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
Outputs
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.