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NG-Tax 2.0: A Semantic Framework for High-Throughput Amplicon Analysis.

Wasin Poncheewin¹, Gerben D A Hermes², Jesse C J van Dam¹

¹Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Wageningen, Netherlands.

Frontiers in Genetics

|March 3, 2020

Summary

NG-Tax 2.0 enhances microbial community analysis by generating amplicon sequence variants (ASVs) with high precision. This semantic framework improves data interoperability and comparative analysis for microbial ecology studies.

Keywords:

FAIR RDF SPARQL amplicon sequence variants ontology operational taxonomic unit semantic web taxonomic classification

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Published on: October 15, 2019

Area of Science:

Microbial Ecology
Bioinformatics
Genomics

Background:

High-throughput sequencing generates vast amounts of marker gene amplicon data.
Accurate classification and analysis of these sequences are crucial for understanding microbial communities.
Existing frameworks may lack interoperability and detailed provenance tracking.

Purpose of the Study:

To introduce NG-Tax 2.0, a semantic framework for FAIR high-throughput analysis and classification of marker gene amplicon sequences.
To enable robust generation and storage of amplicon sequence variants (ASVs) with full data provenance.
To facilitate large-scale comparative analyses and visualization of microbial community data.

Main Methods:

NG-Tax 2.0 processes various amplicon sequence inputs (e.g., 16S rRNA, 18S rRNA) to generate de novo ASVs.
Utilizes an RDF data model for storing ASVs and their provenance in a graph database.
Integrates with an R Shiny toolbox for interactive analysis and visualization.
Exports extended BIOM 1.0 files for downstream analyses.

Main Results:

NG-Tax 2.0 demonstrated significantly higher precision (0.95) compared to QIIME2-DADA2 (0.58) in mock community evaluations.
Recall was comparable between NG-Tax 2.0 (0.85) and QIIME2-DADA2 (0.77).
The graph database enables efficient querying for comparative analyses across thousands of samples.

Conclusions:

NG-Tax 2.0 provides a FAIR-compliant, high-throughput framework for microbial amplicon sequence analysis.
Its semantic approach and graph database integration enhance data interoperability and analytical capabilities.
The tool offers improved precision for ASV generation, aiding microbial ecology research.