Li Luo, PhD
Research Assistant Professor
Department of Internal Medicine
Division of Epidemiology
Cellular and Molecular Oncology
I have the necessary expertise and motivation to participate in this project as the collaborating biostatistician, and devise analytical and computational strategies and perform statistical analysis for this project. I have a background and training in biostatistics with expertise in statistical genomics and genetic epidemiology, and have recently expanded my research interests to include environmental statistics. My research focuses on developing statistical methods and computational strategies for large-scale genomic studies of complex diseases and environmental health studies. Statistical methods for linking the millions of rare and novel variants discovered by NGS to disease phenotypes are limited and require development. I have published statistical methods that utilize functional data analysis techniques to provide a unified analytical framework for analysis of NGS data, through correlating the individual genotype profiles along the genome with both qualitative and quantitative phenotypes. Through years of collaboration on multiple environmental health projects investigating the health effects of mixture metal exposures relating to the abandoned uranium mine wastes in the Navajo Nation, I have been working on identification of statistical methods for analyses of metal mixture exposures that appropriately account for the interaction and combination effects. As a biostatistician co-investigator, I have collaborated successfully with investigators from University of New Mexico and outside institutions in identification of susceptible genetic and environmental factors for complex diseases including cancer, brain diseases, cardiovascular diseases and chronic kidney diseases. In addition, I have provided statistical assistance and consultation in study design, power analysis, statistical analysis, grant and manuscript preparations to investigators. My previous research experiences in areas of both statistical genomics and environmental health research and collaborative work in biomedical research have prepared me well to successfully contribute to the proposed project.