SRIdent: A novel pipeline for real-time identification of species from high-throughput sequencing reads in Metagenomics and clinical diagnostic assays.
Identifieur interne : 001583 ( Main/Exploration ); précédent : 001582; suivant : 001584SRIdent: A novel pipeline for real-time identification of species from high-throughput sequencing reads in Metagenomics and clinical diagnostic assays.
Auteurs : Ramin Karimi ; Andras HajduSource :
- Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference [ 1557-170X ] ; 2015.
Descripteurs français
- KwdFr :
- ADN (analyse), Algorithmes, Alignement de séquences, Analyse de séquence d'ADN, Bases de données génétiques, Biologie informatique (), Données de séquences moléculaires, Génome bactérien, Logiciel, Métagénomique, Réaction de polymérisation en chaîne, Simulation numérique, Spécificité d'espèce, Séquence nucléotidique, Séquençage nucléotidique à haut débit ().
- MESH :
- analyse : ADN.
- Algorithmes, Alignement de séquences, Analyse de séquence d'ADN, Bases de données génétiques, Biologie informatique, Données de séquences moléculaires, Génome bactérien, Logiciel, Métagénomique, Réaction de polymérisation en chaîne, Simulation numérique, Spécificité d'espèce, Séquence nucléotidique, Séquençage nucléotidique à haut débit.
English descriptors
- KwdEn :
- Algorithms, Base Sequence, Computational Biology (methods), Computer Simulation, DNA (analysis), Databases, Genetic, Genome, Bacterial, High-Throughput Nucleotide Sequencing (methods), Metagenomics, Molecular Sequence Data, Polymerase Chain Reaction, Sequence Alignment, Sequence Analysis, DNA, Software, Species Specificity.
- MESH :
- chemical , analysis : DNA.
- methods : Computational Biology, High-Throughput Nucleotide Sequencing.
- Algorithms, Base Sequence, Computer Simulation, Databases, Genetic, Genome, Bacterial, Metagenomics, Molecular Sequence Data, Polymerase Chain Reaction, Sequence Alignment, Sequence Analysis, DNA, Software, Species Specificity.
Abstract
New advances in rapid sequencing of large amounts of DNA have brought a great potential for the study of complex communities of microorganisms. One of the challenging problems is rapid identification of species from sequenced reads. Delays in the identification of pathogens are a barrier to the early diagnosis and proper treatment of infectious diseases. In this paper we proposed SRIdent (Short Read Identifier), an effective pipeline for real-time identification of species from high-throughput sequencing reads in Metagenomics and clinical diagnostic assays. This pipeline is based on generating k-mers from the short reads and searching the existence of DNA signatures in the Reads k-mers, by using Apache Hive data-warehousing. RkmerG (Read k-mers Generator) is a software program presented in this paper, for producing k-mers of the short reads, in order to use in the pipeline. The purpose of this study is to identify the species in a sample, directly from the reads without assembling and alignment.
DOI: 10.1109/EMBC.2015.7319877
PubMed: 26737777
Affiliations:
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Le document en format XML
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Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference</title><idno type="ISSN">1557-170X</idno><imprint><date when="2015" type="published">2015</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithms</term><term>Base Sequence</term><term>Computational Biology (methods)</term><term>Computer Simulation</term><term>DNA (analysis)</term><term>Databases, Genetic</term><term>Genome, Bacterial</term><term>High-Throughput Nucleotide Sequencing (methods)</term><term>Metagenomics</term><term>Molecular Sequence Data</term><term>Polymerase Chain Reaction</term><term>Sequence Alignment</term><term>Sequence Analysis, DNA</term><term>Software</term><term>Species Specificity</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>ADN (analyse)</term><term>Algorithmes</term><term>Alignement de séquences</term><term>Analyse de séquence d'ADN</term><term>Bases de données génétiques</term><term>Biologie informatique ()</term><term>Données de séquences moléculaires</term><term>Génome bactérien</term><term>Logiciel</term><term>Métagénomique</term><term>Réaction de polymérisation en chaîne</term><term>Simulation numérique</term><term>Spécificité d'espèce</term><term>Séquence nucléotidique</term><term>Séquençage nucléotidique à haut débit ()</term></keywords><keywords scheme="MESH" type="chemical" qualifier="analysis" xml:lang="en"><term>DNA</term></keywords><keywords scheme="MESH" qualifier="analyse" xml:lang="fr"><term>ADN</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Computational Biology</term><term>High-Throughput Nucleotide Sequencing</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Algorithms</term><term>Base Sequence</term><term>Computer Simulation</term><term>Databases, Genetic</term><term>Genome, Bacterial</term><term>Metagenomics</term><term>Molecular Sequence Data</term><term>Polymerase Chain Reaction</term><term>Sequence Alignment</term><term>Sequence Analysis, DNA</term><term>Software</term><term>Species Specificity</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Algorithmes</term><term>Alignement de séquences</term><term>Analyse de séquence d'ADN</term><term>Bases de données génétiques</term><term>Biologie informatique</term><term>Données de séquences moléculaires</term><term>Génome bactérien</term><term>Logiciel</term><term>Métagénomique</term><term>Réaction de polymérisation en chaîne</term><term>Simulation numérique</term><term>Spécificité d'espèce</term><term>Séquence nucléotidique</term><term>Séquençage nucléotidique à haut débit</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">New advances in rapid sequencing of large amounts of DNA have brought a great potential for the study of complex communities of microorganisms. One of the challenging problems is rapid identification of species from sequenced reads. Delays in the identification of pathogens are a barrier to the early diagnosis and proper treatment of infectious diseases. In this paper we proposed SRIdent (Short Read Identifier), an effective pipeline for real-time identification of species from high-throughput sequencing reads in Metagenomics and clinical diagnostic assays. This pipeline is based on generating k-mers from the short reads and searching the existence of DNA signatures in the Reads k-mers, by using Apache Hive data-warehousing. RkmerG (Read k-mers Generator) is a software program presented in this paper, for producing k-mers of the short reads, in order to use in the pipeline. The purpose of this study is to identify the species in a sample, directly from the reads without assembling and alignment. </div></front></TEI><affiliations><list></list><tree><noCountry><name sortKey="Hajdu, Andras" sort="Hajdu, Andras" uniqKey="Hajdu A" first="Andras" last="Hajdu">Andras Hajdu</name><name sortKey="Karimi, Ramin" sort="Karimi, Ramin" uniqKey="Karimi R" first="Ramin" last="Karimi">Ramin Karimi</name></noCountry></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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