Analytics
Analytics Hub: Support data analytics, statistics, data science tools, and methods implementation to advance our knowledge of brain health and development
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Our Expertise
We are pioneers in creating open-source, publicly-available methods and analytic tools to improve the reliability and confidence in data analysis.
These methods can influence high-impact, hypothesis-driven research by direct collaboration with research groups or via open-source publicly-available access by interested researchers.
We also train the next generation of statisticians to engage in cutting-edge methods and interdisciplinary research.
Our Directors
Saonli Basu, PhD, Co-Director, Analytics Hub and Professor, Division of Biostatistics & Health Data Science
Lin Zhang, PhD, Co-Director, Analytics Hub and Associate Professor, Division of Biostatistics & Health Data Science
How We Engage
Our Team
Michael Anderson, PhD
Senior Research Professional
Saonli Basu, PhD
Co-Director, Analytics Hub
Professor, Division of Biostatistics & Health Data Science
Thierry Chekouo Tekougang, PhD
Associate Professor and Medtronic Faculty Fellow, Division of Biostatistics & Health Data Science
Christian Coffman, PhD
Senior Research Professional
Erjia Cui, PhD
Assistant Professor, Division of Biostatistics & Health Data Science
Kody DeGolier, MS
Advanced Research Professional
Kelly Duffy, PhD
Senior Research Professional
Annette Xenopoulos-Oddsson, MSc
Project Manager
Lin Zhang, PhD
Co-Director, Analytics Hub
Associate Professor, Division of Biostatistics & Health Data Science
Examples of Our Engagement
Open Source Tools for the Research Community UMN Genomic Data Commons
The Genomic Data Commons (GDC) is a central hub to store both local and publicly available datasets, harmonize the genomic data and develop many analytical pipelines around these integrated databases. We will provide services that would facilitate genomic data storage, curation, integration, visualization, and downstream analysis. Learn more about the UMN Genomic Data Commons
Graduate Student Training
In collaboration with the Interdisciplinary Biostatistics Training in Genetics and Genomics program funded by NIH T32 Training Grant: T32 GM132063, the Analytics Hub participates in the training of graduate students in computational statistics. We provide training through journal club participation and mentoring students on their summer projects to develop analytic pipelines.
Connect With Us
The Analytics Hub offers open, virtual office hours on Fridays from 1:30-2:30 p.m.