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. ORCID: https://orcid.org/0000-0002-6218-6301; Hajibabaei, Mehrdad; Hildebrand, Falk; Mikryukov, Vladimir; Normandeau, Eric; Özkurt, Ezgi; M. Palmer, Jonathan; Pascal, Géraldine; Porter, Teresita M.; Straub, Daniel; Vasar, Martti; Větrovský, Tomáš; Zafeiropoulos, Haris; Anslan, Sten. 2023 A pile of pipelines: an overview of the bioinformatics software for metabarcoding data analyses. Molecular Ecology Resources. https://doi.org/10.1111/1755-0998.13847

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Abstract/Summary

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.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1111/1755-0998.13847
UKCEH and CEH Sections/Science Areas:	UKCEH Fellows
ISSN:	1755-098X
Additional Keywords:	amplicon data analysis, bioinformatics, environmental DNA, metabarcoding, pipeline, review
NORA Subject Terms:	Computer Science Data and Information
Date made live:	09 Nov 2023 11:18 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/535911

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