ARGem

ARGem performs detection, assembly, annotation, and characterization of antibiotic resistance genes (ARGs) and mobile genetic elements from metagenomic short-read DNA sequencing for environmental surveillance.


Key Features:

  • Full-service analysis pipeline: Performs data processing, assembly, and annotation of metagenomic short-read DNA sequencing data.
  • Metadata capture and harmonization: Captures and harmonizes sample metadata to support comparability across projects and monitoring efforts.
  • Efficient short-read assembly: Implements short-read assembly optimized for reasonable runtime to enable accurate ARG annotation.
  • Comprehensive annotation databases: Uses extensive databases for antibiotic resistance genes (ARGs) and mobile genetic elements for gene annotation.
  • Expandable analytical tools: Provides statistical analyses and network analysis capabilities for downstream interpretation.
  • Advanced visualization techniques: Supports visualization of co-occurrence and correlation networks, including output compatible with Cytoscape.
  • Scalability via cloud computing: Can leverage cloud computing resources to scale throughput for larger projects.

Scientific Applications:

  • Environmental surveillance of ARGs: Monitoring prevalence and spread of antibiotic resistance genes in environmental samples.
  • Aquatic metagenome analysis: Characterizing ARGs and mobile genetic elements in aquatic metagenomes.
  • Comparative monitoring across projects: Enabling harmonized comparisons of ARG prevalence across studies through metadata harmonization.
  • Ecological studies of microbiomes: Investigating ARG distribution and dynamics in soil, water bodies, and animal microbiomes.

Methodology:

Integrates data processing, short-read assembly, annotation against ARG and mobile genetic element databases, metadata capture and harmonization, statistical and network analyses, Cytoscape-compatible visualization, and optional scaling via cloud computing resources.

Topics

Details

License:
MIT
Cost:
Free of charge
Tool Type:
workflow
Programming Languages:
Python
Added:
3/27/2024
Last Updated:
11/24/2024

Operations

Publications

Liang X, Zhang J, Kim Y, Ho J, Liu K, Keenum I, Gupta S, Davis B, Hepp SL, Zhang L, Xia K, Knowlton KF, Liao J, Vikesland PJ, Pruden A, Heath LS. ARGem: a new metagenomics pipeline for antibiotic resistance genes: metadata, analysis, and visualization. Frontiers in Genetics. 2023;14. doi:10.3389/fgene.2023.1219297. PMID:37811141. PMCID:PMC10558085.