期刊
GIGASCIENCE
卷 8, 期 6, 页码 -出版社
OXFORD UNIV PRESS
DOI: 10.1093/gigascience/giz066
关键词
metagenome; mobile genetic elements; horizontal gene transfer; phage; plasmid; deep learning
资金
- National Key Research and Development Program of China [2017YFC1200205]
- National Natural Science Foundation of China [31671366]
- Special Research Project of Clinical Medicine + X by Peking University
Background: Phages and plasmids are the major components of mobile genetic elements, and fragments from such elements generally co-exist with chromosome-derived fragments in sequenced metagenomic data. However, there is a lack of efficient methods that can simultaneously identify phages and plasmids in metagenomic data, and the existing tools identifying either phages or plasmids have not yet presented satisfactory performance. Findings: We present PPR-Meta, a 3-class classifier that allows simultaneous identification of both phage and plasmid fragments from metagenomic assemblies. PPR-Meta consists of several modules for predicting sequences of different lengths. Using deep learning, a novel network architecture, referred to as the Bi-path Convolutional Neural Network, is designed to improve the performance for short fragments. PPR-Meta demonstrates much better performance than currently available similar tools individually for phage or plasmid identification, while testing on both artificial contigs and real metagenomic data. PPR-Meta is freely available via http://cqb.pku.edu.cn/ZhuLab/PPR Meta or https://github.com/zhenchengfang/PPR-Meta. Conclusions: To the best of our knowledge, PPR-Meta is the first tool that can simultaneously identify phage and plasmid fragments efficiently and reliably. The software is optimized and can be easily run on a local PC by non-computer professionals. We developed PPR-Meta to promote the research on mobile genetic elements and horizontal gene transfer.
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