metaXplor: an interactive viral and microbial metagenomic data manager

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• Managing large, heterogeneous genomic data is a significant challenge for research laboratories.
• Existing tools for metagenomic analysis (e.g., Qiime, Mothur) lack comprehensive solutions for building scalable, searchable online data repositories.
• Scientists require robust software for ongoing genomic research, particularly for shotgun and metabarcoding metagenomics.

Purpose of the Study:

• To introduce metaXplor, a novel web-based application designed for efficient management, sharing, and exploration of metagenomic data.
• To provide a flexible and scalable solution for researchers working with diverse metagenomic datasets.
• To facilitate the creation of searchable online data repositories for genomic research.

Main Methods:

• metaXplor utilizes a flexible NoSQL data model to accommodate heterogeneous dataset contents.
• The application supports incremental data feeding and advanced filtering capabilities for comprehensive data browsing.
• Features include interactive data visualization, BLAST querying, and an integrated pipeline for phylogenetic placement enrichment.

Main Results:

• metaXplor offers a scalable and distributable web-interfaced application for metagenomic data management.
• Its NoSQL model handles outputs from both shotgun and metabarcoding techniques with minimal constraints.
• The system enables exhaustive content browsing and rapid data retrieval through combined filtering.

Conclusions:

• metaXplor facilitates efficient management and exploration of metagenomic data.
• Deployment is simplified through Docker containers, enabling use on academic servers, cloud platforms, or personal computers.
• The application is poised to accelerate adoption within the research community due to its ease of use and deployment.