ArticleGenetics2011
A Bayesian framework for inference of the genotype-phenotype map for segregating populations.
Article in Genetics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
23 citing papers in PubMed.
- A Bayesian model selection approach to mediation analysis.PLoS genetics · 2022Article
- Estimation of high-dimensional directed acyclic graphs with surrogate intervention.Biostatistics (Oxford, England) · 2020Article
- Robust pathway sampling in phenotype prediction. Application to triple negative breast cancer.BMC bioinformatics · 2020Article
- A Microbe Associated with Sleep Revealed by a Novel Systems Genetic Analysis of the Microbiome in Collaborative Cross Mice.Genetics · 2020Article
- On the Role of Artificial Intelligence in Genomics to Enhance Precision Medicine.Pharmacogenomics and personalized medicine · 2020Review
- Integration of probabilistic regulatory networks into constraint-based models of metabolism with applications to Alzheimer's disease.BMC bioinformatics · 2019Article
- High-Dimensional Bayesian Network Inference From Systems Genetics Data Using Genetic Node Ordering.Frontiers in genetics · 2019Article
- Bayesian Networks Illustrate Genomic and Residual Trait Connections in Maize (G3 (Bethesda, Md.) · 2017Article
- A new statistical framework for genetic pleiotropic analysis of high dimensional phenotype data.BMC genomics · 2016Article
- Statistical Methods in Integrative Genomics.Annual review of statistics and its application · 2016Article
- Estimation of Directed Acyclic Graphs Through Two-stage Adaptive Lasso for Gene Network Inference.Journal of the American Statistical Association · 2016Article
- The center for causal discovery of biomedical knowledge from big data.Journal of the American Medical Informatics Association : JAMIA · 2015Article
- The Wright stuff: reimagining path analysis reveals novel components of the sex determination hierarchy in Drosophila melanogaster.BMC systems biology · 2015Article
- Bayesian network reconstruction using systems genetics data: comparison of MCMC methods.Genetics · 2015Article
- Article
- JOINT ANALYSIS OF SNP AND GENE EXPRESSION DATA IN GENETIC ASSOCIATION STUDIES OF COMPLEX DISEASES.The annals of applied statistics · 2014Article
- Causal inference of gene regulation with subnetwork assembly from genetical genomics data.Nucleic acids research · 2014Article
- Systems genetics approaches to understand complex traits.Nature reviews. Genetics · 2014Review
- Article
- Computational tools for discovery and interpretation of expression quantitative trait loci.Pharmacogenomics · 2012Review
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Complex genetic interactions lie at the foundation of many diseases. Understanding the nature of these interactions is critical to developing rational intervention strategies. In mammalian systems hypothesis testing in vivo is expensive, time consuming, and often restricted to a few physiological endpoints. Thus, computational methods that generate causal hypotheses can help to prioritize targets for experimental intervention. We propose a Bayesian statistical method to infer networks of causal relationships among genotypes and phenotypes using expression quantitative trait loci (eQTL) data from genetically randomized populations. Causal relationships between network variables are described with hierarchical regression models. Prior distributions on the network structure enforce graph sparsity and have the potential to encode prior biological knowledge about the network. An efficient Monte Carlo method is used to search across the model space and sample highly probable networks. The result is an ensemble of networks that provide a measure of confidence in the estimated network topology. These networks can be used to make predictions of system-wide response to perturbations. We applied our method to kidney gene expression data from an MRL/MpJ × SM/J intercross population and predicted a previously uncharacterized feedback loop in the local renin-angiotensin system.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.