Abstract：
BACKGROUND: With the surge in genomic data driven by advancements in sequencing technologies, the demand for efficient bioinformatics tools for sequence analysis has become paramount. BLAST-like alignment tool (BLAT), a sequence alignment tool, faces limitations in performance efficiency and integration with modern programming environments, particularly Python. This study introduces PxBLAT, a Python-based framework designed to enhance the capabilities of BLAT, focusing on usability, computational efficiency, and seamless integration within the Python ecosystem.
RESULTS: PxBLAT demonstrates significant improvements over BLAT in execution speed and data handling, as evidenced by comprehensive benchmarks conducted across various sample groups ranging from 50 to 600 samples. These experiments highlight a notable speedup, reducing execution time compared to BLAT. The framework also introduces user-friendly features such as improved server management, data conversion utilities, and shell completion, enhancing the overall user experience. Additionally, the provision of extensive documentation and comprehensive testing supports community engagement and facilitates the adoption of PxBLAT.
CONCLUSIONS: PxBLAT stands out as a robust alternative to BLAT, offering performance and user interaction enhancements. Its development underscores the potential for modern programming languages to improve bioinformatics tools, aligning with the needs of contemporary genomic research. By providing a more efficient, user-friendly tool, PxBLAT has the potential to impact genomic data analysis workflows, supporting faster and more accurate sequence analysis in a Python environment.
RESULTS: PxBLAT demonstrates significant improvements over BLAT in execution speed and data handling, as evidenced by comprehensive benchmarks conducted across various sample groups ranging from 50 to 600 samples. These experiments highlight a notable speedup, reducing execution time compared to BLAT. The framework also introduces user-friendly features such as improved server management, data conversion utilities, and shell completion, enhancing the overall user experience. Additionally, the provision of extensive documentation and comprehensive testing supports community engagement and facilitates the adoption of PxBLAT.
CONCLUSIONS: PxBLAT stands out as a robust alternative to BLAT, offering performance and user interaction enhancements. Its development underscores the potential for modern programming languages to improve bioinformatics tools, aligning with the needs of contemporary genomic research. By providing a more efficient, user-friendly tool, PxBLAT has the potential to impact genomic data analysis workflows, supporting faster and more accurate sequence analysis in a Python environment.
摘要：
背景：随着测序技术的进步，基因组数据的激增，对用于序列分析的高效生物信息学工具的需求已经变得至关重要。类似BLAST的对齐工具（BLAT），序列比对工具，在性能效率和与现代编程环境的集成方面面临限制，尤其是Python。本研究介绍了PxBLAT，一个基于Python的框架，旨在增强BLAT的功能，专注于可用性，计算效率，和Python生态系统中的无缝集成。
结果：PxBLAT在执行速度和数据处理方面明显优于BLAT，在50至600个样本的不同样本组中进行的综合基准证明了这一点。这些实验突出了显著的加速，与BLAT相比，减少了执行时间。该框架还引入了用户友好的功能，例如改进的服务器管理，数据转换实用程序，和shell完成，提升整体用户体验。此外,提供广泛的文档和全面的测试支持社区参与并促进PxBLAT的采用。
结论：PxBLAT作为BLAT的强大替代品脱颖而出，提供性能和用户交互增强功能。它的发展强调了现代编程语言改进生物信息学工具的潜力，符合当代基因组研究的需要。通过提供更有效的，用户友好的工具，PxBLAT有可能影响基因组数据分析工作流程，在Python环境中支持更快、更准确的序列分析。
结果：PxBLAT在执行速度和数据处理方面明显优于BLAT，在50至600个样本的不同样本组中进行的综合基准证明了这一点。这些实验突出了显著的加速，与BLAT相比，减少了执行时间。该框架还引入了用户友好的功能，例如改进的服务器管理，数据转换实用程序，和shell完成，提升整体用户体验。此外,提供广泛的文档和全面的测试支持社区参与并促进PxBLAT的采用。
结论：PxBLAT作为BLAT的强大替代品脱颖而出，提供性能和用户交互增强功能。它的发展强调了现代编程语言改进生物信息学工具的潜力，符合当代基因组研究的需要。通过提供更有效的，用户友好的工具，PxBLAT有可能影响基因组数据分析工作流程，在Python环境中支持更快、更准确的序列分析。
