Yi-Ju Li
Principal Investigator
Professor of Biostatistics & Bioinformatics
Member of Duke Molecular Physiology Institute
Contact Information

Carmichael Building
(919) 684-0604


As a statistical geneticist, Dr. Li’s research interest is primarily in statistical method development and its application for genetic research of human complex diseases. She has worked extensively in the following disease areas: Alzheimer disease (AD), Myopia, Fuchs endothelial corneal dystrophy (FECD), drug induced liver injury (DILI), osteoarthritis (OA), and various postoperative outcomes of cardiac surgical patients. For statistical method development, Dr. Li is active in the development of various allelic or gene-base association tests for quantitative traits, censored trait, and zero-inflated outcomes for common, rare, or x-linked variants. Dr. Li’s group continues working on cutting edge statistical methods that can be applied to current genetic and genomic data.

Applied genetic studies of complex diseases:

  1. Alzheimer's Disease: The primary focus is to investigate the genetic modifiers of age-at-onset (AAO) of Alzheimer disease (AD). Dr. Li and collaborators have conducted the first genome wide linkage scan for AAO in AD and examined its overlapping with Parkinson disease (PD), another common neurodegenerative disease (1) . Their team identified the first AAO gene, glutathione S-Transferase Omega 1 and 2 (GSTO1) that was shared between AD and PD (2,3). With the available of high-density single nucleotide polymorphisms (SNPs) and sequence data across the genome for AD, Dr. Li and her collaborators, Drs. Eden Martin and Dr. Raymond Gao, currently have an active NIH R01 grant to investigate the genetic basis of AAO in AD. This project is expected to identify AAO genes for AD using advanced statistical methods and enriched AD genetic data from Alzheimer’s Disease Genetics Consortium (ADGC) and Alzheimer’s Disease Sequencing Project (ADSP).
  2. Fuchs Endothelium Corneal Dystrophy (FECD): FECD, first described by Ernst Fuchs in 1910, is a common hereditary disease of the corneal endothelium that leads to vision loss. The decrease of the corneal endothelium cells leads to the formation of excrescences in the central part of Descemet membrane (DM), termed guttae, and eventually progresses to corneal edema. Most patients begin showing symptoms after the age of 50. Dr Li has worked on the genetic studies of FECD since 2006 in collaboration with the late Dr. Gordon Klintworth, Dr. Natalie Afshari, and Dr. Simon Gregory. The Duke FECD team has accumulated an FECD collection of over 1400 individuals and is considered one of the largest such collections in the country. Our FECD research covers a wide spectrum of genetic studies including genome wide linkage scan, sequencing of known candidate genes in our study cohort, genome-wide association studies (GWAS), mitochondrial haplogroup association study, gene-environmental interaction, etc., with several significant papers published (4,5,6,7,8). Since 2013, Dr. Li has served as the PI of this project at Duke, and has established a FECD Genetics Consortium with Dr. Natalie Afshari at University of California, San Diego (UCSD) and Dr. Sudha Iyengar at Case-Western Reserve University (CWRU). Based on over 4500 samples, our consortium has published the large GWAS study (9) to date for FECD. Several active research projects are still ongoing.
  3. Genetic studies of postoperative outcomes after non-emergent coronary artery bypass graft (CABG) with cardiopulmonary bypass: Dr. Li currently directs the Anesthesiology Biostatistics Core in the Department of Anesthesiology at Duke. Dr. Li is also a member of Neurologic Outcome Research Group (NORG) of The Duke Heart Center and has worked on several clinical and genetic studies derived from NORG (10,11). Specifically, Dr. Li’s group is in charge of several GWAS studies to investigate various postoperative outcomes after CABG, including but not limited to renal dysfunction, postoperative onset atrial fibrillation (AFib), cognitive decline, etc.
  4. Drug Induced Liver Injury Network (DILN): Dr. Li is a co-investigator of DILIN as a statistical geneticist to lead the genetic projects within DILIN. The primary focus is to investigate the role of HLA and other genetic variants for the drug-specific induced liver injury. She and her collaborators have published a study to identify HLA alleles associate with trimethoprim-sulfamethoxazole (Bactrim) induced liver injury (12), and a study to identify HLA alleles for green tea induced liver injury (13). Many active projects are ongoing.
  5. Biomarker and Genetic studies of Osteoarthritis (OA): Dr. Li’s group has close collaboration with Dr. Virginia Kraus on investigating biomarkers for predicting the incidence or progression of knee OA as well as genetic studies of joint-specific OA by examining direct genetic effects on OA and indirect effect on OA through biomarkers.
  6. Myopia Genetics: Dr. Li collaborated with Dr. Terri Young at Duke Eye Center and Dr. Seang-Mei Saw at National University of Singapore for genetic studies of myopia. This collaboration has covered whole genome linkage scan, genome wide association studies (GWAS), the next generation sequencing. A number of publications on myopia genetics have been published including the largest genome wide linkage studies for high myopia (14), and refractive errors (15), and the identification of the first candidate gene, CTNND2 gene, for high myopia in Singaporean Chinese (16) based on a GWAS performed on Singapore Cohort study Of the Risk factors for Myopia (SCORM). Furthermore, Dr. Li’s group used both simulated data and SCORM GWAS data to evaluate seven copy number variant (CNV) detection methods, and concluded that QuantiSNP outperformed other methods and PennCNV detects less but more accurate CNVs (17).

Methodology development:

  1. Family-based association methods for detecting X-linked gene: Majority of family-based association methods were developed for testing autosomal markers. Dr. Li collaborated with Drs. Eden Martin and Richard Morris to develop a series of family-based association methods for binary and quantitative traits. This joint work led to two papers for qualitative traits (18,19) and one paper for quantitative traits (20).
  2. Family-based association methods for quantitative traits with and without censoring for common variants: This research was motivated by the study of AAO in AD and PD. In collaboration with Drs. Eden Martin and Andrew Allen, a family-based association method, GATOR, for testing a quantitative trait or trait with censoring like AAO was developed (21,22). Additionally, in collaboration with Dr. Eden Martin, Dr. Li’s group developed an EMK method which is an extension of the family-based association method for quantitative trait proposed by Monks and Kaplan (2000) to general pedigree with the capacity to test both allelic and genotypic association (23).
  3. Family-based association methods for testing rare variants: With the available rare variant data from next generation sequencing in recent years, Dr. Li’s group has been focused on the development of family-based association tests for quantitative traits (24) and survival traits (25). Currently, Dr. Li’s group is pursuing several method projects in this topic for Alzheimer disease family data in conjunction with the genetic studies of AAO of AD.


Yi-Ju Li, PhD, is a Professor in the Department of Biostatistics and Bioinformatics and Duke Molecular Physiology Institute (DMPI). She also directs the Biostatistics and Clinical Outcome group in the Department of Anesthesiology. Dr. Li is a statistical geneticist with research interest in statistical method development and its applications to genomic data derived from human disease genetic studies. Dr. Li has built her research expertise through the statistical method development and applied collaborative projects for genetic studies of human complex diseases. Her work on statistical methods is mostly in association tests including family-based association tests for survival outcomes and quantitative traits, and methods for detecting association of X-linked genes with complex traits. The disease area in her research includes neurodegenerative diseases (Alzheimer's and Parkinson's disease), eye disorders (myopia and Fuchs dystrophy), osteoarthritis (OA), and postoperative outcomes of cardiac surgical patients.

PhD, Statistics, NC State University, Raleigh, NC




If you are interested in obtaining any of these packages, please contact Dr. Li directly.

The EMK program implements two family-based association methods, allele- and genotype- based association methods, that we developed based on the framework of the allele-based method developed by Monks and Kaplan (2000) for quantitative traits (Li et al. 2008).

GATOR implements the family-based association method for quantitative traits with and without censoring described in Allen et al. (2006). It can handle quantitative phenotypes with skewed distributions, censored data, and/or outliers. Currently the program focuses on bi-allelic markers (e.g. single nucleotide polymorphisms). GATOR is able to perform association tests using four different genetic models: general, dominant, recessive, and additive.

X-LRT a suite of family-based tests for detecting association of X-chromosome genes.

XQTL is a family-based allelic/haplotype association test for quantitative traits using X-linked SNP/two-locus markers in a nuclear family design.