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WordSeeker: concurrent bioinformatics software for discovering genome-wide patterns and word-based genomic signatures

Identifieur interne : 000038 ( France/Analysis ); précédent : 000037; suivant : 000039

WordSeeker: concurrent bioinformatics software for discovering genome-wide patterns and word-based genomic signatures

Auteurs : Jens Lichtenberg [États-Unis] ; Kyle Kurz [États-Unis] ; Xiaoyu Liang [États-Unis] ; Rami Al-Ouran [États-Unis] ; Lev Neiman [États-Unis] ; Lee J. Nau [États-Unis] ; Joshua D. Welch [États-Unis] ; Edwin Jacox [France] ; Thomas Bitterman [États-Unis] ; Klaus Ecker [États-Unis] ; Laura Elnitski [États-Unis] ; Frank Drews [États-Unis] ; Stephen Sauchi Lee [États-Unis] ; Lonnie R. Welch [États-Unis]

Source :

RBID : PMC:3040532

Abstract

Background

An important focus of genomic science is the discovery and characterization of all functional elements within genomes. In silico methods are used in genome studies to discover putative regulatory genomic elements (called words or motifs). Although a number of methods have been developed for motif discovery, most of them lack the scalability needed to analyze large genomic data sets.

Methods

This manuscript presents WordSeeker, an enumerative motif discovery toolkit that utilizes multi-core and distributed computational platforms to enable scalable analysis of genomic data. A controller task coordinates activities of worker nodes, each of which (1) enumerates a subset of the DNA word space and (2) scores words with a distributed Markov chain model.

Results

A comprehensive suite of performance tests was conducted to demonstrate the performance, speedup and efficiency of WordSeeker. The scalability of the toolkit enabled the analysis of the entire genome of Arabidopsis thaliana; the results of the analysis were integrated into The Arabidopsis Gene Regulatory Information Server (AGRIS). A public version of WordSeeker was deployed on the Glenn cluster at the Ohio Supercomputer Center.

Conclusion

WordSeeker effectively utilizes concurrent computing platforms to enable the identification of putative functional elements in genomic data sets. This capability facilitates the analysis of the large quantity of sequenced genomic data.


Url:
DOI: 10.1186/1471-2105-11-S12-S6
PubMed: 21210985
PubMed Central: 3040532


Affiliations:


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PMC:3040532

Le document en format XML

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<name sortKey="Bitterman, Thomas" sort="Bitterman, Thomas" uniqKey="Bitterman T" first="Thomas" last="Bitterman">Thomas Bitterman</name>
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<name sortKey="Lee, Stephen Sauchi" sort="Lee, Stephen Sauchi" uniqKey="Lee S" first="Stephen Sauchi" last="Lee">Stephen Sauchi Lee</name>
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<sec>
<title>Background</title>
<p>An important focus of genomic science is the discovery and characterization of all functional elements within genomes.
<italic>In silico</italic>
methods are used in genome studies to discover putative regulatory genomic elements (called words or motifs). Although a number of methods have been developed for motif discovery, most of them lack the scalability needed to analyze large genomic data sets.</p>
</sec>
<sec>
<title>Methods</title>
<p>This manuscript presents WordSeeker, an enumerative motif discovery toolkit that utilizes multi-core and distributed computational platforms to enable scalable analysis of genomic data. A controller task coordinates activities of worker nodes, each of which (1) enumerates a subset of the DNA
<italic>word space</italic>
and (2) scores words with a distributed Markov chain model.</p>
</sec>
<sec>
<title>Results</title>
<p>A comprehensive suite of performance tests was conducted to demonstrate the performance, speedup and efficiency of WordSeeker. The scalability of the toolkit enabled the analysis of the entire genome of
<italic>Arabidopsis thaliana</italic>
; the results of the analysis were integrated into The Arabidopsis Gene Regulatory Information Server (AGRIS). A public version of WordSeeker was deployed on the Glenn cluster at the Ohio Supercomputer Center.</p>
</sec>
<sec>
<title>Conclusion</title>
<p>WordSeeker effectively utilizes concurrent computing platforms to enable the identification of putative functional elements in genomic data sets. This capability facilitates the analysis of the large quantity of sequenced genomic data.</p>
</sec>
</div>
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<affiliations>
<list>
<country>
<li>France</li>
<li>États-Unis</li>
</country>
<region>
<li>Maryland</li>
<li>Provence-Alpes-Côte d'Azur</li>
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<li>Marseille</li>
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<name sortKey="Lichtenberg, Jens" sort="Lichtenberg, Jens" uniqKey="Lichtenberg J" first="Jens" last="Lichtenberg">Jens Lichtenberg</name>
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<name sortKey="Al Ouran, Rami" sort="Al Ouran, Rami" uniqKey="Al Ouran R" first="Rami" last="Al-Ouran">Rami Al-Ouran</name>
<name sortKey="Bitterman, Thomas" sort="Bitterman, Thomas" uniqKey="Bitterman T" first="Thomas" last="Bitterman">Thomas Bitterman</name>
<name sortKey="Drews, Frank" sort="Drews, Frank" uniqKey="Drews F" first="Frank" last="Drews">Frank Drews</name>
<name sortKey="Ecker, Klaus" sort="Ecker, Klaus" uniqKey="Ecker K" first="Klaus" last="Ecker">Klaus Ecker</name>
<name sortKey="Elnitski, Laura" sort="Elnitski, Laura" uniqKey="Elnitski L" first="Laura" last="Elnitski">Laura Elnitski</name>
<name sortKey="Kurz, Kyle" sort="Kurz, Kyle" uniqKey="Kurz K" first="Kyle" last="Kurz">Kyle Kurz</name>
<name sortKey="Lee, Stephen Sauchi" sort="Lee, Stephen Sauchi" uniqKey="Lee S" first="Stephen Sauchi" last="Lee">Stephen Sauchi Lee</name>
<name sortKey="Liang, Xiaoyu" sort="Liang, Xiaoyu" uniqKey="Liang X" first="Xiaoyu" last="Liang">Xiaoyu Liang</name>
<name sortKey="Nau, Lee J" sort="Nau, Lee J" uniqKey="Nau L" first="Lee J" last="Nau">Lee J. Nau</name>
<name sortKey="Neiman, Lev" sort="Neiman, Lev" uniqKey="Neiman L" first="Lev" last="Neiman">Lev Neiman</name>
<name sortKey="Welch, Joshua D" sort="Welch, Joshua D" uniqKey="Welch J" first="Joshua D" last="Welch">Joshua D. Welch</name>
<name sortKey="Welch, Lonnie R" sort="Welch, Lonnie R" uniqKey="Welch L" first="Lonnie R" last="Welch">Lonnie R. Welch</name>
<name sortKey="Welch, Lonnie R" sort="Welch, Lonnie R" uniqKey="Welch L" first="Lonnie R" last="Welch">Lonnie R. Welch</name>
<name sortKey="Welch, Lonnie R" sort="Welch, Lonnie R" uniqKey="Welch L" first="Lonnie R" last="Welch">Lonnie R. Welch</name>
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<country name="France">
<region name="Provence-Alpes-Côte d'Azur">
<name sortKey="Jacox, Edwin" sort="Jacox, Edwin" uniqKey="Jacox E" first="Edwin" last="Jacox">Edwin Jacox</name>
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</country>
</tree>
</affiliations>
</record>

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