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A pile of pipelines: An overview of the bioinformatics software for metabarcoding data analyses.
Hakimzadeh, Ali; Abdala Asbun, Alejandro; Albanese, Davide; Bernard, Maria; Buchner, Dominik; Callahan, Benjamin; Caporaso, J Gregory; Curd, Emily; Djemiel, Christophe; Brandström Durling, Mikael; Elbrecht, Vasco; Gold, Zachary; Gweon, Hyun S; Hajibabaei, Mehrdad; Hildebrand, Falk; Mikryukov, Vladimir; Normandeau, Eric; Özkurt, Ezgi; M Palmer, Jonathan; Pascal, Géraldine; Porter, Teresita M; Straub, Daniel; Vasar, Martti; Vetrovský, Tomás; Zafeiropoulos, Haris; Anslan, Sten.
Afiliação
  • Hakimzadeh A; Institute of Ecology and Earth Sciences, University of Tartu, Tartu, Estonia.
  • Abdala Asbun A; Department of Marine Microbiology and Biogeochemistry, NIOZ Royal Netherlands Institute for Sea Research, Texel, Netherlands.
  • Albanese D; Unit of Computational Biology, Research and Innovation Centre, Fondazione Edmund Mach, Italy.
  • Bernard M; INRAE, AgroParisTech, GABI, Université Paris-Saclay, Jouy-en-Josas, France.
  • Buchner D; INRAE, SIGENAE, Jouy-en-Josas, France.
  • Callahan B; Aquatic Ecosystem Research, University of Duisburg-Essen, Essen, Germany.
  • Caporaso JG; Department of Population Health and Pathobiology, College of Veterinary Medicine and Bioinformatics Research Center, North Carolina State University, Raleigh, North Carolina, USA.
  • Curd E; Center for Applied Microbiome Science, Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, Arizona, USA.
  • Djemiel C; Vermont Biomedical Research Network, University of Vermont, Burlington, Vermont, USA.
  • Brandström Durling M; Agroécologie, INRAE, Institut Agro, Univ. Bourgogne Franche-Comté, Dijon, France.
  • Elbrecht V; Department of Forest Mycology and Plant Pathology, Swedish University of Agricultural Sciences, Uppsala, Sweden.
  • Gold Z; Aquatic Ecosystem Research, University of Duisburg-Essen, Essen, Germany.
  • Gweon HS; Zachary Gold, NOAA Pacific Marine Environmental Laboratory, Seattle, Washington, USA.
  • Hajibabaei M; UK Centre for Ecology & Hydrology, Oxfordshire, UK.
  • Hildebrand F; School of Biological Sciences, University of Reading, Reading, UK.
  • Mikryukov V; Department of Integrative Biology and Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada.
  • Normandeau E; Gut Microbes & Health, Quadram Institute Bioscience, Norfolk, UK.
  • Özkurt E; Earlham Institute, Norwich Research Park, Norfolk, UK.
  • M Palmer J; Institute of Ecology and Earth Sciences, University of Tartu, Tartu, Estonia.
  • Pascal G; Institut de Biologie Intégrative et des Systèmes, Université Laval, Québec, Québec, Canada.
  • Porter TM; Gut Microbes & Health, Quadram Institute Bioscience, Norfolk, UK.
  • Straub D; Earlham Institute, Norwich Research Park, Norfolk, UK.
  • Vasar M; Center for Forest Mycology Research, Northern Research Station, US Forest Service, Madison, Wisconsin, USA.
  • Vetrovský T; GenPhySE, Université de Toulouse, INRAE, ENVT, Castanet Tolosan, France.
  • Zafeiropoulos H; Department of Integrative Biology and Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada.
  • Anslan S; Quantitative Biology Center (QBiC), University of Tübingen, Tübingen, Germany.
Mol Ecol Resour ; 2023 Aug 07.
Article em En | MEDLINE | ID: mdl-37548515
ABSTRACT
Environmental DNA (eDNA) metabarcoding has gained growing attention as a strategy for monitoring biodiversity in ecology. However, taxa identifications produced through metabarcoding require sophisticated processing of high-throughput sequencing data from taxonomically informative DNA barcodes. Various sets of universal and taxon-specific primers have been developed, extending the usability of metabarcoding across archaea, bacteria and eukaryotes. Accordingly, a multitude of metabarcoding data analysis tools and pipelines have also been developed. Often, several developed workflows are designed to process the same amplicon sequencing data, making it somewhat puzzling to choose one among the plethora of existing pipelines. However, each pipeline has its own specific philosophy, strengths and limitations, which should be considered depending on the aims of any specific study, as well as the bioinformatics expertise of the user. In this review, we outline the input data requirements, supported operating systems and particular attributes of thirty-two amplicon processing pipelines with the goal of helping users to select a pipeline for their metabarcoding projects.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article