Here are some potential rotation projects for people interested in rotating in the lab.  Please contact me if any of these pique your interest and know that this is not an exhaustive list!

More Computational

Single Cell Gene Networks

Gene co-expression networks help us to understand how groups of genes that vary between individuals act in concert with one another to create observable phenotypic differences.  We have successfully used these approaches to identify several key genes that play roles in heart failure as well as gain a deeper understanding of the pathways that are activated during heart failure progression.

Just as we can use differences across a population to explore gene networks, so too can we use differences across a tissue – how do variations in cellular neighborhoods and proximity to stressors lead to phenotypic differences?  How can we leverage the explosion of single cell data to improve our co-expression networks?

Cross-Tissue Gene Networks

The GTEx and HMDP cohorts give us access to transcriptomic data from multiple tissues all drawn from the same individuals and paired with genetic and phenotypic information.  Can we use a combination of the wMICA, NEO, and QENIE algorithms to develop a hypothesis-generating gene network that spans the body and links multiple organ systems together?

Genome-Wide Association Studies in the Collaborative Cross and Joint CC-HMDP Cohorts

We have been working for the past year to examine the CC and its susceptibility to isoproterenol-induced Heart Failure.  Although this project will continue through the rest of the 2023-2024 academic year, we are now at a point where we can begin to perform genome-wide association studies on the strains we have already collected, identifying potential candidate genes for in vitro study.  A further open question is how to integrate our new CC data with the ‘old’ HMDP data.

More Computational

Still working on these.  Come talk to me and lets see if we can come up with something together!