Abstract
| Original language | English |
|---|---|
| Article number | e0163111 |
| Journal | P L o S One |
| Volume | 11 |
| Issue number | 9 |
| Number of pages | 14 |
| ISSN | 1932-6203 |
| DOIs | |
| Publication status | Published - 2016 |
Bibliographical note
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Cite this
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MetaPhinder-Identifying Bacteriophage Sequences in Metagenomic Data Sets. / Jurtz, Vanessa Isabell; Villarroel, Julia; Lund, Ole; Larsen, Mette Voldby; Nielsen, Morten.
In: P L o S One, Vol. 11, No. 9, e0163111, 2016.Research output: Contribution to journal › Journal article › Research › peer-review
TY - JOUR
T1 - MetaPhinder-Identifying Bacteriophage Sequences in Metagenomic Data Sets
AU - Jurtz, Vanessa Isabell
AU - Villarroel, Julia
AU - Lund, Ole
AU - Larsen, Mette Voldby
AU - Nielsen, Morten
N1 - This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2016
Y1 - 2016
N2 - 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 metage-nomic 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 outperform 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.
AB - 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 metage-nomic 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 outperform 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.
U2 - 10.1371/journal.pone.0163111
DO - 10.1371/journal.pone.0163111
M3 - Journal article
C2 - 27684958
VL - 11
JO - P L o S One
JF - P L o S One
SN - 1932-6203
IS - 9
M1 - e0163111
ER -