My research group aims to combine both computational and wet lab strategies to answer questions related to the transcriptional regulatory control of human genes. We believe that a complex regulatory control determines the fates of individual non-coding regulatory elements and that the integration of diverse genetic, epigenetic, and disease data is the best way to explore this control. As such, it is important to map and understand how sequence variations in individuals are responsible for mediating differences in gene expression and their phenotypic consequences. The goal of my research is to understand the biological mechanisms underlying transcriptional regulation and how human variation at regulatory regions affects this process.

I was involved in developing the first genome-wide map of open chromatin regions using DNase-seq as a member of the ENCODE project. This was some of the first work done using the now ubiquitous high- throughput sequencing data. I was further involved in demonstrating that heritable genomic variation can result in changes in open chromatin states. I now continue this work in annotation of regulatory regions through a mix of machine learning and wet lab approaches through the web resource RegulomeDB and through membership in the IGVF and SMaHT consortia. My recent work has also focused on using long-read sequencing technology to directly measure the effect of conformational changes in the human genome that can be driven through the movement of transposable elements. This work has also expanded to study short tandem repeat expansions in the human genome with a focus on identification of new disease-associated repeats.