Megan Hagenauer, Ph.D.

I specialize in the analysis and interpretation of high dimensional neuroscience data, with a particular interest in the application of genomics to the study of neuropsychiatric disorder.

 

My research focus has changed over the years. I began my career as a behavioral neuroscientist. As a student, I studied affective neuroscience, reproductive neuroendocrinology, and circadian rhythms, and ended up focusing my dissertation on the hormonal basis for adolescent sleep patterns using animal models. However, while working on my dissertation I developed severe rodent allergies and was forced to switch fields.

 

As a post-doctoral researcher, I began full-time training in bioinformatics and computational neuroscience. Because of my awareness of the complexity and noise present in neuroscience experimental designs, I was able to make substantial improvements in the analysis of brain transcriptional profiling data, and ended up playing a principal role in the analysis of a large number of public and privately-held datasets for the Pritzker Neuropsychiatric Research Consortium, National Institute on Drug Abuse, and Hope for Depression Research Foundation.

 

My role as a professional analyst now extends beyond statistical coding – I evaluate experimental designs for sources of confounding variability and noise, guide researchers in the interpretation of results from large “discovery” datasets, and help triangulate results with publicly-available data sources. I also write custom code to automate laboratory procedures, and recently co-led a workshop that spurred the development of several computational models for the relationship between disrupted sleep and pain sensitivity. 

 

Over the years I have worked closely with undergraduate researchers, and typically my research is buoyed by a team of 3-4 students. I also teach courses in experimental design, statistics, and programming at the University of Michigan, including a module in the Neuroscience Graduate Program “bootcamp” focused on improving experimental design and statistical practices in response to the reproducibility crisis. 

 

In the community, I run an outreach program every December in Ypsilanti Community Schools that introduces several hundred elementary school kids to computer coding as part of Computer Science Education Week.