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      Using PhyloSuite for molecular phylogeny and tree‐based analyses

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          Abstract

          Phylogenetic analysis has entered the genomics (multilocus) era. For less experienced researchers, conquering the large number of software programs required for a multilocus‐based phylogenetic reconstruction can be somewhat daunting and time‐consuming. PhyloSuite, a software with a user‐friendly GUI, was designed to make this process more accessible by integrating multiple software programs needed for multilocus and single‐gene phylogenies and further streamlining the whole process. In this protocol, we aim to explain how to conduct each step of the phylogenetic pipeline and tree‐based analyses in PhyloSuite. We also present a new version of PhyloSuite (v1.2.3), wherein we fixed some bugs, made some optimizations, and introduced some new functions, including a number of tree‐based analyses, such as signal‐to‐noise calculation, saturation analysis, spurious species identification, and etc. The step‐by‐step protocol includes background information (i.e., what the step does), reasons (i.e., why do the step), and operations (i.e., how to do it). This protocol will help researchers quick‐start their way through the multilocus phylogenetic analysis, especially those interested in conducting organelle‐based analyses.

          Abstract

          A new release of PhyloSuite, capable of conducting tree‐based analyses. Detailed guidelines for each step of phylogenetic and tree‐based analyses, following the “What? Why? and How?” structure. This protocol will help beginners learn how to conduct multilocus phylogenetic analyses and help experienced scientists improve their efficiency.

          Highlights

          • A new release of PhyloSuite, capable of conducting tree‐based analyses.

          • Detailed guidelines for each step of phylogenetic and tree‐based analyses, following the “What, Why, and How” structure.

          • This protocol will help beginners learn how to conduct multilocus phylogenetic analyses and help experienced scientists improve their efficiency.

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          Most cited references99

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          MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms.

          The Molecular Evolutionary Genetics Analysis (Mega) software implements many analytical methods and tools for phylogenomics and phylomedicine. Here, we report a transformation of Mega to enable cross-platform use on Microsoft Windows and Linux operating systems. Mega X does not require virtualization or emulation software and provides a uniform user experience across platforms. Mega X has additionally been upgraded to use multiple computing cores for many molecular evolutionary analyses. Mega X is available in two interfaces (graphical and command line) and can be downloaded from www.megasoftware.net free of charge.
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            RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies

            Motivation: Phylogenies are increasingly used in all fields of medical and biological research. Moreover, because of the next-generation sequencing revolution, datasets used for conducting phylogenetic analyses grow at an unprecedented pace. RAxML (Randomized Axelerated Maximum Likelihood) is a popular program for phylogenetic analyses of large datasets under maximum likelihood. Since the last RAxML paper in 2006, it has been continuously maintained and extended to accommodate the increasingly growing input datasets and to serve the needs of the user community. Results: I present some of the most notable new features and extensions of RAxML, such as a substantial extension of substitution models and supported data types, the introduction of SSE3, AVX and AVX2 vector intrinsics, techniques for reducing the memory requirements of the code and a plethora of operations for conducting post-analyses on sets of trees. In addition, an up-to-date 50-page user manual covering all new RAxML options is available. Availability and implementation: The code is available under GNU GPL at https://github.com/stamatak/standard-RAxML. Contact: alexandros.stamatakis@h-its.org Supplementary information: Supplementary data are available at Bioinformatics online.
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              IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies

              Large phylogenomics data sets require fast tree inference methods, especially for maximum-likelihood (ML) phylogenies. Fast programs exist, but due to inherent heuristics to find optimal trees, it is not clear whether the best tree is found. Thus, there is need for additional approaches that employ different search strategies to find ML trees and that are at the same time as fast as currently available ML programs. We show that a combination of hill-climbing approaches and a stochastic perturbation method can be time-efficiently implemented. If we allow the same CPU time as RAxML and PhyML, then our software IQ-TREE found higher likelihoods between 62.2% and 87.1% of the studied alignments, thus efficiently exploring the tree-space. If we use the IQ-TREE stopping rule, RAxML and PhyML are faster in 75.7% and 47.1% of the DNA alignments and 42.2% and 100% of the protein alignments, respectively. However, the range of obtaining higher likelihoods with IQ-TREE improves to 73.3-97.1%.
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                Author and article information

                Contributors
                dongzhang0725@gmail.com
                Journal
                Imeta
                Imeta
                10.1002/(ISSN)2770-596X
                IMT2
                iMeta
                John Wiley and Sons Inc. (Hoboken )
                2770-5986
                2770-596X
                16 February 2023
                February 2023
                : 2
                : 1 ( doiID: 10.1002/imt2.v2.1 )
                : e87
                Affiliations
                [ 1 ] State Key Laboratory of Grassland Agro‐Ecosystems, and College of Ecology Lanzhou University Lanzhou China
                [ 2 ] Institute of Plant Virology, Fujian Agriculture and Forestry University Fuzhou China
                [ 3 ] Key Laboratory of Aquaculture Disease Control, Ministry of Agriculture, and State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences Wuhan China
                Author notes
                [*] [* ] Correspondence Dong Zhang, State Key Laboratory of Grassland Agro‐Ecosystems, and College of Ecology, Lanzhou University, Lanzhou, 730000, China.

                Email: dongzhang0725@ 123456gmail.com

                Author information
                http://orcid.org/0000-0001-5720-5654
                http://orcid.org/0000-0002-2461-3712
                http://orcid.org/0000-0003-4735-2743
                http://orcid.org/0000-0002-0902-6704
                Article
                IMT287
                10.1002/imt2.87
                10989932
                38868339
                d9cb81e2-3be1-4f97-9b0b-32259b959c6b
                © 2023 The Authors. iMeta published by John Wiley & Sons Australia, Ltd on behalf of iMeta Science.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 04 January 2023
                : 18 November 2022
                : 15 January 2023
                Page count
                Figures: 41, Tables: 1, Pages: 42, Words: 13460
                Funding
                Funded by: National Natural Science Foundation of China , doi 10.13039/501100001809;
                Award ID: 32102840
                Award ID: 31872604
                Funded by: Lanzhou University
                Award ID: 561120206
                Funded by: Science and Technology Project of Gansu Province
                Award ID: 21JR7RA533
                Categories
                Protocol
                Protocol
                Custom metadata
                2.0
                February 2023
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.4.0 mode:remove_FC converted:25.03.2024

                annotation,concatenation,itol,loci,multiple‐sequence alignment,partitioning,trimming

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