Research
My research spans computational method development for spatial transcriptomics, genomics and epigenomics of immune regulation, and tools for making AI agent-driven bioinformatics more accessible and trustworthy.
Cell segmentation quality
Imaging-based spatial platforms like 10x Xenium assign millions of transcripts to individual cells — but every downstream conclusion depends on how well cell boundaries were drawn. I develop CRISP (Co-expression Rejection In Segmentation Purity), an open-source tool in R and Python that flags cells co-expressing mutually exclusive marker genes to quantify segmentation errors without ground-truth annotation.
Using CRISP, we benchmarked five segmentation algorithms — including the 10x segmentation kit, Baysor, Proseg, and Segger — across ten mouse organs with a 5,006-gene Xenium panel, revealing a tissue-dependent tradeoff between transcript capture and cell purity.
Preprint
Rose, J.R., Rose, E.S., Assumpcao, J.A.F., Pathak, H., Peck, H.E., Sasser, L.E., Patel, C.J., Vanover, D. & Santangelo, P.J. CRISP enables comparisons of image-based spatial transcriptomic segmentation quality across ten organs. bioRxiv (2026). doi:10.64898/2026.04.16.718947
Xenium analysis pipelines
Alongside the benchmarking work, I’ve built an open-source toolchain for Xenium experiments: Nextflow pipelines for generating alternative segmentations, Seurat-based workflows for QC through annotation, and utilities for splitting and processing tissue microarrays. These are described on the software page.
During my PhD I used integrated RNA-seq and ATAC-seq to ask how transcriptional and epigenetic states encode immune cell identity — and what happens when that regulation goes wrong.
Epigenetics of immune memory
I studied how transcriptomic and epigenomic states define human memory T cell subsets. We identified chromatin regions whose accessibility before and after activation (poised accessible regions) distinguishes memory subsets and their activation potential.
Published
Rose, J.R., Akdogan-Ozdilek, B., Rahmberg, A.R., et al. Distinct transcriptomic and epigenomic modalities underpin human memory T cell subsets and their activation potential. Communications Biology 6, 363 (2023). Read the paper
Autoimmunity
I also investigated the dysregulation of B cells in lupus. We found that disease activity is reflected in the transcriptome — and written into the epigenome — of otherwise resting, naïve B cells in individuals with the disease.
Accepted — J. Clin. Invest.
Rose, J.R., et al. Systemic lupus erythematosus signatures in resting naïve B cells differ by disease activity. Journal of Clinical Investigation (in press).
AI agents are increasingly capable of running bioinformatic analyses end to end — the hard part is trusting the result. I’m working on Stringency, a framework that puts guardrails around agent-driven analysis: it checks that the analysis plan is grounded in best practices before any code runs, keeps a tamper-proof log of every step the agent takes, and pauses at key decisions until a person signs off. The goal is agent-run analyses that a reviewer — or your future self — can trust, reproduce, and audit.
For the full publication list, see my Google Scholar profile.