Abstract

Biological conclusions based on DNA barcoding and metabarcoding analyses can be strongly influenced by the methods utilized for data generation and curation, leading to varying levels of success in the separation of biological variation from experimental error. The 5′ region of cytochrome c oxidase subunit I (COI-5P) is the most common barcode gene for animals, with conserved structure and function that allows for biologically informed error identification. Here, we present coil (https://CRAN.R-project.org/package=coil), an R package for the pre-processing and frameshift error assessment of COI-5P animal barcode and metabarcode sequence data. The package contains functions for placement of barcodes into a common reading frame, accurate translation of sequences to amino acids, and highlighting insertion and deletion errors. The analysis of 10000 barcode sequences of varying quality demonstrated how coil can place barcode sequences in reading frame and distinguish sequences containing indel errors from error-free sequences with greater than 97.5 accuracy. Package limitations were tested through the analysis of COI-5P sequences from the plant and fungal kingdoms as well as the analysis of potential contaminants nuclear mitochondrial pseudogenes and Wolbachia COI-5P sequences. Results demonstrated that coil is a strong technical error identification method but is not reliable for detecting all biological contaminants.