Research Philosophy

We are a team of interdisciplinary scientists that specializes in data-driven translational genomics. Our lab is a hybrid “wet” (experimental) and “dry” (bioinformatics) team. Our work tends to be interdisciplinary, but each individual project or researcher may focus more on experimental or computational innovation. Our lab does not rely on a model system or a specific experimental setting and instead focuses on data-driven exploration, including the development of new technologies. Though not required, projects tend to fit within a part or all of a general framework with these three tenets:

1. Translational motivation. As our approach can be applied to any organism profiled via DNA sequencing, we focus on questions that may directly impact human health, including stem cell reconstitution, treatment side-effects, or limited therapeutic efficacy of cancer immunotherapies.

2. Massive-scale data analyses. The most appealing part of DNA- and RNA-sequencing technologies, in our view, is that they sample a breadth and depth of nucleic acids from cells or tissues. Rather than quantifying only some genes or proteins, modern genomics technologies enable hypothesis generation and testing simultaneously if handled with appropriate statistical rigor and data science convention. In retrospective analyses, multiple datasets can be combined to structure questions that help mitigate observational biases.

3. Genomics technology development. Data-driven hypotheses can crystalize from reanalyses but often lack definitive evidence. Our prior work has taught us that new technologies are often required to test retrospective findings rigorously or scale up the number of measurements for proper inference. Thus, a major focus of the experimental component of our group is to establish new technologies that, once developed, explain phenomenon in high-dimensional data or enable foundational new directions.