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      THAPBI PICT—a fast, cautious, and accurate metabarcoding analysis pipeline

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          Abstract

          THAPBI PICT is an open source software pipeline for metabarcoding analysis of Illumina paired-end reads, including cases of multiplexing where more than one amplicon is amplified per DNA sample. Initially a Phytophthora ITS1 Classification Tool (PICT), we demonstrate using worked examples with our own and public data sets how, with appropriate primer settings and a custom database, it can be applied to other amplicons and organisms, and used for reanalysis of existing datasets. The core dataflow of the implementation is (i) data reduction to unique marker sequences, often called amplicon sequence variants (ASVs), (ii) dynamic thresholds for discarding low abundance sequences to remove noise and artifacts (rather than error correction by default), before (iii) classification using a curated reference database. The default classifier assigns a label to each query sequence based on a database match that is either perfect, or a single base pair edit away (substitution, deletion or insertion). Abundance thresholds for inclusion can be set by the user or automatically using per-batch negative or synthetic control samples. Output is designed for practical interpretation by non-specialists and includes a read report (ASVs with classification and counts per sample), sample report (samples with counts per species classification), and a topological graph of ASVs as nodes with short edit distances as edges. Source code available from https://github.com/peterjc/thapbi-pict/ with documentation including installation instructions.

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          Most cited references56

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          Trimmomatic: a flexible trimmer for Illumina sequence data

          Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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            Cytoscape: a software environment for integrated models of biomolecular interaction networks.

            Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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              DADA2: High resolution sample inference from Illumina amplicon data

              We present DADA2, a software package that models and corrects Illumina-sequenced amplicon errors. DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. In several mock communities DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.
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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ Inc. (San Diego, USA )
                2167-8359
                18 August 2023
                2023
                : 11
                : e15648
                Affiliations
                [1 ]Information and Computational Sciences, The James Hutton Institute , Dundee, United Kingdom
                [2 ]Cell and Molecular Sciences, The James Hutton Institute , Dundee, United Kingdom
                [3 ]The Data Analysis Group, School of Life Sciences, The University of Dundee , Dundee, United Kingdom
                [4 ]Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde , Glasgow, United Kingdom
                Author information
                http://orcid.org/0000-0001-9513-9993
                http://orcid.org/0000-0002-9154-7954
                http://orcid.org/0000-0002-8392-2822
                Article
                15648
                10.7717/peerj.15648
                10441533
                37609440
                b00fa27a-e8fd-4c54-a98b-f995a1da96cb
                © 2023 Cock et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.

                History
                : 30 March 2023
                : 6 June 2023
                Funding
                Funded by: Biotechnology and Biological Sciences Research Council (BBSRC)
                Funded by: Department for Environment, Food and Rural affairs (DEFRA)
                Funded by: Economic and Social Research Council (ESRC)
                Funded by: Forestry Commission, Natural Environment Research Council (NERC)
                Funded by: Scottish Government, under the Tree Health and Plant Biosecurity Initiative
                Award ID: BB/N023463/1
                Funded by: DEFRA
                Funded by: Euphresco ID-PHYT
                Funded by: Rural & Environment Science & Analytical Services (RESAS)
                Funded by: Division of the Scottish Government
                This research was supported by a grant funded jointly by the Biotechnology and Biological Sciences Research Council (BBSRC), Department for Environment, Food and Rural affairs (DEFRA), Economic and Social Research Council (ESRC), Forestry Commission, Natural Environment Research Council (NERC) and Scottish Government, under the Tree Health and Plant Biosecurity Initiative, grant number BB/N023463/1. Also partly funded by DEFRA as part of the Future Proofing Plant Health project in support of Euphresco ID-PHYT, and by the Rural & Environment Science & Analytical Services (RESAS) Division of the Scottish Government. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Biodiversity
                Bioinformatics
                Ecology
                Taxonomy

                amplicon,environmental dna,biodiversity,barcoding,metabarcoding,phytophthora

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