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Author, Editor(s)

Author(s):

Lawyer, Glenn

dblp

Not MPG Author(s):

Struck, Daniel
Ternes, Anne-Marie
Schmit, Jean-Claude
Perez-Bercoff, Danielle

BibTeX cite key*:

Struck2014

Title

Title*:

COMET: Adaptive context-based modeling for ultrafast HIV-1 subtype identification.

Journal

Journal Title*:

Nucleic Acids Research

Journal's URL:


Download URL
for the article:

http://dx.doi.org/10.1093/nar/gku739

Language:

English

Publisher

Publisher's
Name:


Publisher's URL:


Publisher's
Address:


ISSN:


Vol, No, pp, Date

Volume*:

42

Number:

18

Publishing Date:

2014

Pages*:

e144

Number of
VG Pages:


Page Start:


Page End:


Sequence Number:


DOI:


Note, Abstract, ©

Note:


(LaTeX) Abstract:

iral sequence classification has wide applications in clinical, epidemiological,
structural and functional categorization studies. Most existing approaches
rely on an initial alignment step followed by classification based
on phylogenetic or statistical algorithms. Here we present an ultrafast
alignment-free subtyping tool for human immunodeficiency virus type
one (HIV-1) adapted from Prediction by Partial Matching compression.
This tool, named COMET, was compared to the widely used phylogeny-based
REGA and SCUEAL tools using synthetic and clinical HIV data sets
(1,090,698 and 10,625 sequences, respectively). COMET's sensitivity
and specificity were comparable to or higher than the two other subtyping
tools on both data sets for known subtypes. COMET also excelled in
detecting and identifying new recombinant forms, a frequent feature
of the HIV epidemic. Runtime comparisons showed that COMET was almost
as fast as USEARCH. This study demonstrates the advantages of alignment-free
classification of viral sequences, which feature high rates of variation,
recombination and insertions/deletions. COMET is free to use via
an online interface.

URL for the Abstract:


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Access Level:

Internal

Correlation

MPG Unit:

Max-Planck-Institut für Informatik



MPG Subunit:

Computational Biology and Applied Algorithmics

Audience:

experts only

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BibTeX Entry:

@ARTICLE{Struck2014,
AUTHOR = {Lawyer, Glenn},
TITLE = {{COMET}: {A}daptive context-based modeling for ultrafast {HIV-1} subtype identification.},
JOURNAL = {Nucleic Acids Research},
YEAR = {2014},
NUMBER = {18},
VOLUME = {42},
PAGES = {e144},
}


Entry last modified by Glenn Lawyer, 02/18/2015
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Editor(s)
Glenn Lawyer
Created
02/18/2015 12:28:12 PM
Revision
0.



Editor
Glenn Lawyer



Edit Date
02/18/2015 12:28:12 PM