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Exploit the graph to improve a) reliability of causal estimates by empirically assessing pleiotrpy; b) statistical power by exploiting outliers in the data to search for putative novel associations, and using graph traversal algorithms to find links for which direct associations are underpowered; c) interpretability by deconvolving the mediating relationships between arbitrary numbers of traits. 3. Use the causal graph as a tool for phenomic modelling. Example 1: linking molecular phenotypes to new or existing drug targets will enable the prediction of the efficacy and safety of developing interventions. Example 2: using MR against fitness related traits to obtain selection coefficients for each phenotype, I will construct models of human evolution, investigating the cost of complexity and evolutionary trajectories.","funder_award_id":"208806/Z/17/Z","funder":{"id":"https://openalex.org/F4320311904","display_name":"Wellcome 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