Case studies

Bioinformatics Pipeline Development

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 data complexity, performance optimization, 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 genomic analyses.

Our client

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 biomarkers for improved patient outcomes.

Client’s challenge

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

Client’s goals

Develop and implement robust pipelines tailored to each data-type for comprehensive analysis. Additionally, provide essential bioinformatics support 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.

bioinformatics-pipeline-development-workflow

Input: Data types

  1. RNA-Seq
  2. scRNA-Seq
  3. WGS
  4. WES

Deliverables: Production ready pipelines

  1. RNA-Seq pipeline (Single and paired-end)
  2. scRNA-Seq pipeline (single end and paired end)
  3. HLA typing pipeline
  4. Germline WGS/WES pipeline
  5. SAREK pipeline (Germline, somatic and Tumor)
Implementation Timeline

Figure: Implementation timeline

bioinformatics-pipeline-development-values

Impact and results

Five production-ready pipelines were developed and deployed:
  • scRNA-Seq (single-end and paired-end)
  • Whole Genome Sequencing (WGS)
  • 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 pipelines 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.