Improved metagenome binning and assembly using deep variational autoencoders

Despite recent advances in metagenomic binning, reconstruction of microbial species from metagenomics data remains challenging. Here we develop variational autoencoders for metagenomic binning (VAMB), a program that uses deep variational autoencoders to encode sequence coabundance and k -mer distrib...

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Veröffentlicht in:	Nature biotechnology Jg. 39; H. 5; S. 555 - 560
Hauptverfasser:	Nissen, Jakob Nybo, Johansen, Joachim, Allesøe, Rosa Lundbye, Sønderby, Casper Kaae, Armenteros, Jose Juan Almagro, Grønbech, Christopher Heje, Jensen, Lars Juhl, Nielsen, Henrik Bjørn, Petersen, Thomas Nordahl, Winther, Ole, Rasmussen, Simon
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Nature Publishing Group US 01.05.2021 Nature Publishing Group
Schlagworte:	631/114/2785 631/326/2565/2134 631/61/212/2142 Agriculture Bacteroides - genetics Bioinformatics Biomedical and Life Sciences Biomedical Engineering/Biotechnology Biomedicine Biotechnology Clustering Datasets Deep learning Distribution patterns Electronic data processing Genetic research Genome, Bacterial - genetics Genomes Geographical distribution Humans Intestinal microflora Letter Life Sciences Machine learning Metagenome - genetics Metagenomics Methods Microbiomes Microbiota - genetics Microorganisms Molecular Sequence Annotation Nucleotides Software Technology application Denmark
ISSN:	1087-0156, 1546-1696, 1546-1696
Online-Zugang:	Volltext
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