Williams, J, Pettorelli, N, Dowell, R, Macdonald, K, Meyer, C, Steyaert, M, Tweedt, S and Ransome, E (2024) SimpleMetaPipeline: Breaking the bioinformatics bottleneck in metabarcoding. Methods in Ecology and Evolution, 15 (11). pp. 1949-1957.

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Abstract

The democratisation of next-generation sequencing has vastly increased the availability of sequencing data from metabarcoding. However, to effectively prepare these metabarcoding data for subsequent analysis, researchers must consistently apply several different bioinformatic tools—including those which denoise reads, cluster sequences and assign taxonomic identities. This often creates a bioinformatics bottleneck in workflows for non-specialists due to obstacles around: (a) integrating different tools, (b) the inability to easily modify and rerun bioinformatic pipelines involving non-scripted (‘point-and-click’) elements and (c) the multiple outputs that may be required of a single dataset (e.g. amplicon sequence variants [ASVs] and operational taxonomic units [OTUs]), which often results in users running pipelines multiple times. Here, we introduce SimpleMetaPipeline, an open-source bioinformatics pipeline implemented in R, which addresses these obstacles. SimpleMetaPipeline integrates the most robust and commonly used existing bioinformatic tools in a single reproducible pipeline, with a streamlined choice of parameters, to generate a sequence data table containing alternative clustering and assignment options. SimpleMetaPipeline accepts demultiplexed paired-end and single reads from multiple sequencing runs. We describe the pipeline and demonstrate how alternative annotations enable the easy implementation of multi-algorithm agreement tests to strengthen inferences. SimpleMetaPipeline represents a valuable addition to the existing library of pipelines, providing easy and reproducible bioinformatics, including a range of commonly desired clustering and assignment options, such as OTUs and ASVs.

Item Type:	Article
Uncontrolled Keywords:	Human Genome; Genetics; Bioengineering; Biotechnology; Networking and Information Technology R&D (NITRD); Generic health relevance; 0502 Environmental Science and Management; 0602 Ecology; 0603 Evolutionary Biology
Subjects:	Q Science > QH Natural history > QH301 Biology
Divisions:	Biological and Environmental Sciences (from Sep 19)
Publisher:	Wiley
SWORD Depositor:	A Symplectic
Date Deposited:	17 Jan 2025 17:10
Last Modified:	17 Jan 2025 17:15
DOI or ID number:	10.1111/2041-210x.14434
URI:	https://researchonline.ljmu.ac.uk/id/eprint/25320

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