Collaborative Research: Integrating multi-dimensional omics data for quantifying disease heterogeneity

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Many complex diseases such as cancer demonstrate significant across-patient heterogeneity. For a better understanding of disease biology and optimally selecting treatment strategies, it is important to properly model disease heterogeneity. This project will develop a novel framework for modeling disease heterogeneity through the effective integration of information from multiple types of highly complex omics measurements. The proposed analysis framework and approaches will have significant broader impact. Applications of the methods will lead to more accurate identification of heterogeneous patient groups as well as their omics characteristics, which will facilitate the identification/definition of disease subtypes, treatment selection, and clinical decision-making. Data on skin and lung cancer will be analyzed leading to heterogeneity models that will be valuable to basic science researchers and clinicians. The project also involves education and training of graduate students at Yale University and the University of Iowa.High-dimensional omics data have been shown to be highly effective for heterogeneity analysis. Taking advantage of recent developments in multi-dimensional profiling under which data are collected on multiple types of omics measurements, the investigators will systematically develop novel integrated analysis strategies and approaches. Specifically, three sets of methods will be developed under the novel PFR (penalized fused regression) framework. Model averaging will be further developed to facilitate computation and provide additional insights into the proposed approaches. Extensive and rigorous methodological, computational, and theoretical investigations will be conducted. This project will make fundamental contributions to high-dimensional statistics and disease heterogeneity analysis.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.