Large scale explorative oligonucleotide probe selection for thousands of genetic groups on a computing grid: application to phylogenetic probe design using a curated small subunit ribosomal RNA gene database.
Phylogenetic Oligonucleotide Arrays (POAs) were recently adapted for studying the huge microbial communities in a flexible and easy-to-use way. POA coupled with the use of explorative probes to detect the unknown part is now one of the most powerful approaches for a better understanding of microbial...
| Publicado en: | Scientific World Journal pp. 350487 - 350488 |
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| Autores principales: | , , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Wiley-Blackwell
2014
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=103810839&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 103810839 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 1537744X 1BX5 jtl: Scientific World Journal issn: 1537744X maglogo: N pubinfo: dt: 2014 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 103810839 103810839 NLM24516366 2012471345 10.1155/2014/350487 NLM24516366 PMC3913353 103810839 ppf: 350487 ppct: 1 formats: tig: atl: Large scale explorative oligonucleotide probe selection for thousands of genetic groups on a computing grid: application to phylogenetic probe design using a curated small subunit ribosomal RNA gene database. aug: au: Jaziri, Faouzi Peyretaillade, Eric Missaoui, Mohieddine Parisot, Nicolas Cipière, Sébastien Denonfoux, Jérémie Mahul, Antoine Peyret, Pierre Hill, David R C affil: UMR CNRS 6158, ISIMA/LIMOS, Clermont Université et Université Blaise Pascal, F63173 Aubière, France ; Clermont Université et Université d'Auvergne, EA 4678 CIDAM, BP 10448, F63001 Clermont-Ferrand Cedex 1, France. sug: subj: Oligonucleotide Array Sequence Analysis Methods Nucleic Acid Probes Software Algorithms Bioinformatics Methods Resource Databases Genes Evolution ab: Phylogenetic Oligonucleotide Arrays (POAs) were recently adapted for studying the huge microbial communities in a flexible and easy-to-use way. POA coupled with the use of explorative probes to detect the unknown part is now one of the most powerful approaches for a better understanding of microbial community functioning. However, the selection of probes remains a very difficult task. The rapid growth of environmental databases has led to an exponential increase of data to be managed for an efficient design. Consequently, the use of high performance computing facilities is mandatory. In this paper, we present an efficient parallelization method to select known and explorative oligonucleotide probes at large scale using computing grids. We implemented a software that generates and monitors thousands of jobs over the European Computing Grid Infrastructure (EGI). We also developed a new algorithm for the construction of a high-quality curated phylogenetic database to avoid erroneous design due to bad sequence affiliation. We present here the performance and statistics of our method on real biological datasets based on a phylogenetic prokaryotic database at the genus level and a complete design of about 20,000 probes for 2,069 genera of prokaryotes. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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