Causal Inference in Genetic Trio Studies

Understand

We introduce a method to rigorously 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 novel 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 in order to determine statistical significance, and it can leverage any black-box multivariate model and additional non-trio genetic data in order to increase power.