compbiozurich/UZH-BIO392
Apr 2026 – May 2026
2 Months active
Languages Used
MarkdownPythonRpython
Technical Skills
JupyterJupyter NotebookNumPyPandasPythonR programming
Nami Aston
PROFILE
Nami Aston
Developed and maintained educational bioinformatics resources in the compbiozurich/UZH-BIO392 repository, delivering two Jupyter notebooks that guide users through genomics workflows with a focus on reproducibility and clear documentation. Leveraged Python, R, and Pandas to implement data processing pipelines, quality control, variant calling, and short tandem repeat analysis using PCA and clustering. Enhanced course readiness by structuring materials for hands-on learning and future scalability. Addressed a critical bug in FASTQ data size representation, ensuring accurate storage planning for large-scale genomic datasets. Emphasized traceability and auditability by documenting changes, supporting reliable and reproducible analyses across computational biology teaching environments.
Overall Statistics
Feature vs Bugs
67%Features
Repository Contributions
6Total
Bugs
1
Commits
6
Features
2
Lines of code
10,733
Activity Months2
Your Network
49 peopleShared Repositories
27
Work History
May 2026
1 Commits
May 1, 2026Month 2026-05: Delivered a critical bug fix in compbiozurich/UZH-BIO392 to ensure TB-scale genomic data size is represented correctly in FASTQ workflow, preventing storage misestimates and downstream processing errors. The fix was implemented in the notebook Update exday6checkedtask.ipynb and captured in commit 196383c7b3d94488a004a208cca08057ca1791ed. This work improves data integrity, enables reliable storage planning, and strengthens reproducibility across pipelines.
1 Commits
May 1, 2026Month 2026-05: Delivered a critical bug fix in compbiozurich/UZH-BIO392 to ensure TB-scale genomic data size is represented correctly in FASTQ workflow, preventing storage misestimates and downstream processing errors. The fix was implemented in the notebook Update exday6checkedtask.ipynb and captured in commit 196383c7b3d94488a004a208cca08057ca1791ed. This work improves data integrity, enables reliable storage planning, and strengthens reproducibility across pipelines.
May 2026
April 2026
5 Commits • 2 Features
Apr 1, 2026April 2026 — UZH-BIO392: Delivered two comprehensive educational materials and notebooks that enable hands-on genomics analysis, with strong reproducibility and documentation. Major bugs fixed: none reported in this period. Impact: scalable teaching resources, reproducible workflows, and a solid foundation for future enhancements. Technologies demonstrated: R for data exploration, Jupyter notebooks for workflows, data processing pipelines, quality control, variant calling, STR analysis with PCA/clustering, and Git-based collaboration.
April 2026
5 Commits • 2 Features
Apr 1, 2026April 2026 — UZH-BIO392: Delivered two comprehensive educational materials and notebooks that enable hands-on genomics analysis, with strong reproducibility and documentation. Major bugs fixed: none reported in this period. Impact: scalable teaching resources, reproducible workflows, and a solid foundation for future enhancements. Technologies demonstrated: R for data exploration, Jupyter notebooks for workflows, data processing pipelines, quality control, variant calling, STR analysis with PCA/clustering, and Git-based collaboration.
Activity
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Quality Metrics
Correctness96.6%
Maintainability93.4%
Architecture96.6%
Performance93.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
MarkdownPythonRpython
Technical Skills
JupyterJupyter NotebookNumPyPandasPythonR programmingbioinformaticsclinical codingdata analysisdata visualizationgenome technologiesgenomicsmachine learning
Repositories Contributed To
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