Nature子刊：宏基因组的分箱和组装的新方法 | 热心肠日报
Improved metagenome binning and assembly using deep variational autoencoders
使用深度变分自动编码器改进宏基因组的分箱和组装
10.1038/s41587-020-00777-4
01-04, Article
Abstract & Authors:展开
Abstract:收起
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 distribution information before clustering. We show that a variational autoencoder is able to integrate these two distinct data types without any previous knowledge of the datasets. VAMB outperforms existing state-of-the-art binners, reconstructing 29–98% and 45% more near-complete (NC) genomes on simulated and real data, respectively. Furthermore, VAMB is able to separate closely related strains up to 99.5% average nucleotide identity (ANI), and reconstructed 255 and 91 NC Bacteroides vulgatus and Bacteroides dorei sample-specific genomes as two distinct clusters from a dataset of 1,000 human gut microbiome samples. We use 2,606 NC bins from this dataset to show that species of the human gut microbiome have different geographical distribution patterns. VAMB can be run on standard hardware and is freely available at https://github.com/RasmussenLab/vamb.
First Authors:
Jakob Nybo Nissen
Correspondence Authors:
Simon Rasmussen
All Authors:
Jakob Nybo Nissen,Joachim Johansen,Rosa Lundbye Allesøe,Casper Kaae Sønderby,Jose Juan Almagro Armenteros,Christopher Heje Grønbech,Lars Juhl Jensen,Henrik Bjørn Nielsen,Thomas Nordahl Petersen,Ole Winther,Simon Rasmussen