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Please join the UCSF EaRTH Center and the UCSF Program on Reproductive Health and the Environment for a presentation by Dr. Saunak Sen, Professor and Chief of Biostatistics at The University of Tennessee Health Science Center Department of Preventive Medicine.
Dr. Sen will be presenting, "Connecting lipid composition to individual characteristics using matrix linear models for high-throughput data".
Abstract: A major challenge in the analysis of lipidomic data is to connect the characteristics of the lipids to the characteristics of the individuals in whom they were measured. Matrix linear models provide a framework to accomplish that. We will use data from a study where lipid composition was measured using mass spectrometry to understand statin intolerance. We will show the association between lipid characteristics (trigliceride saturation and phosphorylation) and individual characteristics (statin intolerance, fish oil supplementation). We will discuss the use of matrix linear models for high throughput data studies such as eQTL studies, environmental screens, and high-throughput genetic screens. A Julia package implementing our methods is available. If time permits, we will present an interactive visualization of the data analysis using Pluto.
Please join us!
Registration is required, please register here. After registering, you will receive a confirmation email containing information about joining the meeting.
*This presentation is brought to you by the UCSF Environmental Research and Translation for Health Center and the UCSF Program on Reproductive Health and the Environment. Funding for the UCSF EaRTH Center is provided by core center grant P30-ES030284 from the National Institute of Environmental Health Sciences, National Institutes of Health.