IGVF-DACC/igvf-catalog
Mar 2025 – Oct 2025
5 Months active
Languages Used
PythonSQLYAMLtypescriptyamlShellTypeScript
Technical Skills
API IntegrationBioinformaticsData ProcessingVariant AnnotationBackend DevelopmentConfiguration Management
Shengcheng Dong
PROFILE
Shengcheng Dong
Over five months, contributed to IGVF-DACC/igvf-catalog by engineering robust data pipelines and enhancing variant and phenotype data integration. Developed Python and TypeScript adapters to support new data formats, including VCF and EBI eQTL, and expanded variant mapping for pharmacogenomics applications. Refactored YAML-driven configurations and database schemas to standardize data representation, improve ingestion reliability, and streamline catalog maintenance. Addressed data deduplication and schema consistency, enabling more accurate downstream analytics. Implemented parallel processing and comprehensive test coverage to reduce ingest errors and accelerate variant-phenotype analysis, resulting in a more maintainable, extensible, and reliable bioinformatics data catalog for research workflows.
Overall Statistics
Feature vs Bugs
70%Features
Repository Contributions
13Total
Bugs
3
Commits
13
Features
7
Lines of code
12,609
Activity Months5
Your Network
120 peopleWork History
October 2025
1 Commits • 1 Features
Oct 1, 2025Month 2025-10: Delivered a key enhancement to the IGVF data catalog by integrating the EBI eQTL Catalog into IGVF-DACC/igvf-catalog. This work added EBI reference files, updated data_sources.yaml with new entries, refactored parsing logic to support the new catalog, and removed unused parameters. The result is a more capable, consistent data catalog with streamlined configuration and improved data discovery for downstream analyses.
1 Commits • 1 Features
Oct 1, 2025Month 2025-10: Delivered a key enhancement to the IGVF data catalog by integrating the EBI eQTL Catalog into IGVF-DACC/igvf-catalog. This work added EBI reference files, updated data_sources.yaml with new entries, refactored parsing logic to support the new catalog, and removed unused parameters. The result is a more capable, consistent data catalog with streamlined configuration and improved data discovery for downstream analyses.
October 2025
August 2025
4 Commits • 1 Features
Aug 1, 2025August 2025 monthly summary for IGVF-DACC/igvf-catalog: Focused on delivering high-value data engineering features, stabilizing data models, and cleaning up legacy clutter to improve data reliability and developer productivity.
August 2025
4 Commits • 1 Features
Aug 1, 2025August 2025 monthly summary for IGVF-DACC/igvf-catalog: Focused on delivering high-value data engineering features, stabilizing data models, and cleaning up legacy clutter to improve data reliability and developer productivity.
July 2025
5 Commits • 3 Features
Jul 1, 2025July 2025: IGVF-DACC/igvf-catalog delivered robust variant data ingestion improvements, expanded format support, and new phenotype data adapters, strengthening data quality and enabling broader analyses. Key features include VCF support and flexible reference allele handling in the variant loader, enhancements to SEMpl data adapters for new formats and compressed inputs, and a coding_variants model upgrade to store protein identifiers. New adapters for SGE and cV2F phenotype data were added with validation, mapping, and database edge relationships, accompanied by tests. These changes reduce ingest errors, expand downstream annotation capabilities, and accelerate end-to-end variant-phenotype analytics. Tech stack and skills demonstrated include TypeScript data models, YAML-driven configurations, adapter development, test coverage, and handling of compressed data inputs.
5 Commits • 3 Features
Jul 1, 2025July 2025: IGVF-DACC/igvf-catalog delivered robust variant data ingestion improvements, expanded format support, and new phenotype data adapters, strengthening data quality and enabling broader analyses. Key features include VCF support and flexible reference allele handling in the variant loader, enhancements to SEMpl data adapters for new formats and compressed inputs, and a coding_variants model upgrade to store protein identifiers. New adapters for SGE and cV2F phenotype data were added with validation, mapping, and database edge relationships, accompanied by tests. These changes reduce ingest errors, expand downstream annotation capabilities, and accelerate end-to-end variant-phenotype analytics. Tech stack and skills demonstrated include TypeScript data models, YAML-driven configurations, adapter development, test coverage, and handling of compressed data inputs.
July 2025
May 2025
2 Commits • 1 Features
May 1, 2025May 2025 – IGVF catalog: Delivered a critical bug fix and data ingestion improvements that strengthen data integrity, catalog reliability, and business value. Focused on deduplication of dbxref data across UniProt records and enhanced file/linking pipelines using ENCODE URLs.
May 2025
2 Commits • 1 Features
May 1, 2025May 2025 – IGVF catalog: Delivered a critical bug fix and data ingestion improvements that strengthen data integrity, catalog reliability, and business value. Focused on deduplication of dbxref data across UniProt records and enhanced file/linking pipelines using ENCODE URLs.
March 2025
1 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary: Implemented a protein-to-genetic variant mapping enhancement for CYP2C19 in igvf-catalog. A new script maps protein-level mutations (hVGS P) to corresponding genetic variants (hVGS C, hVGS G, SPDI) and generates comprehensive mapping files, improving variant representation accuracy and completeness. This supports more reliable pharmacogenomics analyses and downstream clinical decision support.
1 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary: Implemented a protein-to-genetic variant mapping enhancement for CYP2C19 in igvf-catalog. A new script maps protein-level mutations (hVGS P) to corresponding genetic variants (hVGS C, hVGS G, SPDI) and generates comprehensive mapping files, improving variant representation accuracy and completeness. This supports more reliable pharmacogenomics analyses and downstream clinical decision support.
March 2025
Activity
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Quality Metrics
Correctness85.4%
Maintainability83.0%
Architecture84.6%
Performance73.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
PythonSQLShellTypeScriptYAMLtypescriptyaml
Technical Skills
API IntegrationBackend DevelopmentBioinformaticsConfiguration ManagementData CurationData EngineeringData LoadingData ModelingData ParsingData ProcessingData StandardizationData TransformationDatabase ManagementFile HandlingParallel Processing
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