MAUI-seq: Metabarcoding Data with Unique Molecular Identifiers

MAUI-seq is a multiplexed high-throughput amplicon sequencing method developed by Bryden Fields at the University of York. It uses unique molecular identifiers (UMIs) to improve error correction by exploiting variation among sequences associated with a single UMI. The method is designed for sensitive and flexible profiling of genetic diversity, applicable to microbial 16S rRNA profiling and environmental DNA metabarcoding.

Use Cases

• Benchmarking error-correction performance against tools like DADA2 and UNOISE3 based on the described method.
• Profiling microbial diversity from 16S rRNA gene sequences based on the described application.
• Analyzing environmental DNA (eDNA) samples for biodiversity assessment based on the metabarcoding application.
• Identifying genuine low-abundance alleles or sequences that resemble chimeras based on the described capability.

Strengths

• Method outperforms established tools DADA2 and UNOISE3 in eliminating chimeric and erroneous reads.
• Enables confident recognition of genuine alleles present at low abundance or resembling chimeras.
• Designed to be readily adaptable to most high-throughput amplicon sequencing applications.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Last update date is unknown; freshness unverified.

Provenance

Source

University of York

Collection Method

A multiplexed high-throughput amplicon sequencing (HTAS) method using unique molecular identifiers (UMIs).