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      Evolutionary history of Heptapteridae catfishes using ultraconserved elements (Teleostei, Siluriformes)

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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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            Partitionfinder: combined selection of partitioning schemes and substitution models for phylogenetic analyses.

            In phylogenetic analyses of molecular sequence data, partitioning involves estimating independent models of molecular evolution for different sets of sites in a sequence alignment. Choosing an appropriate partitioning scheme is an important step in most analyses because it can affect the accuracy of phylogenetic reconstruction. Despite this, partitioning schemes are often chosen without explicit statistical justification. Here, we describe two new objective methods for the combined selection of best-fit partitioning schemes and nucleotide substitution models. These methods allow millions of partitioning schemes to be compared in realistic time frames and so permit the objective selection of partitioning schemes even for large multilocus DNA data sets. We demonstrate that these methods significantly outperform previous approaches, including both the ad hoc selection of partitioning schemes (e.g., partitioning by gene or codon position) and a recently proposed hierarchical clustering method. We have implemented these methods in an open-source program, PartitionFinder. This program allows users to select partitioning schemes and substitution models using a range of information-theoretic metrics (e.g., the Bayesian information criterion, akaike information criterion [AIC], and corrected AIC). We hope that PartitionFinder will encourage the objective selection of partitioning schemes and thus lead to improvements in phylogenetic analyses. PartitionFinder is written in Python and runs under Mac OSX 10.4 and above. The program, source code, and a detailed manual are freely available from www.robertlanfear.com/partitionfinder.
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              Double indexing overcomes inaccuracies in multiplex sequencing on the Illumina platform

              Due to the increasing throughput of current DNA sequencing instruments, sample multiplexing is necessary for making economical use of available sequencing capacities. A widely used multiplexing strategy for the Illumina Genome Analyzer utilizes sample-specific indexes, which are embedded in one of the library adapters. However, this and similar multiplex approaches come with a risk of sample misidentification. By introducing indexes into both library adapters (double indexing), we have developed a method that reveals the rate of sample misidentification within current multiplex sequencing experiments. With ~0.3% these rates are orders of magnitude higher than expected and may severely confound applications in cancer genomics and other fields requiring accurate detection of rare variants. We identified the occurrence of mixed clusters on the flow as the predominant source of error. The accuracy of sample identification is further impaired if indexed oligonucleotides are cross-contaminated or if indexed libraries are amplified in bulk. Double-indexing eliminates these problems and increases both the scope and accuracy of multiplex sequencing on the Illumina platform.
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                Author and article information

                Contributors
                (View ORCID Profile)
                (View ORCID Profile)
                Journal
                Zoologica Scripta
                Zool Scr
                Wiley
                0300-3256
                1463-6409
                September 2021
                April 28 2021
                September 2021
                : 50
                : 5
                : 543-554
                Affiliations
                [1 ]Instituto de Biociências Universidade Estadual Paulista Botucatu Brazil
                [2 ]Museu de Zoologia Universidade de São Paulo São Paulo Brazil
                [3 ]Departamento de Biologia e Programa de Pós‐Graduação em Biologia Comparada Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto Universidade de São Paulo Ribeirão Preto Brazil
                [4 ]Department of Ichthyology Academy of Natural Sciences of Drexel University Philadelphia PA USA
                [5 ]Museu de Zoologia Centro de Ciências Biológicas Universidade Estadual de Londrina Londrina Brazil
                Article
                10.1111/zsc.12493
                c3622c1c-c31d-402e-bc2e-fc4df521b857
                © 2021

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

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

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