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

Journal: BMC bioinformatics
Published Date:

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.

Authors

  • Kuo-Ching Liang
    Department of Psychiatry, School of Medicine, Keio University, Tokyo 160-8582, Japan.
  • Yasubumi Sakakibara
    Department of Biosciences and Informatics, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan yasu@bio.keio.ac.jp.