Benchmarking bioinformatic tools for fast and accurate eDNA metabarcoding species identification

Bioinformatic analysis of eDNA metabarcoding data is a crucial step toward rigorously assessing biodiversity. Many programs are now available for each the required analyses, but their relative abilities at providing fast and accurate species lists have seldom been evaluated. We used simulated mock communities real fish to evaluate performance 13 bioinformatic pipelines retrieve occurrence read abundance using 12S mt rRNA gene marker. four indices compare outputs program with samples: sensitivity, F-measure, root-mean-square error (RMSE) on abundances, execution time. found marked differences among only taxonomic assignment step, both in terms F-measure RMSE. Running time was highly different between step. The fastest best were assembled into pipeline. compared this pipeline constructed from existing toolboxes (OBITools, Barque, QIIME 2). Our Barque obtained all appear be better alternatives analysing when complete reference database available. Analysis also indicated only. This study reveals major during choice algorithm can significant impact diversity estimates should made according objectives study.