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PIMENTO: A PrIMEr infereNce TOolkit to facilitate large-scale calling of amplicon sequence variants

Atallah, C.; Richardson, L.; Beracochea, M.; Finn, R. D.

2025-08-20 bioinformatics
10.1101/2025.07.04.663168 bioRxiv
Show abstract

The identification of amplicon sequence variants from DNA metabarcoding data is a common method for revealing the taxonomic makeup of environmental samples, and for allowing comparative studies between similar datasets. A significant hurdle to the large-scale calling of amplicon sequence variants from publicly available nucleotide datasets is the heterogeneous presence of primer sequences in reads, the removal of which is a necessary pre-processing step for this form of analysis. Furthermore, as the details of the experimental primers are rarely captured in the metadata associated with the sequence records, there is a need for a method that can automatically infer the presence and identity of primers in sequencing data. In this work, we introduce PIMENTO, a Python package which uses a dual-strategy approach for identifying primers that are present in sequencing reads to enable their removal, and therefore facilitate amplicon sequence variant calling at scale.

Published in GigaScience (predicted rank #8) · training set

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