Critical reasoning on causal inference in genome-wide linkage and association studies.

Critical reasoning on causal inference in genome-wide linkage and association studies.
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DOI:
10.1016/j.tig.2010.09.002
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发表时间:
2010-12
期刊:
影响因子:
11.4
通讯作者:
Jansen, Ritsert C.
Jansen, Ritsert C.
中科院分区:
生物学1区
文献类型:
--
作者:
Li, Yang;Tesson, Bruno M.;Churchill, Gary A.;Jansen, Ritsert C.

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目前正在对数以万计的临床和分子性状进行全基因组连锁和关联研究,为推断性状和遗传变异之间的因果关系提供了丰富的数据。然而,推理过程是基于发现特征之间相关性的微妙模式,因此具有挑战性,可能会产生大量不可信的因果推理。在这里,我们介绍的关注,并表明他们是有效的,已经在简单的情况下,两个性状链接或关联到同一个基因组区域。我们认为,更全面的分析和贝叶斯推理是必要的,可以克服这些陷阱,虽然不是在每一个可以想象的情况下。我们的结论是,因果推理方法可能仍然是使用的数学建模和生物验证的迭代过程中。
Genome-wide linkage and association studies of tens of thousands of clinical and molecular traits are currently under way, offering rich data for inferring causality between traits and genetic variation. However, the inference process is based on discovering subtle patterns in the correlation between traits and is therefore challenging and could create a flood of untrustworthy causal inferences. Here we introduce the concerns and show they are valid already in simple scenarios of two traits linked or associated to the same genomic region. We argue that more comprehensive analysis and Bayesian reasoning are needed and can overcome some of these pitfalls, although not in every conceivable case. We conclude that causal inference methods may still be of use in the iterative process of mathematical modeling and biological validation.
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