Abstract：
We have recently introduced MAPLE (MAximum Parsimonious Likelihood Estimation), a new pandemic-scale phylogenetic inference method exclusively designed for genomic epidemiology. In response to the need for enhancing MAPLE\'s performance and scalability, here we present two key components: (1) CMAPLE software, a highly optimized C++ reimplementation of MAPLE with many new features and advancements; and (2) CMAPLE library, a suite of Application Programming Interfaces to facilitate the integration of the CMAPLE algorithm into existing phylogenetic inference packages. Notably, we have successfully integrated CMAPLE into the widely used IQ-TREE 2 software, enabling its rapid adoption in the scientific community. These advancements serve as a vital step towards better preparedness for future pandemics, offering researchers powerful tools for large-scale pathogen genomic analysis.
摘要：
我们最近引入了MAPLE(MAximum偏似然估计)，一种专门为基因组流行病学设计的新的大流行尺度系统发育推断方法。为了满足提高MAPLE性能和可扩展性的需要，这里我们介绍两个关键组件：(1)CMAPLE软件，MAPLE的高度优化的C++重新实现，具有许多新功能和改进；和（2）CMAPLE库，一套应用程序编程接口，以促进将CMAPLE算法集成到现有的系统发育推理包中。值得注意的是,我们已经成功地将CMAPLE集成到广泛使用的IQ-TREE2软件中，使其在科学界迅速采用。这些进步是为未来大流行做好准备的重要一步，为研究人员提供大规模病原体基因组分析的强大工具。
