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Meta-analysis of (single-cell method) benchmarks reveals the need for extensibility and interoperability
Anthony Sonrel1,2, Almut Luetge1,2, Charlotte Soneson2,3
1Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.
Genome Biology
|May 17, 2023
Summary
Computational biology benchmarks are crucial for assessing analysis pipelines. While reproducible, current benchmarks are hard to extend, hindering the adoption of new methods and tools.
Area of Science:
- Computational Biology
- Bioinformatics
- Genomics
Background:
- Computational methods are essential in modern molecular biology, particularly for analyzing complex biological data.
- Benchmarking computational tools is critical for evaluating their performance, guiding user choices, and advancing scientific rigor.
Approach:
- A meta-analysis was performed on recent single-cell computational benchmarks.
- The analysis focused on scope, extensibility, neutrality, technical features, and adherence to open data and reproducibility best practices.
Key Points:
- Most benchmarks provide accessible code and are designed for reproducibility.
- However, benchmarks often lack extensibility, making it challenging to incorporate emerging methods or assessment techniques.
- Limited reusability of intermediate results hinders broader adoption and community advancement.
Conclusions:
- Enhancing benchmark extensibility and reusability is vital for the progress of computational biology.
- Adopting containerization and workflow systems can significantly improve the utility and impact of computational benchmarks.
