IIQ2 Phase 2: Clinical Trial Monitoring Dashboard
[Accepted for Publication: American Journal of Reproductive Immunology (Feb 2026)]
Role: Bioinformatics Lead & Epidemiologist
Position: Postdoctoral Fellowship @ University of Manitoba
Domain: Mucosal Immunology, Transcriptomics, Reproductive Health
1 The Challenge
Understanding the spatial and molecular composition of Tissue-Resident Memory (TRM) T cells in the female reproductive tract is critical for developing mucosal vaccines and HIV prevention strategies. However, the interplay between these cells in the ectocervix vs. the endocervix required high-resolution analysis that traditional bulk sequencing cannot provide.
2 The Solution
I integrated flow cytometry phenotyping with single-cell RNA sequencing (scRNA-seq) to map the molecular landscape of the cervical mucosa. This multi-modal approach allowed the research team to move beyond broad cell categories to identify unique, niche-specific T cell clusters.
- High-Resolution Mapping: Leveraged scRNA-seq to generate a molecular data matrix at the individual cell level, uncovering distinct molecular signatures for TRM subsets.
- Cross-Platform Integration: Coupled flow cytometry data with transcriptomic profiles to validate the presence and composition of established T cell subsets.
- Clinical Association Analysis: Investigated how these cellular compositions correlate with clinical findings from patients at a colposcopy clinic in Nairobi.
3 Technical Deep-Dive
- Bioinformatics Pipeline: Developed custom R workflows for scRNA-seq processing, including quality control, normalization, dimensional reduction (UMAP/t-SNE), and cluster annotation.
- Tech Stack:
R,Seurat,Bioconductor,SingleCellExperiment,ggplot2. - Impact: Resulted in the manuscript “Enumeration, phenotyping, and clinical associations of tissue-resident T cells in the ecto- and endocervix of women attending a colposcopy clinic”, accepted in the American Journal of Reproductive Immunology (2026).