ksgeist/Merrimack_DSE6630
May 2025 – Jul 2025
3 Months active
Languages Used
RR MarkdownTextHTMLMarkdown
Technical Skills
Code CommentingCode DocumentationData AnalysisData CleaningData ImputationData Interpretation
nicklagoni
PROFILE
Nicklagoni
Over three months, Nick Lagoni developed and maintained robust bioinformatics and machine learning workflows in the ksgeist/Merrimack_DSE6630 repository. He engineered reproducible pipelines for regression modeling, Random Forest, and SVM-based feature selection, integrating R and R Markdown to ensure clarity and traceability. Nick enhanced cross-platform compatibility, improved data preprocessing, and implemented overlap analyses between Random Forest and DESeq2 results to inform feature selection. His work included comprehensive documentation updates, visualizations, and QA improvements, addressing data leakage and overfitting. By coupling statistical modeling with clear documentation, Nick enabled interpretable, business-relevant genomic analyses and improved onboarding for future contributors.
Overall Statistics
Feature vs Bugs
82%Features
Repository Contributions
53Total
Bugs
4
Commits
53
Features
18
Lines of code
5,987
Activity Months3
Your Network
17 peopleWork History
July 2025
8 Commits • 4 Features
Jul 1, 2025July 2025 performance summary for ksgeist/Merrimack_DSE6630. Delivered analytics and documentation improvements that tightly couple machine learning feature importance with differential expression signals to inform biology-driven feature selection and robust model evaluation. Implemented and documented overlap analyses between Random Forest important genes and DESeq2 significant genes, including Out-of-Bag (OOB) performance reporting and practical recommendations for feature selection and cross-validation. Built an SVM-based feature importance workflow, integrated gene overlap with DESeq2 results, and analyzed SVM kernels to guide model choice and interpretability. Enhanced Demo_3.Rmd with Q21-24 content, including PCA/volcano plot interpretations and data partitioning strategies to mitigate overfitting with many predictors. Updated Demo HTML documentation to include author/date, revised question IDs, and expanded explanations across RNA-seq QC, batch effects, and differential expression analysis. All changes contribute to business value through robust, interpretable genomic analyses and improved reproducibility across the repository.
8 Commits • 4 Features
Jul 1, 2025July 2025 performance summary for ksgeist/Merrimack_DSE6630. Delivered analytics and documentation improvements that tightly couple machine learning feature importance with differential expression signals to inform biology-driven feature selection and robust model evaluation. Implemented and documented overlap analyses between Random Forest important genes and DESeq2 significant genes, including Out-of-Bag (OOB) performance reporting and practical recommendations for feature selection and cross-validation. Built an SVM-based feature importance workflow, integrated gene overlap with DESeq2 results, and analyzed SVM kernels to guide model choice and interpretability. Enhanced Demo_3.Rmd with Q21-24 content, including PCA/volcano plot interpretations and data partitioning strategies to mitigate overfitting with many predictors. Updated Demo HTML documentation to include author/date, revised question IDs, and expanded explanations across RNA-seq QC, batch effects, and differential expression analysis. All changes contribute to business value through robust, interpretable genomic analyses and improved reproducibility across the repository.
July 2025
June 2025
21 Commits • 6 Features
Jun 1, 2025June 2025 monthly summary for ksgeist/Merrimack_DSE6630 focusing on delivering measurable features, fixing critical issues, and enabling broader adoption through improved documentation and visuals.
June 2025
21 Commits • 6 Features
Jun 1, 2025June 2025 monthly summary for ksgeist/Merrimack_DSE6630 focusing on delivering measurable features, fixing critical issues, and enabling broader adoption through improved documentation and visuals.
May 2025
24 Commits • 8 Features
May 1, 2025May 2025 monthly summary for ksgeist/Merrimack_DSE6630: Delivered maintainable documentation and demo improvements, enhanced cross-platform compatibility, and advanced ML scaffolding, delivering measurable business value through clearer QA, more robust experiments, and portable data pipelines.
24 Commits • 8 Features
May 1, 2025May 2025 monthly summary for ksgeist/Merrimack_DSE6630: Delivered maintainable documentation and demo improvements, enhanced cross-platform compatibility, and advanced ML scaffolding, delivering measurable business value through clearer QA, more robust experiments, and portable data pipelines.
May 2025
Activity
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Quality Metrics
Correctness85.4%
Maintainability85.6%
Architecture72.6%
Performance72.8%
AI Usage22.6%
Skills & Technologies
Programming Languages
HTMLMarkdownRR MarkdownText
Technical Skills
BioinformaticsCode CommentingCode DocumentationData AnalysisData CleaningData ImputationData InterpretationData Leakage PreventionData ManipulationData PreprocessingData ScienceData TransformationData VisualizationData WranglingDocument Formatting
Repositories Contributed To
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