TBtools-II: A "one for all, all for one"bioinformatics platform for biological big-data mining

文献类型： 外文期刊

第一作者： Chen, Chengjie

作者： Chen, Chengjie;Wu, Ya;Zeng, Zaohai;Xu, Jing;Liu, Yuanlong;He, Yehua;Xia, Rui;Chen, Chengjie;Zeng, Zaohai;Xu, Jing;Liu, Yuanlong;Xia, Rui;Chen, Chengjie;Zeng, Zaohai;Xu, Jing;Liu, Yuanlong;Xia, Rui;Li, Jiawei;Wang, Xiao;Feng, Junting;Chen, Hao

作者机构：

关键词： TBtools-II; plugin; biological big data; BSA-seq

期刊名称：MOLECULAR PLANT （ 影响因子：27.5； 五年影响因子：22.6 ）

ISSN： 1674-2052

年卷期： 2023 年 16 卷 11 期

页码：

收录情况： SCI

摘要： Since the official release of the stand-alone bioinformatics toolkit TBtools in 2020, its superior functionality in data analysis has been demonstrated by its widespread adoption by many thousands of users and references in more than 5000 academic articles. Now, TBtools is a commonly used tool in biological laboratories. Over the past 3 years, thanks to invaluable feedback and suggestions from numerous users, we have optimized and expanded the functionality of the toolkit, leading to the development of an upgraded version-TBtools-II. In this upgrade, we have incorporated over 100 new features, such as those for comparative genomics analysis, phylogenetic analysis, and data visualization. Meanwhile, to better meet the increasing needs of personalized data analysis, we have launched the plugin mode, which enables users to develop their own plugins and manage their selection, installation, and removal according to individual needs. To date, the plugin store has amassed over 50 plugins, with more than half of them being independently developed and contributed by TBtools users. These plugins offer a range of data analysis options including co-expression network analysis, single-cell data analysis, and bulked segregant analysis sequencing data analysis. Overall, TBtools is now transforming from a stand-alone software to a compre-hensive bioinformatics platform of a vibrant and cooperative community in which users are also developers and contributors. By promoting the theme "one for all, all for one", we believe that TBtools-II will greatly benefit more biological researchers in this big-data era.

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