Dr. Hendricks is a statistical geneticist and biostatistician interested in the complex nature of human diseases and traits. Her research spans a variety of health and disease projects including work in large scale genetic, methylation, metabolomic, and expression studies as well as more focused functional and model organism research. Recent applied and collaborative projects include understanding the mechanisms and mediators behind successful nutrition interventions in children and adults. Dr. Hendricks’s recent methodological work focuses on developing methods and user-friendly software to increase the utility and equity of publicly available genetic data, especially for diverse and under-represented ancestral populations. Dr. Hendricks is proud to have an active and dynamic research group mentoring amazing undergraduate and graduate students.


  • Statistics
  • Genetics & Genomics
  • Data Science for All

Meet the Team

Principal Investigator


Audrey E. Hendricks

Associate Professor of Statistics

Undergraduate Research Assistants


Derek Gunnels

Undergraduate Student in Computer Science


Souha Tifour

5yr BS Mathematics, MS Statistics Student

Graduate Research Assistants


Katie Marker

Co-mentor Summix Project; PhD Student in Human Medical Genetics and Genomics


Nicholas Weaver

PhD Student in Applied Mathematics


Adelle Price

MS Student in Statistics


Hayley Stoneman

PhD Student in Human Medical Genetics and Genomics


Jessica Murphy

PhD Student in Biostatistics


Sage Sigler

MS Student in Statistics



Megan Null

PhD-Applied Mathematics (2020)



Ian Arriaga MacKenzie

BS Math / MS Stats (2021)


Alexandria Ronco

BS-Mathematics (2020)


Gregory Matesi

BS Math / MS Student in Statistics


Jordan Hall

PhD-Applied Mathematics (2021)


Mobin Khajeh-Sharafabadi

BS in Biochemistry, Minor in Math (2021)

Ryan Scherenberg

BS-Business (2019)

Sam Chen

BS Student in Mathematics

Yinfei Wu

BS-Mathematics (2019)

Kaichao Chang

BS-Mathematics (2020)




Identifying foods and food compounds in healthy diets leading to improved health outcomes


Genome Sequencing Program


Rare variant association tests using external control data from genetic databases


Estimating ancestry proportions from genetic summary data

Recent Publications and News

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Summix: A method for detecting and adjusting for population structure in genetic summary data

Publicly available genetic summary data have high utility in research and the clinic, including prioritizing putative causal variants, …

2020 Genomic Innovator Awards

Dr. Hendricks is honored to receive one of the National Human Genome Research Institute’s 2020 Genomic Innovator Awards. She is excited to develop methods and software to increase the utility and equity of large genomic resources, especially for understudied and diverse ancestral populations. Congratulations to all awardees!

Exome Sequencing Identifies Genes and Gene Sets Contributing to Severe Childhood Obesity, Linking PHIP Variants to Repressed POMC Transcription

Obesity is genetically heterogeneous with monogenic and complex polygenic forms. Using exome and targeted sequencing in 2,737 severely obese cases and 6,704 controls, we identified three genes (PHIP, DGKI, and ZMYM4) with an excess burden of very rare predicted deleterious variants in cases. Additionally, we found an excess burden of predicted deleterious variants involving genes nearest to loci from obesity genome-wide association studies. Genes and gene sets influencing obesity with variable penetrance provide compelling evidence for a continuum of causality in the genetic architecture of obesity, and explain some of its missing heritability.


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