ArticleProceedings of the National Academy of Sciences of the United States of America2020
Causal inference in genetic trio studies.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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18 citing papers in PubMed, 50 citations in OpenAlex.
- Robust Inference With Ghostknockoffs in Genome-Wide Association Studies With Sample Relatedness.Genetic epidemiology · 2026Article
- CIT-Lasso: a scalable approach beyond guilty by association for identifying causal variants from genome-wide summary statistics.Genome biology · 2026Article
- A generalized test of genotype-phenotype causality in population-sampled nuclear families.PLoS genetics · 2026Article
- KnockoffHybrid: A knockoff framework for hybrid analysis of trio and population designs in genome-wide association studies.American journal of human genetics · 2024Article
- How do stochastic processes and genetic threshold effects explain incomplete penetrance and inform causal disease mechanisms?Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Review
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- Leveraging family data to design Mendelian randomization that is provably robust to population stratification.Genome research · 2023Article
- DIET: Conditional independence testing with marginal dependence measures of residual information.Proceedings of machine learning research · 2023Article
- Inferring the mode and strength of ongoing selection.Genome research · 2023Article
- Leveraging family data to design Mendelian Randomization that is provably robust to population stratification.bioRxiv : the preprint server for biology · 2023Article
- KnockoffTrio: A knockoff framework for the identification of putative causal variants in genome-wide association studies with trio design.American journal of human genetics · 2022Article
- Article
- Interpretable machine learning for genomics.Human genetics · 2022Article
- Article
- False discovery rate control in genome-wide association studies with population structure.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Sexual Dimorphism through the Lens of Genome Manipulation, Forward Genetics, and Spatiotemporal Sequencing.Genome biology and evolution · 2021Article
- Double Empirical Bayes Testing.International statistical review = Revue internationale de statistique · 2020Article
- Toward causality and improving external validity.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We introduce a method to draw causal inferences-inferences immune to all possible confounding-from genetic data that include parents and offspring. Causal conclusions are possible with these data because the natural randomness in meiosis can be viewed as a high-dimensional randomized experiment. We make this observation actionable by developing a conditional independence test that identifies regions of the genome containing distinct causal variants. The proposed digital twin test compares an observed offspring to carefully constructed synthetic offspring from the same parents to determine statistical significance, and it can leverage any black-box multivariate model and additional nontrio genetic data to increase power. Crucially, our inferences are based only on a well-established mathematical model of recombination and make no assumptions about the relationship between the genotypes and phenotypes. We compare our method to the widely used transmission disequilibrium test and demonstrate enhanced power and localization.
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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.