Presented By: Michigan Institute for Data Science
Novel Tools to Increase the Reliability and Reproducibility of Population Genetics Research
Yajuan Si – Research Assistant Professor, Survey Research Center, Institute for Social Research
Advances in population genetic research have the potential to create numerous important advances in the science of population dynamics. The interplay of micro-level biology and macro-level social sciences documents gene–environment–phenotype interactions and allows us to examine how genetics relates to child health and wellbeing. However, traditional genetics research is based on nonrepresentative samples that deviate from the target population, such as convenience and volunteer samples. This lack of representativeness may distort association studies. Recent findings have provoked concern about misinterpretation, irreproducibility and lack of generalizability, exemplifying the need to leverage survey research with genetics for population-based research. This project is motivated by the research team’s collaborative work on the Fragile Family and Child Wellbeing Study and the Adolescent Brain Cognitive Development Study, which present these common problems in population genetics studies, to advance the integration of genetic science into population dynamics research. The project will evaluate sample selection effects, identify population heterogeneity in polygenic score analysis, and develop strategies to adjust for selection bias in the association studies of educational attainment, cognition status and substance use for child health and wellbeing. This interdisciplinary project will strengthen the validity and generalizability of population genetics research, deepen new understandings of human behavior and facilitate advances in population science.
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