BlastKOALA and GhostKOALA: KEGG Tools for Functional Characterization of Genome and Metagenome Sequences.

By Minoru Kanehisa, Yoko Sato, Kanae Morishima. Journal of Molecular Biology, 2016

3,617 citations recorded by the source corpus.

BlastKOALA and GhostKOALA are automatic annotation servers for genome and metagenome sequences, which perform KO (KEGG Orthology) assignments to characterize individual gene functions and reconstruct KEGG pathways, BRITE hierarchies and KEGG modules to infer high-level functions of the organism or the ecosystem. Both servers are made freely available at the KEGG Web site (http://www.kegg.jp/blastkoala/). In BlastKOALA, the KO assignment is performed by a modified version of the internally used KOALA algorithm after the BLAST search against a non-redundant dataset of pangenome sequences at the species, genus or family level, which is generated from the KEGG GENES database by retaining the KO content of each taxonomic category. In GhostKOALA, which utilizes more rapid GHOSTX for database search and is suitable for metagenome annotation, the pangenome dataset is supplemented with Cd-hit clusters including those for viral genes. The result files may be downloaded and manipulated for further KEGG Mapper analysis, such as comparative pathway analysis using multiple BlastKOALA results.

Subfields: Ecology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/9b7fd8586b339a053c5f0a4b0618211b2f3bd06e

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Citations in the corpus

KEGG: new perspectives on genomes, pathways, diseases and drugs (2016, methodology): “A non-redundant dataset is a collection of pangenomes created at the species or genus level for prokaryotes and at the genus or family level for eukaryotes by removing redundant sequences but retaining functional contents (KO contents) within each pangenome (1,10).”
Effect of ammonia on anaerobic digestion of municipal solid waste: Inhibitory performance, bioaugmentation and microbiome functional reconstruction (2020, neutral): “2) [42, 43] in normal mode and connected with KEGG IDs with Diamond (v0.”
New approach for understanding genome variations in KEGG (2018, methodology): “A tool to identify antimicrobial resistance in pathogen genomes is available (11) as part of the BlastKOALA server (12,13).”
A practical guide to amplicon and metagenomic analysis of microbiome data (2020, background): “These genes must be combined into functional annotations, such as KEGG Orthology (KO), modules and pathways, representing a form of dimensional reduction (Kanehisa et al., 2016).”
KofamKOALA: KEGG Ortholog assignment based on profile HMM and adaptive score threshold (2019, methodology): “To perform another test using only 20 prokaryotic genomes as test queries, we reduced the target databases either by excluding profile HMMs composed exclusively of eukaryotic sequences (for KofamScan) or by using the target database for prokaryotes (for BlastKOALA, GhostKOALA and KAAS).”
Cometabolism of the Superphylum Patescibacteria with Anammox Bacteria in a Long-Term Freshwater Anammox Column Reactor (2021, methodology): “Predicted amino acid sequences were annotated using KEGG BlastKOALA (KEGG Orthology and Links Annotation) [22].”