Long-read genomics
ONT data, rDNA structural variation, TeloBP refinement, repeat-aware analysis, assembly graph cleanup.
UCI MCSB Ph.D. Student · Computational Genomics
Measuring the genome where repeats make biology hard to see.
I study repeat-rich genome structure with long-read sequencing, algorithm development, and cancer genomics. My current work connects rDNA structural variation, telomere dynamics, genome assembly, and spatial or single-cell tumor ecosystems.
Research Direction
Algorithms for genome structure, built close to biological questions.
I build analysis workflows that make complex genomic structures measurable. Recent work includes a fast Python-based long repeat inversion algorithm for ONT data, telomere-age regression modeling, and assembly graph cleanup for a Telomere-to-Telomere fusion genome in S. pombe.
I am especially interested in disease contexts where structural variation, repeat biology, and tumor ecosystems can clarify mechanisms that standard short-read or bulk summaries miss.
Working Range
From wet-lab context to reproducible computation.
Statistical modeling
Linear, spline, and polynomial regression for telomere-age relationships, including 3D visualization workflows.
Spatial biology
Visium and Xenium melanoma analysis using Scanpy, Seurat, and CellChat for niche and communication mapping.
Research infrastructure
Linux/Unix, HPC, Snakemake, Nextflow, Docker, Git/GitHub, and Ubuntu server administration.
Experience
A current computational-genomics track with translational roots.
Graduate Student Researcher, Center for Complex Biological Systems, UC Irvine
Developing repeat-aware algorithms and pipelines for ONT long-read data, telomere modeling, T2T assembly, spatial genomics, and single-cell tumor analysis.
Staff Research Associate III, Moores Cancer Center, UCSD Health
Conducted clinical and computational research in urological oncology, contributing to peer-reviewed publications and ASCO presentation work.
Graduate Researcher, Quantitative and Computational Biology, USC
Used HPC systems for structure-based GPCR ligand screening across an 11-billion-molecule dataset and 4D flexible docking in ICM-Pro.
Research Intern, Scripps Translational Science Institute
Analyzed UK Biobank data with GWAS, PLINK2, QCtool, FUMA-GWAS, and R machine-learning models.
Publications & Conferences
Selected evidence.
Driver mutations associated with signatures of platinum sensitivity in germ cell tumors.
Sawa, Y. C., Jia, L., Krause, H., et al. npj Precision Oncology, 2024.
doi.org/10.1038/s41698-024-00727-2Refining the serum miR-371a-3p test for viable germ cell tumor detection.
Lafin, J. T., Scarpini, C. G., Amini, A., ..., Sawa, Y., et al. Scientific Reports, 2023.
doi.org/10.1038/s41598-023-37271-1Molecular drivers of organotropism & cisplatin resistance in germ cell tumors.
Sawa, Y. C., Bagrodia, A., et al. Oral presentation, ASCO Annual Meeting, Chicago, 2023.
Toolkit
Built for data that needs both biological judgment and compute discipline.
- Python
- R
- Shell/Bash
- Linux/Unix
- HPC
- Snakemake
- Nextflow
- Docker
- MySQL
- NGS analysis
- Long-read sequencing
- Scanpy
- Seurat
- CellChat
- PCR/qPCR
- NGS library preparation
Contact