|Summary:||Fast annotation and classification of antibiotic resistance gene-like sequences from metagenomic data.|
- Integrated "ARDB and CARD, the two most commonly used databases. SARG was curated to remove redundant sequences and optimized to facilitate query sequence identification by similarity. A database with a hierarchical structure (type-subtype-reference sequence) was then constructed to facilitate classification (assigning ARG-like sequence to type, subtype and reference sequence) of sequences identified through similarity search." The server utilizes the SARG DB and a hybrid functional gene annotation pipeline to do fast annotation and classification of ARG-like sequences from metagenomic data.
- Source code is available on GitHub.
- Please refer to the manual page for ARGs-OAP
- Supports anonymous access and creation of user logins.
- ARGs-OAP v2.0 with an Expanded SARG Database and Hidden Markov Models for Enhancement Characterization and Quantification of Antibiotic Resistance Genes in Environmental Metagenomes, Xiaole Yin, Xiao-Tao Jiang, Benli Chai, Liguan Li, Ying Yang, James R Cole, James M Tiedje, Tong Zhang. Bioinformatics, bty053, doi:10.1093/bioinformatics/bty053, 02 February 2018
- ARGs-OAP: online analysis pipeline for antibiotic resistance genes detection from metagenomic data using an integrated structured ARG-database, Ying Yang, Xiaotao Jiang, Benli Chai, Liping Ma, Bing Li, Anni Zhang, James R. Cole, James M. Tiedje, and Tong Zhang. Bioinformatics (2016) 32 (15): 2346-2351. doi: 10.1093/bioinformatics/btw136
- ARGs-OAP tagged publications in the Galaxy Publication library
- Environmental Biotechnology Laboratory, Department of Civil Engineering, The University of Hong Kong
- School of Marine Sciences, Sun Yat-Sen University, Guangzhou, China
- Department of Plant, Soil, and Microbial Sciences, Michigan State University