Joelle Mbatchou, Ph.D.

Senior Manager, Statistical Genetics

Regeneron Genetics Center

• Leading and mentoring a team member in the development of an analytical pipeline for time-to-event data.
• Develop machine learning methods to integrate functional annotations into rare variant association analyses using exome sequencing data.

Manager, Statistical Genetics

Regeneron Genetics Center

• Routinely carry out statistical analyses using cloud-based computing platforms on large-scale and high-dimensional human genetics datasets containing millions of genetic variants and 100,000s of individuals.
• Develop statistical methods and computational tools geared for large-scale genetic and genomics studies.
• Build WDL pipelines for data sets with 100,000s of individuals from whole-exome and whole-genome sequencing data.

Senior Statistical Geneticist

Regeneron Genetics Center

• Developed a computationally efficient whole genome regression method REGENIE for large-scale genetic association analyses which can be more than 100x faster than current state-of-the-art methods and can handle population structure and imbalanced binary traits.
• Implemented REGENIE into a C++ software which was publicly released on GitHub.
• Published the REGENIE method as first author in Nature Genetics where it was applied to UK Biobank data (>100 phenotypes, >400K individuals and >10M genetic variants).

Graduate Student Researcher

Department of Statistics, University of Chicago

• Developed a computationally fast method JASPER to assess significance for a general class of association tests, including tests for high dimensional phenotypes and gene-based tests, adjusting for population structure and family relatedness.
• Designed a permutation-based testing procedure BRASS for assessing significance with binary traits in structured samples for association tests with unknown exact/asymptotic distributions.
• Built C/C++ software to evaluate JASPER and BRASS through simulation studies & real data applications.

Instructor

Summer Institute in Statistical Genetics · University of Washington / Georgia Institute of Technology

• Taught the association mapping module on genome-wide association studies and sequencing (120 students).
• Designed coursework as well as hands-on practical exercises using software such as PLINK, REGENIE and R packages GWASTools and bigsnpr.
• Built a website to host the course materials using workflowr R package.

Teaching Assistant & Course Instructor

• Assisted in undergraduate courses: Statistical Methods and Applications, Statistical Models/Methods, Applied Regression Analysis and Analysis of Categorical Data.
• Created introductory material for R and STATA through weekly computer sessions; organized weekly office hours.
• Taught introductory statistical methods (STAT 234) in 2018 to a class of 36 students.
• Statistics Collaborative Learning Team Leader (2016–2017).