CAUSAL GRAPHICAL MODELS IN SYSTEMS GENETICS: A UNIFIED FRAMEWORK FOR JOINT INFERENCE OF CAUSAL NETWORK AND GENETIC ARCHITECTURE FOR CORRELATED PHENOTYPES

被引:73
|
作者
Neto, Elias Chaibub [1 ]
Keller, Mark P. [2 ]
Attie, Alan D. [2 ]
Yandell, Brian S. [1 ]
机构
[1] Univ Wisconsin, Dept Stat, Madison, WI 53706 USA
[2] Univ Wisconsin, Dept Biochem, Madison, WI 53706 USA
来源
ANNALS OF APPLIED STATISTICS | 2010年 / 4卷 / 01期
关键词
Causal graphical models; QTL mapping; joint inference of phenotype network and genetic architecture; systems genetics; homogeneous conditional Gaussian regression models; Markov chain Monte Carlo; QUANTITATIVE TRAIT LOCI; BAYESIAN NETWORKS; EXPRESSION; SPECIFICITY; CROSSES; MARKERS;
D O I
10.1214/09-AOAS288
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Causal inference approaches in systems genetics exploit quantitative trait loci (QTL) genotypes to infer causal relationships among phenotypes. The genetic architecture of each phenotype may be complex, and poorly estimated genetic architectures may compromise the inference of causal relationships among phenotypes. Existing methods assume QTLs are known or inferred without regard to the phenotype network structure. In this paper we develop a QTL-driven phenotype network method (QTLnet) to jointly infer a causal phenotype network and associated genetic architecture for sets of correlated phenotypes. Randomization of alleles during meiosis and the unidirectional influence of genotype on phenotype allow the inference of QTLs causal to phenotypes. Causal relationships among phenotypes can be inferred using these QTL nodes, enabling us to distinguish among phenotype networks that would otherwise be distribution equivalent. We jointly model phenotypes and QTLs using homogeneous conditional Gaussian regression models, and we derive a graphical criterion for distribution equivalence. We validate the QTLnet approach in a simulation study. Finally, we illustrate with simulated data and a real example how QTLnet can be used to infer both direct and indirect effects of QTLs and phenotypes that co-map to a genomic region.
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页码:320 / 339
页数:20
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