Director, Center for Computational and Quantitative Genetics

Professor, Department of Human Genetics

E-mail: mpepste at emory dot edu

Mike received his undergraduate degree in Mathematics and Biological Anthropology & Anatomy from Duke University and subsequently earned his Ph.D. in Biostatistics from the University of Michigan School of Public Health under the guidance of Drs. Michael Boehnke and Xihong Lin. Since joining the faculty in the Department of Human Genetics at Emory University in 2002, he has conducted interdisciplinary research primarily focused on the development and application of statistical and computational techniques for gene mapping of complex human traits and diseases. He is involved in several large-scale genetic studies of complex traits with a particular focus on schizophrenia, post-traumatic stress disorder, epilepsy, Alzheimer’s disease, and craniofacial disorders. In his spare time, he enjoys spending time with his family, hiking, reading, attending rock concerts, and being an obnoxious Duke basketball fan. 

Google Scholar: https://scholar.google.com/citations?user=hNyL5jMAAAAJ&hl=en

Projects:

• GAMuT: Gene Association with Multiple Traits

• RobustJoint: testing of SNP and SNP-environment interaction

• Chaplin: Case-Control Haplotype Inference

• LSKM: Multilocus Association Test for Quantitative Traits

• StratScore: genetic association mapping of disease that corrects for the confounding effects of population stratification

• Scout: combined association analysis of triads and unrelated subjects

• BiasedUrn: disease-exposure association with potential confounders

• SKAT: SNP-set Kernel Association Test

Publications:

• STACCato: Supervised Tensor Analysis tool for studying Cell-cell Communication using scRNA-seq data across multiple samples and conditions. PubMed, Dec. 16, 2023

• Cis- and trans-eQTL TWASs of breast and ovarian cancer identify more than 100 susceptibility genes in the BCAC and OCAC consortia. AJHG 111, May 8, 2024

• Identifying latent genetic interactions in genome-wide association studies using multiple traits. Genome Medicine 16(62), April 25, 2024

• POIROT: a powerful test for parent-of-origin effects in unrelated samples leveraging multiple phenotypes. Bioinformatics 39(4), April 17, 2023

• OTTERS: A powerful TWAS framework leveraging summary-level reference data. Nature Communications 14, March 7 2023

• Efficient estimation of indirect effects in case-control studies using a unified likelihood framework. Statistics in Medicine (2022), March 30, 2022   

• TIGAR-V2: Efficient TWAS tool with nonparametric Bayesian eQTL weights of 49 tissue types from GTEx V8. Human Genetics and Genomics Advances (2022), Volume 3, Issue 1, 13 January 2022

• Powerful and Efficient Strategies for Genetic Association Testing of Symptom and Questionnaire Data in Psychiatric Genetic Studies. Scientific Reports 9, May 17, 2019   

• Case-control Association Study of Autoimmunity Associated Variants in PDCD1 and Juvenile Idiopathic Arthritis. Current Rheumatology Reviews,  Dec. 1, 2017,   13(3),   p. 219-223

• A Statistical Approach for Testing Cross-Phenotype Effects of Rare Variants. Cell,  March 3, 2016,   98(3),   p. 525-540

• Inference on Haplotype Effects in Case-Control Studies Using Unphased Genotype Data. AJHG,  Dec 1, 2003, 73, p. 1316-1329

• Comparison of prospective and retrospective methods for haplotype inference in case‐control studies. Genetic Epidemiology, Sept. 15 2004, 27(3), p. 192-201

• A Permutation Procedure to Correct for Confounders in Case-Control Studies, Including Tests of Rare Variation. AJHG,  Aug. 10, 2012, 91(2), p. 215-223

• A Powerful and Flexible Multilocus Association Test for Quantitative Traits. AJHG,  Feb. 8, 2008, 82(2), p. 386-397

• Powerful SNP-set analysis for case-control genome-wide association studies. AJHG,  Jun. 11, 2010, 86(6), p. 929-942

• A simple and improved correction for population stratification in case-control studies. AJHG,  May. 1, 2007, 80(5), p. 921-930

• Genetic Association Analysis Using Data from Triads and Unrelated Subjects. AJHG,  Apr. 1, 2005, 76(4), p. 592-608

• Correcting Systematic Inflation in Genetic Association Tests That Consider Interaction Effects. JAMA Psychiatry,  Dec. 1, 2014, 71(12), p. 1392-1399