Schäfer Richard A, Yang Rendong
Department of Urology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, United States.
Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, United States.
Brief Bioinform. 2025 Jul 2;26(4). doi: 10.1093/bib/bbaf379.
Efficiently querying genomic intervals is fundamental to modern bioinformatics, enabling researchers to extract and analyze specific regions from large genomic datasets. While various tools have been developed for this purpose, there lacks a comprehensive comparison of their performance, memory usage, and practical utility. We present a systematic evaluation of genomic interval query tools using simulated datasets of varying sizes. Our benchmarking framework, segmeter, assesses both basic and complex interval queries, examining runtime performance, memory efficiency, and query precision across different tools. This comprehensive analysis provides insights into the strengths and limitations of different approaches to genomic interval querying, offering guidance for tool selection based on specific use cases and data requirements. The segmeter framework and all benchmark data are freely available, facilitating reproducibility and enabling researchers to conduct their own comparative analyses.
高效查询基因组区间是现代生物信息学的基础，使研究人员能够从大型基因组数据集中提取和分析特定区域。虽然已经为此开发了各种工具，但缺乏对它们的性能、内存使用情况和实际效用的全面比较。我们使用不同大小的模拟数据集对基因组区间查询工具进行了系统评估。我们的基准测试框架segmeter评估基本和复杂的区间查询，检查不同工具的运行时性能、内存效率和查询精度。这种全面分析深入了解了基因组区间查询不同方法的优缺点，为根据特定用例和数据要求选择工具提供了指导。segmeter框架和所有基准数据均可免费获取，便于重复使用，并使研究人员能够进行自己的比较分析。
