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TREEasy: An automated workflow to infer gene trees, species trees, and phylogenetic networks from multilocus data
https://oist.repo.nii.ac.jp/records/1536
https://oist.repo.nii.ac.jp/records/1536b8fe06ed-0948-4ac5-9ebb-b0bf8ed1789b
名前 / ファイル | ライセンス | アクション |
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Mao_et_al-2020-Molecular_Ecology_Resources (5.4 MB)
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Item type | 学術雑誌論文 / Journal Article(1) | |||||
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公開日 | 2020-06-04 | |||||
タイトル | ||||||
言語 | en | |||||
タイトル | TREEasy: An automated workflow to infer gene trees, species trees, and phylogenetic networks from multilocus data | |||||
言語 | ||||||
言語 | eng | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
資源タイプ | journal article | |||||
著者(英) |
Mao, Yafei
× Mao, Yafei× Hou, Siqing× Shi, Junfeng× Economo, Evan P. |
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書誌情報 |
en : Molecular Ecology Resources 巻 20, 号 3, p. 832-840, 発行日 2020-03-24 |
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抄録 | ||||||
内容記述タイプ | Other | |||||
内容記述 | Multilocus genomic data sets can be used to infer a rich set of information about the evolutionary history of a lineage, including gene trees, species trees, and phylogenetic networks. However, user-friendly tools to run such integrated analyses are lacking, and workflows often require tedious reformatting and handling time to shepherd data through a series of individual programs. Here, we present a tool written in Python-TREEasy-that performs automated sequence alignment (with MAFFT), gene tree inference (with IQ-Tree), species inference from concatenated data (with IQ-Tree and RaxML-NG), species tree inference from gene trees (with ASTRAL, MP-EST, and STELLS2), and phylogenetic network inference (with SNaQ and PhyloNet). The tool only requires FASTA files and nine parameters as inputs. The tool can be run as command line or through a Graphical User Interface (GUI). As examples, we reproduced a recent analysis of staghorn coral evolution, and performed a new analysis on the evolution of the "WGD clade" of yeast. The latter revealed novel patterns that were not identified by previous analyses. TREEasy represents a reliable and simple tool to accelerate research in systematic biology (https://github.com/MaoYafei/TREEasy). | |||||
出版者 | ||||||
出版者 | John Wiley & Sons | |||||
ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 1755-098X | |||||
ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 1755-0998 | |||||
PubMed番号 | ||||||
関連タイプ | isVersionOf | |||||
識別子タイプ | PMID | |||||
関連識別子 | info:pmid/32073732 | |||||
DOI | ||||||
関連タイプ | isVersionOf | |||||
識別子タイプ | DOI | |||||
関連識別子 | info:doi/10.1111/1755-0998.13149 | |||||
権利 | ||||||
権利情報 | © 2020 John Wiley & Sons Ltd | |||||
権利 | ||||||
権利情報 | This is the peer reviewed version of the following article: Mao, Y, Hou, S, Shi, J, Economo, EP. TREEasy: An automated workflow to infer gene trees, species trees, and phylogenetic networks from multilocus data. Mol Ecol Resour. 2020; 20: 832– 840., which has been published in final form at https://doi.org/10.1111/1755-0998.13149. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. | |||||
関連サイト | ||||||
識別子タイプ | URI | |||||
関連識別子 | https://onlinelibrary.wiley.com/doi/full/10.1111/1755-0998.13149 | |||||
著者版フラグ | ||||||
出版タイプ | AM | |||||
出版タイプResource | http://purl.org/coar/version/c_ab4af688f83e57aa |