frogs_filters
frogs_filters filters Operational Taxonomic Units (OTUs) using multiple criteria to refine metagenomic datasets for downstream analysis.
Key Features:
- Multi-Criteria OTU Filtering: Applies multiple, configurable criteria to filter OTUs in metagenomic datasets.
- Galaxy Integration: Executes filtering workflows via the Galaxy execution engine on the Galaxy@Pasteur instance at Institut Pasteur.
- Programmatic API Access: Interacts with Galaxy using the Galaxy API or the Bioblend library for job submission and management.
- Computational Resource Management: Leverages the Institut Pasteur cluster for job execution and access to storage.
Scientific Applications:
- Metagenomic data analysis: Refines OTU tables to improve community composition, diversity analyses, and downstream statistical inference.
- Microbial ecology: Enables filtering strategies used in ecological assessments to adjust abundance and diversity estimates.
- Clinical microbiology: Supports OTU filtering in clinical microbiome studies for research and diagnostic investigation.
Methodology:
Communication with Galaxy via the Galaxy API or the Bioblend library to submit and manage jobs on the Galaxy@Pasteur execution engine and access cluster storage.
Topics
Collections
Details
- Maturity:
- Mature
- Tool Type:
- web application
- Operating Systems:
- Linux, Windows, Mac
- Added:
- 12/19/2016
- Last Updated:
- 6/16/2020
Operations
Data Inputs & Outputs
Filtering
Inputs
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.
Mareuil F, Doppelt-Azeroual O, Ménager H. A public Galaxy platform at Pasteur used as an execution engine for web services. Unknown Journal. 2017. doi:10.7490/f1000research.1114334.1.