Supplemental Data and Results Package for Pappalardo et al (2025) publication "Taxon-specific BLAST percent identity thresholds for identification of unknown sequences using metabarcoding"

This data package includes input data and results associated with the publication “Taxon-specific BLAST percent identity thresholds for identification of unknown sequences using metabarcoding” by Pappalardo et al. (2025) in Methods in Ecology and Evolution. We developed taxon-specific confidence thresholds for marine eukaryotes to improve the performance of BLAST-based assignment methods. To benchmark the taxonomic assignments and generate the thresholds, we used the MIDORI2 reference database. We also tested our approach using published whole-community DNA datasets and evaluated factors that affect the accuracy of taxonomic assignments. We provide confidence thresholds for multiple taxonomic levels using the mitochondrial cytochrome c oxidase subunit I (COI) and large ribosomal RNA (lrRNA or 16S rRNA in metazoans) to achieve five false positive error rates (0%, 1%, 5%, 10%, and 20%). Additionally, we tested two methods to pick the BLAST final hit, the best-hit and best-shared (similar to the lowest common ancestor) methods. Our results suggest that using taxon-optimized thresholds can increase taxonomic assignment at higher taxonomic levels while preventing misclassifications at lower taxonomic levels. By defining a predefined error rate, the user can decide on the acceptable error for their study goal. The paper has a companion R Shiny application for a user-friendly way to apply the thresholds to users’ datasets. The R Shiny application is available at [https://shiny.si.edu/ebbs_blast_filter/](https://shiny.si.edu/ebbs_blast_filter/) and [https://paulapappalardo.shinyapps.io/ebbs_blast_filter/](https://paulapappalardo.shinyapps.io/ebbs_blast_filter/).