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

被引：44

作者：

Li, Yang ^{[1
]}

Tesson, Bruno M. ^{[1
]}

Churchill, Gary A. ^{[2
]}

Jansen, Ritsert C. ^{[1
,3
]}

机构：

[1] Univ Groningen, Groningen Bioinformat Ctr, NL-9700 AB Groningen, Netherlands

[2] Jackson Lab, Bar Harbor, ME 04609 USA

[3] Univ Groningen, Univ Med Ctr Groningen, Dept Genet, NL-9700 AB Groningen, Netherlands

来源：

TRENDS IN GENETICS | 2010年 / 26卷 / 12期

关键词：

GENE-EXPRESSION; NETWORKS;

D O I：

10.1016/j.tig.2010.09.002

中图分类号：

Q3 [遗传学];

学科分类号：

071007 ; 090102 ;

摘要：

Genome-wide linkage and association studies of tens of thousands of clinical and molecular traits are currently underway, 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 that they are already valid in simple scenarios of two traits linked to or associated with the same genomic region. We argue that more comprehensive analysis and Bayesian reasoning are needed and that these can overcome some of the pitfalls, although not in every conceivable case. We conclude that causal inference methods can still be of use in the iterative process of mathematical modeling and biological validation.

引用

页码：493 / 498

页数：6

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