QuantGen Group at Michigan State University


Our group is interested in the analysis and prediction of complex traits and diseases using genetic (integrating pedigrees, genomics, and other omics) and environmental information. Our research involves methods, software development, and applications in human health, plant and animal breeding. Most of us are affiliated with the Department of Epidemiology and Biostatistics at Michigan State University.


Genomic Analysis and Prediction of Complex Traits. Development and evaluation of methods and software for analysis and prediction of complex traits using high-dimensional genomic data (e.g., SNPs, genotyping by sequencing, and other types of sequence data). Our research in this area has focused on the use of shrinkage and variable selection in parametric models, as well as on the use of some semi-parametric methods (e.g., RKHS).

Genomics x Environment. Development of methods for integrating high-dimensional genomic and environmental data in a unified framework. We have developed methods that can model interactions between high-dimensional marker panels and high-dimensional environmental covariates. These methods were originally developed and tested with data from wheat trails. We are currently extending some of these methods for analysis of complex human traits and diseases.

Integration of Data from Multiple Omics Layers. Development of models and software for integrating high-dimensional multi-layer omics data. Our focus is on methods that can integrate whole-omics profiles and can model interactions between two or more high-dimensional predictor sets (e.g., genome-by-methylome interactions). We are currently working on using these methods for prediction of breast cancer outcomes and in plant omics applications.

Software development for analysis of big omics data. We have developed several R packages for genetic analysis using pedigrees, genomes and other omics (see software below for further details).

Genomic Analysis of Obesity and Response to Exercise. We maintain an active collaboration with researchers from the TIGER (Training Interventions and Genetics of Exercise Response) study, developing and implementing methods for the identification of genetic factors influencing Body Composition and Response to Exercise Intervention.


BGLR. The Bayesian Generalized Linear Regression R package implements a variety of shrinkage and variable selection methods. The package can be used with whole-genome data (e.g., SNPs, gene expression or other omics), pedigrees and non-genetic covariates, including high-dimensional environmental data. Article CRAN Source Code

BGData. A suite of R packages to enable analysis of extremely large genomic data sets (potentially millions of individuals and millions of molecular markers). Article CRAN Source Code

pedigreemm. An R package for analysis of complex traits and diseases using generalized linear mixed models using likelihood methods. Article Documentation CRAN

pedigreeR. R functions related to pedigrees. Source Code

MTM. Implements a Bayesian Multi-Trait Gaussian models with user defined-(co)variance structures. Documentation Source Code



Ben Drabing
Ben Drabing


  • Areas of Interest: Multiomics.
Elizabeth McMahon
Elizabeth McMahon


  • Areas of Interest: Biostatistics, Statistical Genetics, Psychopathology, Clinical Trials, Pharmacology.
Mingyue Tan
Mingyue Tan


  • Areas of Interest: Protein analysis, especially applying statistical methods to them.
Yifei Li
Yifei Li


  • Areas of Interest: Statistical Genetics
Alexa Lupi
Alexa Lupi PhD Student


  • Areas of Interest: Biostatistics, Statistical Genetics, Epidemiology
Ana I. Vazquez
Ana I. Vazquez Associate Professor


Anirban Samaddar
Anirban Samaddar PhD Student


  • Areas of Interest: Bayesian Statistics, Time Series, Statistical Genetics
Guanqi Lu
Guanqi Lu PhD Student


  • Areas of Interest: Statistical Genetics, Biostatistics
Gustavo de los Campos
Gustavo de los Campos Professor


Harold Wu
Harold Wu PhD Student


  • Areas of Interest: Statistical Genetics, Statistical Modeling, Clinical Trials
Marco López-Cruz
Marco López-Cruz Postdoctoral Research Associate


Paulino Pérez
Paulino Pérez Associate Professor


Past Members

Agustín González Reymúndez
Agustín González Reymúndez Postdoc


  • Areas of Interest: Genomic tools for QTL mapping and genomic prediction, with applications in human genetics and plant breeding
Alexander Grueneberg
Alexander Grueneberg Programmer


C. Austin Pickens
C. Austin Pickens Doctoral Candidate


  • Areas of Interest: Novel biomarker discovery using mass spectrometry-based lipidomics and disease prediction
  • Links: GitHub, ResearchGate
Deniz Akdemir
Deniz Akdemir Postdoc


  • Areas of Interest: Data Mining, Multivariate Statistics, Statistical Genetics, Animal and Plant Breeding
Felix Enciso
Felix Enciso PhD Candidate


  • Areas of Interest: Genome-wide association and genome selection studies for complex traits in potato, genetic engineering in potato using CRIPRS/Cas9 technology
  • Links: GitHub, Publications
Fernando Aguate
Fernando Aguate Postdoc


  • Areas of Interest: Biostatistics, Statistical Genetics, Plant Breeding, Software Development
  • Links: Website, GitHub, Google Scholar
  • Also joined us as a visitor in 2016 while at Facultad de Ciencias Agropecuarias, Universidad Nacional de Córdoba (Argentina)
Filipe Couto
Filipe Couto Postdoc


  • Areas of Interest: Biostatistics, plant Breeding, genome-wide association studies and prediction of complex traits in plants
Gabriel Rovere
Gabriel Rovere Postdoc


  • Areas of Interest: Animal Breeding. Livestock Genetic Evaluations, Horse Breeding, Breeding Goals.
Hank Wu
Hank Wu Master Student


  • Areas of Interest: Biostatistics
Hwasoon Kim
Hwasoon Kim Postdoc


  • Areas of Interest: Biostatistics, Clinical Trials
  • Links: Website, GitHub
Lian Lian
Lian Lian Postdoc


  • Areas of Interest: Statistical Genetics, Plant Breeding
Mengying Sun
Mengying Sun Research Assistant


  • Areas of Interest: Statistical Modeling
  • Links: GitHub
Michael P. Behring
Michael P. Behring PhD Candidate


  • Areas of Interest: Epidemiology, Genetics of Cancer
Paige Duren
Paige Duren


  • Areas of Interest: Nursing
Raka Mandal
Raka Mandal PhD Student


  • Areas of Interest: Biostatistics, Statistical Learning, Bayesian Statistics
Scott Funkhouser
Scott Funkhouser PhD Student


  • Areas of Interest: Software development for multiple omics layers, genomic prediction
  • Links: Website, GitHub
  • Software: editTools
Shyamali Mukerjee
Shyamali Mukerjee Master Student


  • Areas of Interest: Statistical Genetics, Application of Statistical Methods to Public Health Issues
Siddharth Avadhanam
Siddharth Avadhanam Master Student


  • Areas of Interest: Statistical Genetics, Biostatistics, Bioinformatics
Wesley Bird
Wesley Bird Undergraduate Student


  • Areas of Interest: Medical Laboratory Science and Human Biology
  • REPID Scholar
Xuemeng Wang
Xuemeng Wang Master Student


  • Areas of Interest: Biostatistics, Statistical Modeling
Yeni Liliana Bernal Rubio
Yeni Liliana Bernal Rubio Postdoc


Yogasudha Veturi
Yogasudha Veturi PhD Candidate


  • Areas of Interest: Biostatistics, Statistical Genetics, Plant Breeding



Cecilia Salvoro
Cecilia Salvoro


  • Affiliation: Department of Biology, University of Padova, Padova, Italy
  • Areas of Interest: Human Genetics, Next-generation Sequencing, Genetic Mapping of Diseases, Prediction of Eye Color
  • Links: ResearchGate
Maria Martinez Castillero
Maria Martinez Castillero


  • Affiliation: University of Padova (Italy)
  • Areas of Interest: Quantitative genetics, programming, animal science
  • Links: LinkedIn
Pernille Bjarup Hansen
Pernille Bjarup Hansen


  • Affiliation: Department of Molecular Biology and Genetics, Aarhus University, Flakkebjerg, Denmark
  • Areas of interest: Plant genetics, quantitative genetics, abiotic stress and plant breeding


Muhammad Yasir Nawaz
Muhammad Yasir Nawaz


  • Areas of Interest: Genomic prediction, Livestock breeding, Application of statistical methods to public and animal health issues


Hugo O. Toledo Alvarado
Hugo O. Toledo Alvarado


  • Affiliation: Università degli studi di Padova (Italy)
  • Project: The use of Fourier-Transform Infrared (FTIR) Spectra as an innovative tool for predicting fertility traits in dairy cattle
M. Angeles Pérez-Cabal
M. Angeles Pérez-Cabal


  • Affiliation: Complutense of University of Madrid (Spain)
  • Areas of Interest: Animal Breeding


Juan Pablo Gutierrez Garcia
Juan Pablo Gutierrez Garcia


  • Affiliation: Complutense of University of Madrid (Spain)
  • Areas of Interest: Animal Breeding and Conservation Genetics
  • Links: Website


Christina Lehermeier
Christina Lehermeier


  • Affiliation: Plant Breeding, Technische Universität München (Germany)
  • Areas of Interest: Statistics, Quantitative Genetics, Plant Breeding
  • Links: Google Scholar, TUM Plant Breeding
Swetlana Berger
Swetlana Berger


  • Affiliation: Georg-August-Universität Göttingen (Germany)
  • Areas of Interest: Scale effects in genomic modelling and prediction