Abstract
BackgroundPhages 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.FindingsWe 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.ConclusionsTo 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.
Highlights
Reviewer Comments to Author: Authors present a tool which is able to perform multiclass prediction of phage, plasmid and chromosome sequences in metagenomic data. Using this deep learning approach along with its architecture and the weighted average of all windows is worthy of publication by itself
The same thing may be said about phages/prophages, chromosomes and plasmids
Some other minor comments: Page 5, line 13: "research has shown that viral sequences are highly fragmented in the metagenome [19], which may prevent binning, thereby limiting the usage of MARVEL." This is an unfair affirmation, since its only supporting reference is a 2013 article and it is safe to say that much has been done to improve metagenomic assemblers since
Summary
Title: PPR-Meta: a tool for identifying phages and plasmids from metagenomic fragments using deep learning Reviewer Comments to Author: Authors present a tool which is able to perform multiclass prediction of phage, plasmid and chromosome sequences in metagenomic data. Some other minor comments: Page 5, line 13: "research has shown that viral sequences are highly fragmented in the metagenome [19], which may prevent binning, thereby limiting the usage of MARVEL." This is an unfair affirmation, since its only supporting reference is a 2013 article and it is safe to say that much has been done to improve metagenomic assemblers since .
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
