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      Does phylogeny explain bias in quantitative DNA metabarcoding?

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      Metabarcoding and Metagenomics
      Pensoft Publishers

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          Abstract

          Estimating species biomass or abundance from the number of high-throughput sequencing (HTS) reads is an aspirational goal for DNA metabarcoding, yet studies have found varied correlations. Performance varies depending on the gene marker and taxonomic group and, in part, may be related to primer-template mismatches, which are likely to exhibit phylogenetic signals. In this study, we compared commonly used fragments of two gene markers for beetles, the mitochondrial cytochrome c oxidase subunit I (COI) and 16S ribosomal RNA (16S), which have similar lengths, but different propensity for primer-template mismatches. We tested whether primer-template mismatches influence the relationship between species biomass and HTS read abundance and whether the effect of mismatches was explained by phylogeny. A significant correlation between species biomass and HTS read abundance existed for 16S, but not for COI, which had more primer-template mismatches. Models incorporating the effects of mismatch type or number improved the estimation of species biomass from HTS read abundance for COI and strong phylogenetic signals were identified. Researchers seeking to quantify biomass from metabarcoding studies should consider the effect of primer-template mismatches for the taxonomic group of interest and, for beetles, 16S appears a good candidate. Phylogenetic correction can also improve biomass estimation when using gene markers with higher primer mismatching.

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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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            phytools: an R package for phylogenetic comparative biology (and other things)

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              brms: An R Package for Bayesian Multilevel Models Using Stan

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                Author and article information

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                Journal
                Metabarcoding and Metagenomics
                MBMG
                Pensoft Publishers
                2534-9708
                June 13 2023
                June 13 2023
                : 7
                Article
                10.3897/mbmg.7.101266
                e59802ca-cf85-4636-b266-b64f608f3f5f
                © 2023

                http://creativecommons.org/licenses/by/4.0/

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