A highly efficient and effective motif discovery method for ChIP-seq/ChIP-chip data using positional information
Identifieur interne : 002485 ( Main/Exploration ); précédent : 002484; suivant : 002486A highly efficient and effective motif discovery method for ChIP-seq/ChIP-chip data using positional information
Auteurs : Xiaotu Ma ; Ashwinikumar Kulkarni ; Zhihua Zhang ; Zhenyu Xuan ; Robert Serfling [États-Unis] ; Michael Q. Zhang [République populaire de Chine]Source :
- Nucleic Acids Research [ 0305-1048 ] ; 2011.
Descripteurs français
- KwdFr :
- Algorithmes, Analyse de regroupements, Analyse de séquence d'ADN, Animaux, Cellules souches embryonnaires (métabolisme), Drosophila melanogaster (génétique), Facteurs de transcription (métabolisme), Immunoprécipitation de la chromatine, Logiciel, Motifs nucléotidiques, Protéines de répression, Réseaux de régulation génique, Simulation numérique, Sites de fixation, Souris, Séquençage nucléotidique à haut débit, Séquençage par oligonucléotides en batterie, Éléments de régulation transcriptionnelle.
- MESH :
- génétique : Drosophila melanogaster.
- métabolisme : Cellules souches embryonnaires, Facteurs de transcription.
- Algorithmes, Analyse de regroupements, Analyse de séquence d'ADN, Animaux, Immunoprécipitation de la chromatine, Logiciel, Motifs nucléotidiques, Protéines de répression, Réseaux de régulation génique, Simulation numérique, Sites de fixation, Souris, Séquençage nucléotidique à haut débit, Séquençage par oligonucléotides en batterie, Éléments de régulation transcriptionnelle.
English descriptors
- KwdEn :
- Algorithms, Animals, Binding Sites, CCCTC-Binding Factor, Chromatin Immunoprecipitation, Cluster Analysis, Computer Simulation, Drosophila melanogaster (genetics), Embryonic Stem Cells (metabolism), Gene Regulatory Networks, High-Throughput Nucleotide Sequencing, Mice, Nucleotide Motifs, Oligonucleotide Array Sequence Analysis, Regulatory Elements, Transcriptional, Repressor Proteins, Sequence Analysis, DNA, Software, Transcription Factors (metabolism).
- MESH :
- chemical , metabolism : Transcription Factors.
- chemical : CCCTC-Binding Factor, Repressor Proteins.
- genetics : Drosophila melanogaster.
- metabolism : Embryonic Stem Cells.
- Algorithms, Animals, Binding Sites, Chromatin Immunoprecipitation, Cluster Analysis, Computer Simulation, Gene Regulatory Networks, High-Throughput Nucleotide Sequencing, Mice, Nucleotide Motifs, Oligonucleotide Array Sequence Analysis, Regulatory Elements, Transcriptional, Sequence Analysis, DNA, Software.
Abstract
Identification of DNA motifs from ChIP-seq/ChIP-chip [chromatin immunoprecipitation (ChIP)] data is a powerful method for understanding the transcriptional regulatory network. However, most established methods are designed for small sample sizes and are inefficient for ChIP data. Here we propose a new
Url:
DOI: 10.1093/nar/gkr1135
PubMed: 22228832
PubMed Central: 3326300
Affiliations:
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Le document en format XML
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Campbell Road, Richardson, TX 75080, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Mathematics, University of Texas at Dallas, 800 W. Campbell Road, Richardson, TX 75080</wicri:regionArea><placeName><region type="state">Texas</region></placeName></affiliation></author><author><name sortKey="Zhang, Michael Q" sort="Zhang, Michael Q" uniqKey="Zhang M" first="Michael Q." last="Zhang">Michael Q. Zhang</name><affiliation><nlm:aff id="gkr1135-AFF1">Department of Molecular and Cell Biology, Center for Systems Biology,</nlm:aff><wicri:noCountry code="subfield">Center for Systems Biology</wicri:noCountry></affiliation><affiliation wicri:level="1"><nlm:aff id="gkr1135-AFF1">Division of Bioinformatics, Center for Synthetic and Systems Biology, TNLIST, Tsinghua University, Beijing 100084, China</nlm:aff><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Division of Bioinformatics, Center for Synthetic and Systems Biology, TNLIST, Tsinghua University, Beijing 100084</wicri:regionArea><placeName><settlement type="city">Pékin</settlement></placeName></affiliation></author></analytic><series><title level="j">Nucleic Acids Research</title><idno type="ISSN">0305-1048</idno><idno type="eISSN">1362-4962</idno><imprint><date when="2011">2011</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithms</term><term>Animals</term><term>Binding Sites</term><term>CCCTC-Binding Factor</term><term>Chromatin Immunoprecipitation</term><term>Cluster Analysis</term><term>Computer Simulation</term><term>Drosophila melanogaster (genetics)</term><term>Embryonic Stem Cells (metabolism)</term><term>Gene Regulatory Networks</term><term>High-Throughput Nucleotide Sequencing</term><term>Mice</term><term>Nucleotide Motifs</term><term>Oligonucleotide Array Sequence Analysis</term><term>Regulatory Elements, Transcriptional</term><term>Repressor Proteins</term><term>Sequence Analysis, DNA</term><term>Software</term><term>Transcription Factors (metabolism)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Algorithmes</term><term>Analyse de regroupements</term><term>Analyse de séquence d'ADN</term><term>Animaux</term><term>Cellules souches embryonnaires (métabolisme)</term><term>Drosophila melanogaster (génétique)</term><term>Facteurs de transcription (métabolisme)</term><term>Immunoprécipitation de la chromatine</term><term>Logiciel</term><term>Motifs nucléotidiques</term><term>Protéines de répression</term><term>Réseaux de régulation génique</term><term>Simulation numérique</term><term>Sites de fixation</term><term>Souris</term><term>Séquençage nucléotidique à haut débit</term><term>Séquençage par oligonucléotides en batterie</term><term>Éléments de régulation transcriptionnelle</term></keywords><keywords scheme="MESH" type="chemical" qualifier="metabolism" xml:lang="en"><term>Transcription Factors</term></keywords><keywords scheme="MESH" type="chemical" xml:lang="en"><term>CCCTC-Binding Factor</term><term>Repressor Proteins</term></keywords><keywords scheme="MESH" qualifier="genetics" xml:lang="en"><term>Drosophila melanogaster</term></keywords><keywords scheme="MESH" qualifier="génétique" xml:lang="fr"><term>Drosophila melanogaster</term></keywords><keywords scheme="MESH" qualifier="metabolism" xml:lang="en"><term>Embryonic Stem Cells</term></keywords><keywords scheme="MESH" qualifier="métabolisme" xml:lang="fr"><term>Cellules souches embryonnaires</term><term>Facteurs de transcription</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Algorithms</term><term>Animals</term><term>Binding Sites</term><term>Chromatin Immunoprecipitation</term><term>Cluster Analysis</term><term>Computer Simulation</term><term>Gene Regulatory Networks</term><term>High-Throughput Nucleotide Sequencing</term><term>Mice</term><term>Nucleotide Motifs</term><term>Oligonucleotide Array Sequence Analysis</term><term>Regulatory Elements, Transcriptional</term><term>Sequence Analysis, DNA</term><term>Software</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Algorithmes</term><term>Analyse de regroupements</term><term>Analyse de séquence d'ADN</term><term>Animaux</term><term>Immunoprécipitation de la chromatine</term><term>Logiciel</term><term>Motifs nucléotidiques</term><term>Protéines de répression</term><term>Réseaux de régulation génique</term><term>Simulation numérique</term><term>Sites de fixation</term><term>Souris</term><term>Séquençage nucléotidique à haut débit</term><term>Séquençage par oligonucléotides en batterie</term><term>Éléments de régulation transcriptionnelle</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Identification of DNA motifs from ChIP-seq/ChIP-chip [chromatin immunoprecipitation (ChIP)] data is a powerful method for understanding the transcriptional regulatory network. However, most established methods are designed for small sample sizes and are inefficient for ChIP data. Here we propose a new <italic>k-</italic>mer occurrence model to reflect the fact that functional DNA <italic>k</italic>-mers often cluster around ChIP peak summits. With this model, we introduced a new measure to discover functional <italic>k-</italic>mers. Using simulation, we demonstrated that our method is more robust against noises in ChIP data than available methods. A novel word clustering method is also implemented to group similar <italic>k</italic>-mers into position weight matrices (PWMs). Our method was applied to a diverse set of ChIP experiments to demonstrate its high sensitivity and specificity. Importantly, our method is much faster than several other methods for large sample sizes. Thus, we have developed an efficient and effective motif discovery method for ChIP experiments.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Tompa, M" uniqKey="Tompa M">M Tompa</name></author><author><name sortKey="Li, N" uniqKey="Li N">N Li</name></author><author><name sortKey="Bailey, Tl" uniqKey="Bailey T">TL Bailey</name></author><author><name sortKey="Church, Gm" uniqKey="Church G">GM Church</name></author><author><name sortKey="De Moor, B" uniqKey="De Moor B">B De Moor</name></author><author><name sortKey="Eskin, E" uniqKey="Eskin E">E Eskin</name></author><author><name sortKey="Favorov, Av" uniqKey="Favorov A">AV Favorov</name></author><author><name sortKey="Frith, Mc" uniqKey="Frith M">MC Frith</name></author><author><name sortKey="Fu, Y" uniqKey="Fu Y">Y Fu</name></author><author><name sortKey="Kent, Wj" uniqKey="Kent W">WJ Kent</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Stormo, 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Bailey</name></author></analytic></biblStruct></listBibl></div1></back></TEI><affiliations><list><country><li>République populaire de Chine</li><li>États-Unis</li></country><region><li>Texas</li></region><settlement><li>Pékin</li></settlement></list><tree><noCountry><name sortKey="Kulkarni, Ashwinikumar" sort="Kulkarni, Ashwinikumar" uniqKey="Kulkarni A" first="Ashwinikumar" last="Kulkarni">Ashwinikumar Kulkarni</name><name sortKey="Ma, Xiaotu" sort="Ma, Xiaotu" uniqKey="Ma X" first="Xiaotu" last="Ma">Xiaotu Ma</name><name sortKey="Xuan, Zhenyu" sort="Xuan, Zhenyu" uniqKey="Xuan Z" first="Zhenyu" last="Xuan">Zhenyu Xuan</name><name sortKey="Zhang, Zhihua" sort="Zhang, Zhihua" uniqKey="Zhang Z" first="Zhihua" last="Zhang">Zhihua Zhang</name></noCountry><country name="États-Unis"><region name="Texas"><name sortKey="Serfling, Robert" sort="Serfling, Robert" uniqKey="Serfling R" first="Robert" last="Serfling">Robert Serfling</name></region></country><country name="République populaire de 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