
Joepio developed an end-to-end automation script for GRCh38 reference genome preparation in the hartwigmedical/scripts repository. Using shell scripting and bioinformatics tools, Joepio created PrepareReference.sh to streamline the process of downloading the GRCh38 reference, applying masking definitions and the PhiX genome, combining and masking components, and indexing the final reference genome. This solution reduced manual intervention, improved reproducibility, and standardized reference data preparation for the Hartwig Medical Database. The work demonstrated depth in genome preparation and scripting, enabling faster and more reliable data readiness for clinical pipelines. No bugs were reported, reflecting careful implementation and robust workflow design.

Summary for 2025-04: Delivered end-to-end automation for GRCh38 reference genome preparation in hartwigmedical/scripts. Key deliverable: PrepareReference.sh, a shell script that downloads the GRCh38 reference, applies masking definitions and the PhiX genome, combines and masks components, and indexes the prepared reference genome for use in the Hartwig Medical Database. This automation reduces manual steps, improves reproducibility, and standardizes reference data across environments, enabling faster data readiness for downstream analyses. No major bugs reported this month. Impact: accelerates data readiness, reduces manual error, and supports scalable, compliant data workflows in clinical data pipelines. Technologies and skills demonstrated: shell scripting, automation of bioinformatics prep, use of masking/indexing tools, version control, and reproducible workflow design.
Summary for 2025-04: Delivered end-to-end automation for GRCh38 reference genome preparation in hartwigmedical/scripts. Key deliverable: PrepareReference.sh, a shell script that downloads the GRCh38 reference, applies masking definitions and the PhiX genome, combines and masks components, and indexes the prepared reference genome for use in the Hartwig Medical Database. This automation reduces manual steps, improves reproducibility, and standardizes reference data across environments, enabling faster data readiness for downstream analyses. No major bugs reported this month. Impact: accelerates data readiness, reduces manual error, and supports scalable, compliant data workflows in clinical data pipelines. Technologies and skills demonstrated: shell scripting, automation of bioinformatics prep, use of masking/indexing tools, version control, and reproducible workflow design.
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