
During November 2024, Shyi developed and integrated a new genetic dataset for the LiLabAtVT/I2GDS2024 repository to support R Studio-based analytics. Shyi curated and formatted the arg_pre_abs.csv file using data management skills and CSV handling, structuring it to represent gene presence or absence across isolate IDs. This dataset was version-controlled and committed to the repository, ensuring reproducibility and auditability for downstream workflows. By providing a clean, structured input for R Studio, Shyi enabled immediate gene-level analysis and visualization. The work demonstrated careful data curation and repository management, though the scope was focused on a single feature without bug fixes.

Monthly summary for 2024-11 focusing on key deliverables, impact, and technical accomplishments for LiLabAtVT/I2GDS2024. Key feature delivered this month: added a new genetic dataset input for R Studio analysis to streamline downstream analytics and visualizations. All changes are trackable via a single commit reference, ensuring reproducibility and auditability.
Monthly summary for 2024-11 focusing on key deliverables, impact, and technical accomplishments for LiLabAtVT/I2GDS2024. Key feature delivered this month: added a new genetic dataset input for R Studio analysis to streamline downstream analytics and visualizations. All changes are trackable via a single commit reference, ensuring reproducibility and auditability.
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