Are we throwing away good data? Evaluation of chimera detection algorithms on long-read amplicons reveals high false-positive rates across algorithms.

ABSTRACT: Long-read amplicon sequencing has enabled us to return to full-length DNA barcodes, which benefit from the higher taxonomic resolution in metabarcoding-based biodiversity studies. However, chimeric sequences (artificial constructs formed when incomplete amplicons fuse during polymerase chain reaction (PCR)) remain challenging, potentially skewing diversity estimates and ecological inferences. Here, we benchmark three de novo chimera detection algorithms, uchime_denovo, removeBimeraDenovo, and chimeras_denovo, on simulated and empirical eukaryotic full-ITS (rRNA ITS1-5.8S-ITS2) datasets to evaluate their precision, sensitivity, and effects on the final OTUs composition/community structure. Upon simulated data, uchime_denovo achieved the highest precision e

SUBMITTER: Hakimzadeh A 

PROVIDER: S-EPMC12684403 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature