MetaPhinder-Identifying Bacteriophage Sequences in Metagenomic Data Sets

Bacteriophages are the most abundant biological entity on the planet, but at the same time do not account for much of the genetic material isolated from most environments due to their small genome sizes. They also show great genetic diversity and mosaic genomes making it challenging to analyze and u...

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Bibliographic Details
Published in:PloS one 2016-09, Vol.11 (9), p.e0163111-e0163111
Main Authors: Jurtz, Vanessa Isabell, Villarroel, Julia, Lund, Ole, Voldby Larsen, Mette, Nielsen, Morten
Format: Article
Language:English
Subjects:
Acids
Analysis
Antibiotics
Bacteria
Bioinformatics
Biology and Life Sciences
CRISPR
Datasets
Drug resistance
Epidemiology
Gene sequencing
Genes
Genetic diversity
Genetic engineering
Genomes
Genomics
Identification
Methods
Molecular biology
Phages
Proteins
Research and Analysis Methods
Taxonomy
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Summary:Bacteriophages are the most abundant biological entity on the planet, but at the same time do not account for much of the genetic material isolated from most environments due to their small genome sizes. They also show great genetic diversity and mosaic genomes making it challenging to analyze and understand them. Here we present MetaPhinder, a method to identify assembled genomic fragments (i.e.contigs) of phage origin in metagenomic data sets. The method is based on a comparison to a database of whole genome bacteriophage sequences, integrating hits to multiple genomes to accomodate for the mosaic genome structure of many bacteriophages. The method is demonstrated to out-perform both BLAST methods based on single hits and methods based on k-mer comparisons. MetaPhinder is available as a web service at the Center for Genomic Epidemiology https://cge.cbs.dtu.dk/services/MetaPhinder/, while the source code can be downloaded from https://bitbucket.org/genomicepidemiology/metaphinder or https://github.com/vanessajurtz/MetaPhinder.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0163111