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nf-core/scge Pipeline
Cloud-native tumor-normal sequencing pipeline for the NIH Common Fund's Somatic Cell Genome Editing program. Built with Nextflow DSL2 and DRAGEN hardware acceleration on AWS.
The Problem
The NIH Common Fund’s Somatic Cell Genome Editing (SCGE) program required a reproducible, scalable tumor-normal variant calling pipeline capable of handling petabyte-scale sequencing datasets. Existing workflows lacked the cloud elasticity and hardware acceleration needed for high-depth clinical-grade analysis under tight nf-core reproducibility standards.
The Solution
Co-developed a cloud-native Nextflow DSL2 pipeline adhering to full nf-core community conventions — enabling automated, reproducible somatic variant calling at NIH scale.
Architecture
- Nextflow DSL2 for modular, composable workflow components with strict versioning
- Illumina DRAGEN hardware acceleration on AWS Batch for high-depth tumor-normal variant calling — dramatically reducing compute time vs. software-only approaches
- nf-core conventions for reproducibility, automated testing, CI/CD, and community contribution standards
- Docker/Singularity dual containerization for portability across HPC and cloud environments
- AWS Batch elastic compute scaling — spin up and tear down resources automatically based on input queue depth
Key Results
- Minimized runtime for high-depth tumor-normal variant calling through DRAGEN acceleration
- Full compliance with nf-core community standards, enabling peer review and external validation
- Handles petabyte-scale sequencing datasets with automated ingestion and provenance tracking
- Production-deployed for active NIH SCGE program research cohorts