Leveraging Functional Data Analysis in “Omics” Studies of Childhood Obesity.

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Functional Data Analysis (FDA) is a branch of statistics that efficiently exploits measurements collected across continuous domains. This type of complex, structured data is often at the heart of contemporary “Omics” applications, which may involve, e.g., longitudinal measurements, measurements collected over space, measurements mapped along genome sequences, etc. In this lecture, I will provide a short, intuitive primer on FDA and illustrate its use in studies of the “Omics” correlates of childhood obesity.