Why it mattered
Cancer analysis pipelines are often technically correct but operationally annoying. This work focused on interpretability and workflow clarity, not just output files.
Cancer data tooling
CNV Cancer RNA-seq Analysis
A CopyKAT-driven pipeline and dashboard for inferring and visualizing copy-number variation patterns in cancer single-cell RNA-seq data.
Made malignant-versus-normal cell separation easier to inspect and communicate through a stronger analysis surface.
What I built
A reproducible analysis path and a dashboard that made CNV structure easier to explore, compare, and explain to collaborators.
What I learned
Bioinformatics tooling wins when it lowers cognitive friction for the next person touching the data.
More work