| name | aamb |
| description | AAMB / AVAMB — adversarial autoencoder metagenomic binning and its ensemble with VAMB for improved near-complete MAG recovery. Use when: (1) Running AAMB as a DL single binner, (2) AVAMB ensemble (VAMB+AAMB) for extra NC genomes, (3) Diversifying bins before DAS Tool/BASALT. Upstream (VAMB tree): https://github.com/RasmussenLab/vamb. Still QC with checkm2; prefer basalt ★ for multi-assembly catalogues.
|
| license | MIT |
| category | analysis-tools |
| tags | ["binning","AAMB","AVAMB","VAMB","deep-learning"] |
| upstream | https://github.com/RasmussenLab/vamb |
| stage | binning |
AAMB / AVAMB
Upstream: RasmussenLab/vamb (AAMB/AVAMB
paths documented in the VAMB repository)
Citation
Piera Líndez, P. et al. Adversarial and variational autoencoders improve
metagenomic binning. Commun. Biol. 6, 1073 (2023).
https://doi.org/10.1038/s42003-023-05452-3
See also docs/references.md.
Analytical thinking
AAMB uses adversarial autoencoders on coabundance + TNF; AVAMB ensembles
AAMB with VAMB and recovered substantially more near-complete genomes in the
paper vs VAMB alone. Treat as a diverse DL binner for ensembles — not a
replacement for basalt multi-assembly refinement.
Related VAMB-family tools: vamb, taxvamb.
How to run
Related skills
vamb · taxvamb · semibin2 · dastool · basalt · tool-selection
