Taxonomic metagenome tool

Taxonomic metagenome tool classifies shotgun metagenomic sequences to determine the taxonomic composition of microbial communities from next-generation DNA sequencing data.


Key Features:

  • Taxonomic Classification: Categorizes shotgun metagenomic sequences into taxonomic groups to identify microbial community composition.
  • Sequence Alignment and Classification Algorithms: Implements algorithms for sequence alignment and taxonomic classification.
  • Advanced Statistical and Computational Methods: Applies advanced statistical and computational methods for analysis of large metagenomic datasets.
  • Integration with Galaxy Project: Integrates with the Galaxy Project framework.
  • Scalability for Biomedical Analyses: Scales to large next-generation DNA sequencing datasets for biomedical studies.

Scientific Applications:

  • Microbial Ecology Studies: Enables exploration of microbial community structure and dynamics across environments.
  • Human Microbiome Research: Supports analysis of human-associated microbiomes to study composition related to health and disease.
  • Environmental Monitoring: Facilitates assessment of biodiversity and detection of pathogenic organisms in environmental samples.

Methodology:

Uses algorithms for sequence alignment and classification and applies advanced statistical and computational methods, with integration into the Galaxy Project framework.

Topics

Details

Tool Type:
web application
Operating Systems:
Linux, Windows, Mac
Added:
8/14/2015
Last Updated:
11/25/2024

Operations

Data Inputs & Outputs

Taxonomic classification

Publications

Afgan E, Baker D, van den Beek M, Blankenberg D, Bouvier D, Čech M, Chilton J, Clements D, Coraor N, Eberhard C, Grüning B, Guerler A, Hillman-Jackson J, Von Kuster G, Rasche E, Soranzo N, Turaga N, Taylor J, Nekrutenko A, Goecks J. The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update. Nucleic Acids Research. 2016;44(W1):W3-W10. doi:10.1093/nar/gkw343. PMID:27137889. PMCID:PMC4987906.