Adversarial and variational autoencoders improve metagenomic binning.
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ABSTRACT:
SUBMITTER: Lindez PP
PROVIDER: S-EPMC10590447 | biostudies-literature | 2023 Oct
REPOSITORIES: biostudies-literature
Publications
Adversarial and variational autoencoders improve metagenomic binning.
Líndez Pau Piera PP Johansen Joachim J Kutuzova Svetlana S Sigurdsson Arnor Ingi AI Nissen Jakob Nybo JN Rasmussen Simon S
Communications biology 20231021 1
Assembly of reads from metagenomic samples is a hard problem, often resulting in highly fragmented genome assemblies. Metagenomic binning allows us to reconstruct genomes by re-grouping the sequences by their organism of origin, thus representing a crucial processing step when exploring the biological diversity of metagenomic samples. Here we present Adversarial Autoencoders for Metagenomics Binning (AAMB), an ensemble deep learning approach that integrates sequence co-abundances and tetranucleo ...[more]
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