行病学33:406-418,2009.© 2009 Wiley-Liss公司。
Odds ratios or other effect sizes estimated from genome scans are upwardly biased, because only the top-ranking associations are reported, and moreover only if they reach a defined level of significance. No unbiased estimate exists based on data selected in this fashion, but replication studies are routinely performed that allow unbiased estimation of the effect sizes. Estimation based on replication data alone is inefficient in the sense that the initial scan could, in principle, contribute information on the effect size. We propose an unbiased estimator combining information from both the initial scan and the replication study, which is more efficient than that based just on the replication. Specifically, we adjust the standard combined estimate to allow for selection by rank and significance in the initial scan. Our approach explicitly allows for multiple associations arising from a scan, and is robust to mis-specification of a significance threshold. We require replication data to be available but argue that, in most applications, estimates of effect sizes are only useful when associations have been replicated. We illustrate our approach on some recently completed scans and explore its efficiency by simulation. Genet. Epidemiol. 33:406–418, 2009. © 2009 Wiley-Liss, Inc.
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