EXCEEDS logo
Exceeds
John Orgera

PROFILE

John Orgera

Raj Orge contributed to the mskcc-omics-workflows/modules repository by enhancing neoantigen input pipelines and standardizing module parameters to improve clarity and reliability. He integrated Ensembl annotation data, enabling more accurate genomic predictions, and implemented configurable kD cutoffs with improved mutation and frameshift detection. Raj updated test suites and CI/CD workflows using Nextflow, Python, and GitHub Actions, ensuring compatibility with evolving tool versions and reducing maintenance overhead. His work focused on robust workflow development, aligning cross-module APIs, and automating testing, which streamlined deployment processes and improved end-to-end accuracy for genomic data processing pipelines within a short two-month period.

Overall Statistics

Feature vs Bugs

80%Features

Repository Contributions

19Total
Bugs
1
Commits
19
Features
4
Lines of code
1,135
Activity Months2

Work History

February 2025

13 Commits • 3 Features

Feb 1, 2025

February 2025 monthly summary for mskcc-omics-workflows/modules: Focused on delivering robust Neoantigen input pipeline enhancements, Ensembl annotation integration, and CI/CD improvements. These changes increased prediction accuracy, reliability, and deployment velocity, delivering measurable business value.

December 2024

6 Commits • 1 Features

Dec 1, 2024

Month 2024-12: Consolidated API clarity and pipeline reliability in mskcc-omics-workflows/modules. Delivered cross-module parameter standardization (rename typePan to fromPan) across NETMHCPAN4, netmhc3, and netmhcstabpan; updated tests accordingly. In parallel, fixed CI/test stability by updating snapshots and CI installation to align with newer nf-test and Nextflow versions, ensuring reliable test results going forward. These efforts reduce onboarding friction, lower risk in production deployments, and improve maintainability across the repository.

Activity

Loading activity data...

Quality Metrics

Correctness86.4%
Maintainability87.2%
Architecture81.0%
Performance79.0%
AI Usage20.0%

Skills & Technologies

Programming Languages

GroovyJSONN/ANextflowPythonShellYAMLnf

Technical Skills

BioinformaticsCI/CDCommand Line InterfaceData FilteringData ProcessingDevOpsGenomic Data ProcessingGenomicsGitHub ActionsNextflowNextflow ScriptingPipeline DevelopmentPython ScriptingScriptingTesting

Repositories Contributed To

1 repo

Overview of all repositories you've contributed to across your timeline

mskcc-omics-workflows/modules

Dec 2024 Feb 2025
2 Months active

Languages Used

GroovyN/AYAMLnfJSONNextflowPythonShell

Technical Skills

CI/CDDevOpsTestingWorkflow DevelopmentWorkflow Managementnextflow

Generated by Exceeds AIThis report is designed for sharing and indexing