childhealthbiostatscore/CHCO-Code
Oct 2024 – Oct 2025
13 Months active
Languages Used
MarkdownRSQLR MarkdownShellRmdPythonQuarto
Technical Skills
Code RefactoringData CleaningFile ManagementBioinformaticsData AnalysisData Visualization
Hailey
PROFILE
Hailey
Hannah Hampson engineered and maintained the CHCO-Code repository, delivering robust pipelines for single-cell and multi-omics data analysis across liver, kidney, and brain research domains. She developed end-to-end workflows for RNA-seq, proteomics, and clinical data, integrating tools like R, Python, and AWS Lambda to enable scalable, reproducible analyses. Her work included modular code refactoring, advanced statistical modeling, and cloud-based data storage using S3, supporting cross-cohort integration and high-throughput processing. By automating quality control, harmonizing metadata, and standardizing file management, Hannah improved data integrity and project maintainability, accelerating insight generation and supporting publication-ready results for translational research teams.
Overall Statistics
Feature vs Bugs
90%Features
Repository Contributions
426Total
Bugs
22
Commits
426
Features
209
Lines of code
436,100
Activity Months13
Your Network
97 people
Work History
October 2025
22 Commits • 10 Features
Oct 1, 2025Summary for 2025-10: Delivered substantial data workflow enhancements across CHCO-Code, emphasizing reproducibility, data integration, and project hygiene. Implemented adipose tissue transcriptomics workflow and persisted data to GitHub; added a new liver PET file and refreshed existing data; updated TODAY/Teenlabs proteomics and GSEA analyses; remodeled manuscript figures and cleaned environment and paths (removing deprecated code and updating directory structures); expanded clinical variants analysis and cell-type annotations (TGs added, updated TG cell types, oro states and hep balloon category); integrated IR data updates with new sources (CROC, RH) and refreshed IR variables; standardized cell naming across the project; created a new project scaffold; and fixed directory handling to ensure proper project structure. These efforts improved data traceability, accelerated downstream analyses, and supported faster decision-making for manuscript-ready insights.
22 Commits • 10 Features
Oct 1, 2025Summary for 2025-10: Delivered substantial data workflow enhancements across CHCO-Code, emphasizing reproducibility, data integration, and project hygiene. Implemented adipose tissue transcriptomics workflow and persisted data to GitHub; added a new liver PET file and refreshed existing data; updated TODAY/Teenlabs proteomics and GSEA analyses; remodeled manuscript figures and cleaned environment and paths (removing deprecated code and updating directory structures); expanded clinical variants analysis and cell-type annotations (TGs added, updated TG cell types, oro states and hep balloon category); integrated IR data updates with new sources (CROC, RH) and refreshed IR variables; standardized cell naming across the project; created a new project scaffold; and fixed directory handling to ensure proper project structure. These efforts improved data traceability, accelerated downstream analyses, and supported faster decision-making for manuscript-ready insights.
October 2025
September 2025
28 Commits • 14 Features
Sep 1, 2025September 2025 monthly results for childhealthbiostatscore/CHCO-Code: Focused on stabilizing data integrity, accelerating analysis, and improving maintainability to deliver reliable research outcomes and faster publication-readiness. Delivered robust data handling fixes, corrected analysis logic, completed core results pipeline, and enhanced repository hygiene and deployment readiness. Business value includes improved data trust for grants, reproducible analyses, faster iterations, and scalable workflows for proteomics and IPA analyses.
September 2025
28 Commits • 14 Features
Sep 1, 2025September 2025 monthly results for childhealthbiostatscore/CHCO-Code: Focused on stabilizing data integrity, accelerating analysis, and improving maintainability to deliver reliable research outcomes and faster publication-readiness. Delivered robust data handling fixes, corrected analysis logic, completed core results pipeline, and enhanced repository hygiene and deployment readiness. Business value includes improved data trust for grants, reproducible analyses, faster iterations, and scalable workflows for proteomics and IPA analyses.
August 2025
11 Commits • 3 Features
Aug 1, 2025Monthly summary for 2025-08 for repository childhealthbiostatscore/CHCO-Code focused on delivering end-to-end data analysis enhancements across liver PET workflows, cross-study brain biomarkers, and cell-type labeling improvements. Emphasizes business value through improved insight generation, data quality, and reproducibility.
11 Commits • 3 Features
Aug 1, 2025Monthly summary for 2025-08 for repository childhealthbiostatscore/CHCO-Code focused on delivering end-to-end data analysis enhancements across liver PET workflows, cross-study brain biomarkers, and cell-type labeling improvements. Emphasizes business value through improved insight generation, data quality, and reproducibility.
August 2025
July 2025
15 Commits • 5 Features
Jul 1, 2025July 2025 monthly summary for CHCO-Code: Key features delivered across the liver and kidney single-cell RNA-seq workstreams, major maintenance improvements, and strong technical execution that enabled cross-cohort clinical insights and reproducibility. Highlights include: Liver scRNA-seq pipeline enhancements with CellChat integration and improved ALT/AST-related visualizations; Cross-cohort liver data integration with NEBULA/DESeq2 differential expression analyses; Kidney organoid marker lists and differential expression; SKAT tutorial and rare variant analysis documentation; Archive old files and stabilize analysis paths, plus a visualization bug fix (UMAP aspect ratio). These efforts delivered measurable business value by improving biomarker interpretability, data consistency, and reproducibility, and expanding the team's capacity to onboard new datasets.
July 2025
15 Commits • 5 Features
Jul 1, 2025July 2025 monthly summary for CHCO-Code: Key features delivered across the liver and kidney single-cell RNA-seq workstreams, major maintenance improvements, and strong technical execution that enabled cross-cohort clinical insights and reproducibility. Highlights include: Liver scRNA-seq pipeline enhancements with CellChat integration and improved ALT/AST-related visualizations; Cross-cohort liver data integration with NEBULA/DESeq2 differential expression analyses; Kidney organoid marker lists and differential expression; SKAT tutorial and rare variant analysis documentation; Archive old files and stabilize analysis paths, plus a visualization bug fix (UMAP aspect ratio). These efforts delivered measurable business value by improving biomarker interpretability, data consistency, and reproducibility, and expanding the team's capacity to onboard new datasets.
June 2025
19 Commits • 4 Features
Jun 1, 2025June 2025 monthly summary for CHCO-Code. Delivered end-to-end organoid RNA-seq analysis pipeline with data loading, pseudobulking, QC, NEBULA differential expression, and rich visualizations (UMAP, volcano plots, pathway analysis). Implemented hepatocyte-focused QC, feature selection, PCA, clustering, and NEBULA-based differential expression with enhanced visualization. Completed cross-dataset liver analysis with differential expression and pathway enrichment via NEBULA and IPA, plus proteomics integration, including harmonized data and robust reporting. Established data storage and I/O infrastructure for liver workflows using S3 (via Cyberduck/reticulate) and prepared a Lambda-based deployment to streamline data processing. Also addressed reliability and reproducibility by updating file paths, preprocessing steps, and library dependencies, improving overall workflow stability. These efforts improve end-to-end scalability, reproducibility, and business value by accelerating insight generation from single-cell analyses and enabling cross-study comparisons.
19 Commits • 4 Features
Jun 1, 2025June 2025 monthly summary for CHCO-Code. Delivered end-to-end organoid RNA-seq analysis pipeline with data loading, pseudobulking, QC, NEBULA differential expression, and rich visualizations (UMAP, volcano plots, pathway analysis). Implemented hepatocyte-focused QC, feature selection, PCA, clustering, and NEBULA-based differential expression with enhanced visualization. Completed cross-dataset liver analysis with differential expression and pathway enrichment via NEBULA and IPA, plus proteomics integration, including harmonized data and robust reporting. Established data storage and I/O infrastructure for liver workflows using S3 (via Cyberduck/reticulate) and prepared a Lambda-based deployment to streamline data processing. Also addressed reliability and reproducibility by updating file paths, preprocessing steps, and library dependencies, improving overall workflow stability. These efforts improve end-to-end scalability, reproducibility, and business value by accelerating insight generation from single-cell analyses and enabling cross-study comparisons.
June 2025
May 2025
42 Commits • 25 Features
May 1, 2025May 2025 delivered a set of robust data pipeline enhancements and analytics features for CHCO-Code, driving reliability, data integrity, and business value across research workflows. The work laid groundwork for scalable cloud deployment, richer multi-omics analyses, and clearer data provenance while reducing operational risk in production deployments.
May 2025
42 Commits • 25 Features
May 1, 2025May 2025 delivered a set of robust data pipeline enhancements and analytics features for CHCO-Code, driving reliability, data integrity, and business value across research workflows. The work laid groundwork for scalable cloud deployment, richer multi-omics analyses, and clearer data provenance while reducing operational risk in production deployments.
April 2025
70 Commits • 43 Features
Apr 1, 2025April 2025 CHCO-Code monthly summary focusing on business value and technical achievements across the liver analysis pipeline, performance, and data quality efforts. Key features delivered: - Liver analysis enhancements and simulation scaffolding: hepatocyte and cell-type analyses, liver pathways updates, dot plots, and initial simulation scaffolding (commits include 9c5723f1ea..., 74a8625027..., ec7faee101..., c9a02f9bae..., 72cf54e978...). - GSEA and dotplot enhancements: GSEA code improvements and dotplot refinements for key transcripts (commits eaa8f067318..., 9f93398c517...). - Oro pathways and oroboros analysis: updated pathways, titles, and oroboros analysis improvements (commits 43f9ad92f6..., f20ba525e2..., ef64ca06e8...). - Performance and scalability: newly introduced parallelization on Lambda and loop optimizations to boost throughput (commits a451d3f821..., 8b7193e69d..., e31a330f0e...). - Data quality, reporting, and modeling robustness: organoid QC improvements, descriptive statistics and Table 1 updates, Markdown outputs from scripts, and updates to analysis workflow (commits ddb04d4534..., a01ff48d5d..., 1372cf4116..., 3309c98cbb..., 7c062dd5b31...). Major bugs fixed: - Commented out FC calculation to fix broken behavior (commit 234cf9071a...). - MT filtering code error fix and validation across analyses (commit b28b9e80d0...). - Removed age adjustment in analysis (commit 4d9f1fb1d93...). - Removed obese control filter to correct data filtering behavior (commit 2bd655939ed6...). Overall impact and accomplishments: - Significantly accelerated analytical throughput and enabled scalable liver/genomics workflows, while improving result quality, reproducibility, and reporting efficiency. The updated pipeline supports full gene-set workflows and more robust filtering, increasing confidence for downstream business decisions and stakeholder communications. Technologies/skills demonstrated: - Parallel and multicore computing (Lambda, HPC), advanced statistical modeling (covariance modeling, REML), and high-throughput data processing pipelines. Proficiency with GSEA/MSigDB, Oroboros workflows, organoid QC, and automated Markdown/report generation.
70 Commits • 43 Features
Apr 1, 2025April 2025 CHCO-Code monthly summary focusing on business value and technical achievements across the liver analysis pipeline, performance, and data quality efforts. Key features delivered: - Liver analysis enhancements and simulation scaffolding: hepatocyte and cell-type analyses, liver pathways updates, dot plots, and initial simulation scaffolding (commits include 9c5723f1ea..., 74a8625027..., ec7faee101..., c9a02f9bae..., 72cf54e978...). - GSEA and dotplot enhancements: GSEA code improvements and dotplot refinements for key transcripts (commits eaa8f067318..., 9f93398c517...). - Oro pathways and oroboros analysis: updated pathways, titles, and oroboros analysis improvements (commits 43f9ad92f6..., f20ba525e2..., ef64ca06e8...). - Performance and scalability: newly introduced parallelization on Lambda and loop optimizations to boost throughput (commits a451d3f821..., 8b7193e69d..., e31a330f0e...). - Data quality, reporting, and modeling robustness: organoid QC improvements, descriptive statistics and Table 1 updates, Markdown outputs from scripts, and updates to analysis workflow (commits ddb04d4534..., a01ff48d5d..., 1372cf4116..., 3309c98cbb..., 7c062dd5b31...). Major bugs fixed: - Commented out FC calculation to fix broken behavior (commit 234cf9071a...). - MT filtering code error fix and validation across analyses (commit b28b9e80d0...). - Removed age adjustment in analysis (commit 4d9f1fb1d93...). - Removed obese control filter to correct data filtering behavior (commit 2bd655939ed6...). Overall impact and accomplishments: - Significantly accelerated analytical throughput and enabled scalable liver/genomics workflows, while improving result quality, reproducibility, and reporting efficiency. The updated pipeline supports full gene-set workflows and more robust filtering, increasing confidence for downstream business decisions and stakeholder communications. Technologies/skills demonstrated: - Parallel and multicore computing (Lambda, HPC), advanced statistical modeling (covariance modeling, REML), and high-throughput data processing pipelines. Proficiency with GSEA/MSigDB, Oroboros workflows, organoid QC, and automated Markdown/report generation.
April 2025
March 2025
32 Commits • 20 Features
Mar 1, 2025March 2025: Delivered end-to-end QC and preprocessing enhancements for scrnaseq data, modularized visualization, refreshed core utilities, and expanded model checks; fixed UMAP labeling bug and improved documentation and project structure to support maintainability and onboarding. These changes improve data quality, reproducibility, and efficiency across CHCO-Code, enabling faster, more reliable downstream analyses.
March 2025
32 Commits • 20 Features
Mar 1, 2025March 2025: Delivered end-to-end QC and preprocessing enhancements for scrnaseq data, modularized visualization, refreshed core utilities, and expanded model checks; fixed UMAP labeling bug and improved documentation and project structure to support maintainability and onboarding. These changes improve data quality, reproducibility, and efficiency across CHCO-Code, enabling faster, more reliable downstream analyses.
February 2025
67 Commits • 33 Features
Feb 1, 2025February 2025 performance summary for childhealthbiostatscore/CHCO-Code. Focused on delivering core data processing enhancements, expanding analytical modeling capabilities, and improving code quality, reproducibility, and workflow hygiene. Key outcomes include end-to-end kidney data updates, mito filtering improvements, liver/kidney analytical modeling upgrades, data integration and terminology standardization, and strengthened scaffolding for multi-analysis workflows, accelerating downstream decision-making and enabling scalable analyses.
67 Commits • 33 Features
Feb 1, 2025February 2025 performance summary for childhealthbiostatscore/CHCO-Code. Focused on delivering core data processing enhancements, expanding analytical modeling capabilities, and improving code quality, reproducibility, and workflow hygiene. Key outcomes include end-to-end kidney data updates, mito filtering improvements, liver/kidney analytical modeling upgrades, data integration and terminology standardization, and strengthened scaffolding for multi-analysis workflows, accelerating downstream decision-making and enabling scalable analyses.
February 2025
January 2025
49 Commits • 18 Features
Jan 1, 2025January 2025 monthly summary for CHCO-Code: Delivered substantial improvements across kidney and liver analytics, reinforced data loading and configuration, and tightened release process. Key features delivered include Venn Diagram and Kidney Analysis Enhancements, Alt/AST Protein Associations Analysis, Single-Cell Liver Data Processing, Kidney Single-Cell Analysis Enhancements, and Oat Analysis Pipeline Improvements with visualization. Major bugs fixed include auto stash before merges for clean merges and cleanup of accidentally saved files/plots, contributing to more reliable builds. Overall impact: faster, more reliable data processing and richer, integrative analyses across kidney, liver, and brain datasets, enabling actionable insights for translational studies. Technologies demonstrated: Python data processing, scRNA-seq analysis pipelines, data loading/config management, and disciplined version control.
January 2025
49 Commits • 18 Features
Jan 1, 2025January 2025 monthly summary for CHCO-Code: Delivered substantial improvements across kidney and liver analytics, reinforced data loading and configuration, and tightened release process. Key features delivered include Venn Diagram and Kidney Analysis Enhancements, Alt/AST Protein Associations Analysis, Single-Cell Liver Data Processing, Kidney Single-Cell Analysis Enhancements, and Oat Analysis Pipeline Improvements with visualization. Major bugs fixed include auto stash before merges for clean merges and cleanup of accidentally saved files/plots, contributing to more reliable builds. Overall impact: faster, more reliable data processing and richer, integrative analyses across kidney, liver, and brain datasets, enabling actionable insights for translational studies. Technologies demonstrated: Python data processing, scRNA-seq analysis pipelines, data loading/config management, and disciplined version control.
December 2024
40 Commits • 18 Features
Dec 1, 2024December 2024 performance highlights for CHCO-Code: Delivered feature-rich analytics and repository improvements that enhance reliability, reproducibility, and speed of downstream analyses. Major work included comprehensive code cleanup and refactor to reduce technical debt; expanded cell-type visualization with heatmaps, UMAPs, and per-cell-type expression; kidney and liver analytics growth with metadata management, ALT/AST integration, and DEG/GSEA support; and automation of Git workflows for safer, repeatable releases. A targeted set of bug fixes and hygiene improvements further streamlined the codebase. These changes increase business value by enabling deeper, faster analyses and more maintainable software foundations.
40 Commits • 18 Features
Dec 1, 2024December 2024 performance highlights for CHCO-Code: Delivered feature-rich analytics and repository improvements that enhance reliability, reproducibility, and speed of downstream analyses. Major work included comprehensive code cleanup and refactor to reduce technical debt; expanded cell-type visualization with heatmaps, UMAPs, and per-cell-type expression; kidney and liver analytics growth with metadata management, ALT/AST integration, and DEG/GSEA support; and automation of Git workflows for safer, repeatable releases. A targeted set of bug fixes and hygiene improvements further streamlined the codebase. These changes increase business value by enabling deeper, faster analyses and more maintainable software foundations.
December 2024
November 2024
30 Commits • 15 Features
Nov 1, 2024November 2024 performance summary for childhealthbiostatscore/CHCO-Code. Delivered end-to-end data pipeline improvements, integrated senescence analytics, and enhanced visualization capabilities, while improving code quality and maintaining robust data governance. These efforts unlock reproducible data workflows, faster insight generation, and stronger business value for downstream stakeholders.
November 2024
30 Commits • 15 Features
Nov 1, 2024November 2024 performance summary for childhealthbiostatscore/CHCO-Code. Delivered end-to-end data pipeline improvements, integrated senescence analytics, and enhanced visualization capabilities, while improving code quality and maintaining robust data governance. These efforts unlock reproducible data workflows, faster insight generation, and stronger business value for downstream stakeholders.
October 2024
1 Commits • 1 Features
Oct 1, 2024Monthly summary for 2024-10 focused on repository hygiene and maintainability for CHCO-Code. Executed targeted cleanup to streamline the codebase by removing legacy assets associated with kidney and liver scRNA analyses. The change reduces clutter, storage usage, and cognitive load for contributors, while preserving current workflows and production integrity.
1 Commits • 1 Features
Oct 1, 2024Monthly summary for 2024-10 focused on repository hygiene and maintainability for CHCO-Code. Executed targeted cleanup to streamline the codebase by removing legacy assets associated with kidney and liver scRNA analyses. The change reduces clutter, storage usage, and cognitive load for contributors, while preserving current workflows and production integrity.
October 2024
Activity
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Quality Metrics
Correctness83.6%
Maintainability82.6%
Architecture78.6%
Performance71.0%
AI Usage21.0%
Skills & Technologies
Programming Languages
MarkdownPythonQuartoRR MarkdownRmdSQLShellqmd
Technical Skills
AWS LambdaAWS S3Bayesian StatisticsBioinformaticsBioinformatics ScriptingBiostatisticsCellChatCellChat AnalysisClinical Data AnalysisCloud IntegrationCloud StorageCloud Storage IntegrationCode OrganizationCode RefactoringCox Proportional Hazards Model
Repositories Contributed To
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