
Developed an end-to-end automation script for GRCh38 reference genome preparation within the hartwigmedical/scripts repository, focusing on streamlining bioinformatics workflows. The solution, implemented in Shell, automated the downloading of the GRCh38 reference, application of masking definitions and the PhiX genome, and the combination, masking, and indexing of genome components. This approach reduced manual intervention, improved reproducibility, and standardized reference data preparation for the Hartwig Medical Database. By leveraging scripting and genome preparation expertise, the work enabled faster data readiness and supported scalable, compliant clinical data pipelines. No major bugs were reported, reflecting a stable and well-tested automation process.
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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