
Worked on expanding the nf-core/methylseq repository by integrating Picard-based targeted sequencing quality control within a modular Nextflow pipeline. Developed new modules in Groovy and YAML for sequence dictionary creation, BED-to-interval conversion, and hybrid-selection metrics, and organized these into a dedicated subworkflow for targeted sequencing analysis. Refactored the inclusion of BEDTOOLS_INTERSECT to improve modularity and code reuse, enhancing maintainability and future extensibility. Prioritized test readiness and parameterization to support robust analytics for targeted methylation sequencing panels. The work focused on feature development and workflow reorganization, with traceable, commit-driven progress and no critical bugs reported during the development period.
This month focused on expanding nf-core/methylseq capabilities for targeted sequencing QC by integrating Picard-based analysis within a modular workflow. Key work includes Picard modules for sequence dictionaries, BED-to-interval conversions, and hybrid-selection metrics; the creation of a dedicated subworkflow for targeted sequencing analysis using Picard; and a reorganization of BEDTOOLS_INTERSECT inclusion to improve modularity and reuse. No critical bug fixes were required this month; instead, refactoring and test readiness were prioritized to accelerate future delivery. Overall, these changes increase analysis fidelity for targeted panels, improve maintainability, and enable easier extension of methylation sequencing workflows across projects.
This month focused on expanding nf-core/methylseq capabilities for targeted sequencing QC by integrating Picard-based analysis within a modular workflow. Key work includes Picard modules for sequence dictionaries, BED-to-interval conversions, and hybrid-selection metrics; the creation of a dedicated subworkflow for targeted sequencing analysis using Picard; and a reorganization of BEDTOOLS_INTERSECT inclusion to improve modularity and reuse. No critical bug fixes were required this month; instead, refactoring and test readiness were prioritized to accelerate future delivery. Overall, these changes increase analysis fidelity for targeted panels, improve maintainability, and enable easier extension of methylation sequencing workflows across projects.

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