Kssdtree: an interactive Python package for phylogenetic analysis based on sketching technique
文献类型: 外文期刊
作者: Hang Yang;Xiaoxin Lu;Jiaxing Chang;Qing Chang;Wen Zheng;Zehua Chen;Huiguang Yi
作者机构:
关键词: (1-1-2)
期刊名称: Bioinformatics (Oxford, England)
ISSN: 1367-4811
年卷期: 2024 年 40 卷 10 期
页码:
收录情况: SCIE(2024版)
摘要: SUMMARY: Sketching technologies have recently emerged as a promising solution for real-time, large-scale phylogenetic analysis. However, existing sketching-based phylogenetic tools exhibit drawbacks, including platform restrictions, deficiencies in tree visualization, and inherent distance estimation bias. These limitations collectively impede the overall convenience and efficiency of the analysis. In this study, we introduce Kssdtree, an interactive Python package designed to address these challenges. Kssdtree surpasses other sketching-based tools by demonstrating superior performance in terms of both accuracy and time efficiency on comprehensive benchmarking datasets. Notably, Kssdtree offers key advantages such as intra-species phylogenomic analysis and GTDB-based phylogenetic placement analysis, significantly enhancing the scope and depth of phylogenetic investigations. Through extensive evaluations and comparisons, Kssdtree stands out as an efficient and versatile method for real-time, large-scale phylogenetic analysis. AVAILABILITY AND IMPLEMENTATION: The Kssdtree Python package is freely accessible at https://pypi.org/project/kssdtree and source code is available at https://github.com/yhlink/kssdtree. The documentation and instantiation for the software is available at https://kssdtree.readthedocs.io/en/latest. The video tutorial is available at https://youtu.be/_6hg59Yn-Ws.
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