Evidence map›Paper›PMID 39298462›Full record

ArticleBioinformatics (Oxford, England)2024

Kssdtree: an interactive Python package for phylogenetic analysis based on sketching technique.

Hang Yang, Xiaoxin Lu, Jiaxing Chang, Qing Chang, Wen Zheng, Zehua Chen, Huiguang Yi

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Hang YangCollege of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Jinzhong 030600, China.
Xiaoxin LuShenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518055, China.
Jiaxing ChangCollege of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Jinzhong 030600, China.
Qing ChangShenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518055, China.
Wen ZhengCollege of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Jinzhong 030600, China.
Zehua ChenCollege of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Jinzhong 030600, China.
Huiguang YiShenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518055, China.

Funding

Shenzhen Basic Research Institutions JCKY2020-44Shenzhen Fundamental Research Program JCYJ20220818103212025
6 · The paper itself

Abstract

summarySketching 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.

Indexed as

PhylogenySoftwareComputational Biology

Identifiers

PMID39298462
PMCPMC11467128

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.