Open AccessNGSpeciesID: DNA barcode and amplicon consensus generation from long‐read sequencing data
Author(s) -
Sahlin Kristoffer,
Lim Marisa C. W.,
Prost Stefan
Publication year - 2021
Publication title -
ecology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.17
H-Index - 63
ISSN - 2045-7758
DOI - 10.1002/ece3.7146
Subject(s) - computer science , nanopore sequencing , amplicon , barcode , dna sequencing , scalability , usability , preprocessor , consensus sequence , computational biology , data mining , biology , base sequence , artificial intelligence , database , dna , genetics , polymerase chain reaction , gene , human–computer interaction , operating system
Third‐generation sequencing technologies, such as Oxford Nanopore Technologies (ONT) and Pacific Biosciences (PacBio), have gained popularity over the last years. These platforms can generate millions of long‐read sequences. This is not only advantageous for genome sequencing projects, but also advantageous for amplicon‐based high‐throughput sequencing experiments, such as DNA barcoding. However, the relatively high error rates associated with these technologies still pose challenges for generating high‐quality consensus sequences. Here, we present NGSpeciesID, a program which can generate highly accurate consensus sequences from long‐read amplicon sequencing technologies, including ONT and PacBio. The tool includes clustering of the reads to help filter out contaminants or reads with high error rates and employs polishing strategies specific to the appropriate sequencing platform. We show that NGSpeciesID produces consensus sequences with improved usability by minimizing preprocessing and software installation and scalability by enabling rapid processing of hundreds to thousands of samples, while maintaining similar consensus accuracy as current pipelines.