Overview
Excelra partnered with a leading Computational Oncology department to develop customized, production-ready bioinformatics pipelines tailored for RNA-Seq, scRNA-Seq, WGS/WES, and HLA typing data. The objective was to handle complex biological datasets and enhance research throughput. Addressing challenges in bioinformatics for cancer research, bioinformatics applications, and tool integration, Excelra implemented a modular, scalable architecture using Nextflow and Docker. The phased rollout from Q2 2023 to Q1 2024 included continuous enhancements in error handling, QC, and internalization of Sarek workflows. This initiative empowered oncology researchers with high-performance, reproducible pipelines, significantly accelerating biomarker discovery and bioinformatics solutions for genomic analyses.
Our client
The client is a U.S.-based biotechnology company specializing in oncology. Focused on advancing cancer research, they leverage cutting-edge genomic and bioinformatics technologies to drive the development of precision therapies and precision medicine biomarkers for improved patient outcomes.
Client’s challenge
- Data complexity: Managing diverse biological data formats and structures.
- Algorithm selection: Choosing suitable tools and algorithms for analysis tasks.
- Performance optimization: Ensuring efficiency in speed, resource usage, and scalability.
- Integration challenges: Integrating multiple tools and modules while maintaining
compatibility.
Client’s goals
Develop and implement robust bioinformatic workflows tailored to each data type for comprehensive analysis. Additionally, provide essential scientific application services to enhance the capabilities of the Computational Oncology department in conducting cutting-edge research.
Our approach
Data complexity
Managing diverse biological data formats and structures.
Input: Data types
- RNA-Seq
- scRNA-Seq
- WGS
- WES
Deliverables: Production ready pipelines
- RNA-Seq pipeline (Single and paired-end)
- scRNA-Seq pipeline (single end and paired end)
- HLA typing pipeline
- Germline WGS/WES pipeline
- SAREK pipeline (Germline, somatic and Tumor)
Figure: Implementation timeline
Impact and results
Five production-ready pipelines were developed and deployed:
- RNA-Seq (single-end and paired-end)
- scRNA-Seq (single-end and paired-end)
- Whole Genome Sequencing (WGS)
- Whole Exome Sequencing (WES)
- HLA typing
- SAREK pipeline for germline, somatic, and tumor variant calling
Pipelines were built using a modular architecture and integrated with workflow managers to ensure scalability, reproducibility, and ease of maintenance. Each pipeline underwent comprehensive testing, including benchmarking and User Acceptance Testing (UAT), followed by iterative refinement and improvement. Performance optimization was achieved across resource utilization, execution speed, and tool compatibility. Version control and detailed documentation were established to ensure transparency, facilitate collaboration, and support future updates.
Conclusion
This bioinformatics pipeline development initiative addressed the complex analytical needs of a leading Computational Oncology department. By delivering customized, well-documented, and high-performance bioinformatic workflows across various data types, the project streamlined data analysis workflows, enabling more efficient, accurate, and scalable research. The integration of robust workflow managers and systematic testing ensured long-term reliability and usability, empowering the department to pursue advanced oncology research with greater speed and confidence.
