Erica DePasquale, PhD

I am a researcher and a computational biologist. My research interests are quite varied and include past studies of forensic genomics, intrauterine growth restriction, preeclampsia, traumatic brain injury, schizophrenia, acute myeloid leukemia (AML) and blastic plasmacytoid dendritic cell neoplasm (BPDCN). My recent interests are focused on advancing our understanding of pediatric liver biology and developing new computational tools that leverage the fascinating new "-omics" data we generate daily.

My work is highly collaborative. I engage with various investigators within and outside the Division of Gastroenterology, Hepatology and Nutrition. As such, the breadth of problems I am trying to solve is quite extensive. For me, it's more about using my computational expertise to enable the wet lab scientists, who are the experts in all the above areas, to make the most of their data and find any results that could make a difference in pediatric healthcare.

For example, we are working on creating a pediatric liver atlas using multiomic sequencing technology that will allow us to better understand age-related differences in the liver from infancy into adulthood. It will also serve as a reference to compare tissues from patients with liver disease so we can explore the biological mechanisms that drive disease. Similarly, I work closely with investigators to dive deeply into the immunological basis of acute and chronic liver transplant rejection, with the aim of creating better anti-rejection medications for future transplant patients. On the computational side, I am part of a team that is developing a new algorithm to correct for technical artifacts in spatial sequencing data. Ultimately, these cutting-edge tools and analyses can lead to improved outcomes for children.

My bioinformatics research has led me to develop many publicly available tools for processing "-omics" data. I developed one of the first methods for identifying doublets in single-cell sequencing called DoubletDecon (2018). In addition, I led the development of a web interface that allows researchers to process kinome array data called Kinome Random Sampling Analyzer (KRSA). I have also co-developed two additional data analysis tools, CellHarmony for label transfer across datasets and MisC for cleaning spatial transcriptomics data.

I've been involved in scientific research while working toward my various degrees since 2009, beginning with wet lab science for many years before shifting toward bioinformatics in 2016. I earned my PhD (2020) and started my postdoctoral work right after that (2021). I joined Cincinnati Children's as a PhD student in the Biomedical Informatics program (2016-2020), then came back again as a bioinformatician in the Division of Gastroenterology, Hepatology and Nutrition (2022-2025) before becoming an assistant professor (2025).