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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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Published in: | PloS one 2016-09, Vol.11 (9), p.e0163111-e0163111 |
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description | 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. |
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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.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0163111</identifier><identifier>PMID: 27684958</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>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</subject><ispartof>PloS one, 2016-09, Vol.11 (9), p.e0163111-e0163111</ispartof><rights>COPYRIGHT 2016 Public Library of Science</rights><rights>2016 Jurtz et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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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.</description><subject>Acids</subject><subject>Analysis</subject><subject>Antibiotics</subject><subject>Bacteria</subject><subject>Bioinformatics</subject><subject>Biology and Life Sciences</subject><subject>CRISPR</subject><subject>Datasets</subject><subject>Drug resistance</subject><subject>Epidemiology</subject><subject>Gene sequencing</subject><subject>Genes</subject><subject>Genetic diversity</subject><subject>Genetic engineering</subject><subject>Genomes</subject><subject>Genomics</subject><subject>Identification</subject><subject>Methods</subject><subject>Molecular biology</subject><subject>Phages</subject><subject>Proteins</subject><subject>Research and Analysis 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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 |
title | MetaPhinder-Identifying Bacteriophage Sequences in Metagenomic Data Sets |
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