MetaVelvet-DL: a MetaVelvet deep learning extension for de novo metagenome assembly.

ABSTRACT:

Background

The increasing use of whole metagenome sequencing has spurred the need to improve de novo assemblers to facilitate the discovery of unknown species and the analysis of their genomic functions. MetaVelvet-SL is a short-read de novo metagenome assembler that partitions a multi-species de Bruijn graph into single-species sub-graphs. This study aimed to improve the performance of MetaVelvet-SL by using a deep learning-based model to predict the partition nodes in a multi-species de Bruijn graph.

Results

This study showed that the recent advances in deep learning offer the opportunity to better exploit sequence information and differentiate genomes of different species in a metagenomic sample. We developed an extension to MetaVelvet-SL, which we named MetaVelvet-DL, th

SUBMITTER: Liang KC 

PROVIDER: S-EPMC8171044 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature