March 2026 monthly summary for nf-core/modules: Delivered a major enhancement to the Differential and Functional Enrichment Analysis Workflows, including module updates, refactored code structure, and expanded outputs. Added new output channels for plots and statistical data, and ensured alignment with code review feedback to improve quality and maintainability. Updated snapshots to reflect output changes, improving reproducibility and downstream reporting. This work strengthens analysis reliability and supports scalable feature development, with clear collaboration and adherence to coding standards.

October 2025 — Focus on launching and branding for nf-core/differentialabundance project on nf-core/website. Implemented a dedicated project introduction page, accompanying markdown documentation of aims/goals/leaders, and added a new logo to the site branding. No major bugs fixed this month; work centers on visibility, onboarding, and alignment with branding guidelines. Commits reflect hackathon-driven rollout and ecosystem alignment.

April 2025 monthly work summary for nf-core/modules focusing on key accomplishments, major bug fixes, and overall impact. Delivered enhancements to the differential analysis workflow with multi-contrast input, improved reliability and reproducibility through standardized Limma results, and fixed normalization channel handling across workflows.

February 2025 monthly summary for nf-core/modules focusing on delivering robust variance-stabilized matrices (VST) handling and ensuring data flow integrity across differential and functional workflows, with emphasis on reproducibility, test alignment, and maintainability.

January 2025 nf-core/modules monthly summary focusing on feature delivery and robustness improvements that enable more flexible, scalable analyses across pipelines.

December 2024 — nf-core/modules: Delivered modernization and compatibility updates for the propr/grea module, integrated propd analysis into abundance_differential_filter, and introduced a new module to generate GSEA Chip files. These changes enhance stability, interoperability with Bioconductor ecosystems, broaden analysis capabilities, and improve reproducibility through tests and versioning. The work strengthens business value by enabling more robust differential analysis, smoother module maintenance, and ready-to-use outputs for downstream workflows.

Month: 2024-11 | Repository: nf-core/modules Key accomplishments: - Propr/Propd module enhancements for differential proportionality analysis were delivered, including refined input parameters, updated dependencies, and improved output handling. - More flexible options for saving results were introduced, along with improved methods for calculating and reporting statistical significance. Impact and value: - Increased accuracy, reproducibility, and interpretability of differential proportionality analyses in nf-core/modules, enabling faster downstream decision-making for research teams. - Streamlined result management and reporting, reducing manual post-processing effort and enabling easier integration into pipelines. Technologies/skills demonstrated: - Differential proportionality analysis concepts, parameterization, and robust significance reporting. - Dependency management and backward-compatible output interfaces. - Code maintenance practices and change management evidenced by commit update module propr/propd (#7083). Note: Major bugs fixed in this month were not provided in the input data.