A total crapshoot? Evaluating bioinformatic decisions in animal diet metabarcoding analyses

Devon R. O'Rourke, Nicholas A. Bokulich, Matthew D. MacManes & Jeffrey T. Foster
Metabarcoding studies provide a powerful approach to estimate the diversity and abundance of organisms in mixed communities in nature. While strategies exist for optimizing sample and sequence library preparation, best practices for bioinformatic processing of amplicon sequence data are lacking in animal diet studies. Here we evaluate how decisions made in core bioinformatic processes, including sequence filtering, database design, and classification, can influence animal metabarcoding results. We show that denoising methods have lower error rates...
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