A pile of pipelines: An overview of the bioinformatics software for metabarcoding data analyses.

TitleA pile of pipelines: An overview of the bioinformatics software for metabarcoding data analyses.
Publication TypeJournal Article
Year of Publication2023
AuthorsHakimzadeh, A, Asbun, AAbdala, Albanese, D, Bernard, M, Buchner, D, Callahan, B, J Caporaso, G, Curd, E, Djemiel, C, Durling, MBrandströ, Elbrecht, V, Gold, Z, Gweon, HS, Hajibabaei, M, Hildebrand, F, Mikryukov, V, Normandeau, E, Özkurt, E, Palmer, JM, Pascal, G, Porter, TM, Straub, D, Vasar, M, Větrovský, T, Zafeiropoulos, H, Anslan, S
JournalMol Ecol Resour
Date Published2023 Aug 07
ISSN1755-0998
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.

DOI10.1111/1755-0998.13847
Alternate JournalMol Ecol Resour
PubMed ID37548515
Grant ListP20 GM103449 / GM / NIGMS NIH HHS / United States
P20GM103449 / GM / NIGMS NIH HHS / United States
ned