QuantGen Group at Michigan State University

About

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.

Projects

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.

Software

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

GPTL. Improving Polygenic Score Prediction for Underrepresented Groups Through Transfer Learning. Pre-print article Source Code

People

Ben Smith
Ben Smith

[email protected]

  • Areas of Interest: DNA methylation, epigenetics, and statistical genetics.
Hanyu Yang
Hanyu Yang

[email protected]

  • Areas of interest: Statistical Genetics, GWAS, Quantile Regression
Harish Neelam
Harish Neelam

[email protected]

  • Areas of interest: Statistical genetics, Computational precision health and Clinical statistics
Yifei Li
Yifei Li

[email protected]

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

[email protected]

Fernando Aguate
Fernando Aguate Postdoc

[email protected]

  • 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)
Guanqi Lu
Guanqi Lu PhD Student

[email protected]

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

[email protected]

Harold Wu
Harold Wu PhD Candidate

[email protected]

Marco López-Cruz
Marco López-Cruz Postdoctoral Research Associate

[email protected]

Paulino Pérez
Paulino Pérez Associate Professor

[email protected]

Past Members

Ben Drabing
Ben Drabing

[email protected]

  • Areas of Interest: Multiomics.
Elizabeth McMahon
Elizabeth McMahon

[email protected]

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

[email protected]

  • Areas of Interest: Protein analysis, especially applying statistical methods to them.
Agustín González Reymúndez
Agustín González Reymúndez Postdoc

[email protected]

  • Areas of Interest: Genomic tools for QTL mapping and genomic prediction, with applications in human genetics and plant breeding
Alexa Lupi
Alexa Lupi PhD Student

[email protected]

  • Areas of Interest: Biostatistics, Statistical Genetics, Epidemiology
Alexander Grueneberg
Alexander Grueneberg Programmer

[email protected]

Anirban Samaddar
Anirban Samaddar PhD Student

[email protected]

  • Areas of Interest: Bayesian Statistics, Time Series, Statistical Genetics
C. Austin Pickens
C. Austin Pickens Doctoral Candidate

[email protected]

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

[email protected]

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

[email protected]

  • 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
Filipe Couto
Filipe Couto Postdoc

[email protected]

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

[email protected]

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

[email protected]

  • Areas of Interest: Biostatistics
Hwasoon Kim
Hwasoon Kim Postdoc

[email protected]

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

[email protected]

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

[email protected]

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

[email protected]

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

[email protected]

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

[email protected]

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

[email protected]

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

[email protected]

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

[email protected]

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

[email protected]

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

[email protected]

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

[email protected]

Yogasudha Veturi
Yogasudha Veturi PhD Candidate

[email protected]

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

Visitors

2018

Cecilia Salvoro
Cecilia Salvoro

[email protected]

  • 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

[email protected]

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

[email protected]

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

2017

Muhammad Yasir Nawaz
Muhammad Yasir Nawaz

[email protected]

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

2016

Hugo O. Toledo Alvarado
Hugo O. Toledo Alvarado

[email protected]

  • 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

[email protected]

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

2015

Juan Pablo Gutierrez Garcia
Juan Pablo Gutierrez Garcia

[email protected]

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

2014

Christina Lehermeier
Christina Lehermeier

[email protected]

  • 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

[email protected]

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