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      Early presence of Batrachochytrium dendrobatidis in Mexico with a contemporary dominance of the global panzootic lineage

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          Fitting Linear Mixed-Effects Models Usinglme4

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            Is Open Access

            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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              MUSCLE: multiple sequence alignment with high accuracy and high throughput.

              We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.
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                Author and article information

                Contributors
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                Journal
                Molecular Ecology
                Mol Ecol
                Wiley
                0962-1083
                1365-294X
                January 2021
                December 08 2020
                January 2021
                : 30
                : 2
                : 424-437
                Affiliations
                [1 ]Instituto de Biología Universidad Nacional Autónoma de México Ciudad de México México
                [2 ]Posgrado en Ciencias Biológicas Instituto de Biología Universidad Nacional Autónoma de México Ciudad de México México
                [3 ]Department of Environmental Science, Policy, and Management University of California Berkeley CA USA
                [4 ]Museum of Vertebrate Zoology University of California Berkeley CA USA
                [5 ]School of Biological Sciences Washington State University Vancouver BC USA
                Article
                10.1111/mec.15733
                33205419
                0a9f914b-9cb6-4039-9cf6-2d9174ca85a9
                © 2021

                http://onlinelibrary.wiley.com/termsAndConditions#vor

                http://doi.wiley.com/10.1002/tdm_license_1.1

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