A highly efficient and effective motif discovery method for ChIP-seq/ChIP-chip data using positional information.
Identifieur interne : 001D11 ( PubMed/Checkpoint ); précédent : 001D10; suivant : 001D12A highly efficient and effective motif discovery method for ChIP-seq/ChIP-chip data using positional information.
Auteurs : Xiaotu Ma [États-Unis] ; Ashwinikumar Kulkarni ; Zhihua Zhang ; Zhenyu Xuan ; Robert Serfling ; Michael Q. ZhangSource :
- Nucleic acids research [ 1362-4962 ] ; 2012.
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 k-mer occurrence model to reflect the fact that functional DNA k-mers often cluster around ChIP peak summits. With this model, we introduced a new measure to discover functional k-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 k-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.
DOI: 10.1093/nar/gkr1135
PubMed: 22228832
Affiliations:
Links toward previous steps (curation, corpus...)
Links to Exploration step
pubmed:22228832Le document en format XML
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<front><div type="abstract" xml:lang="en">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 k-mer occurrence model to reflect the fact that functional DNA k-mers often cluster around ChIP peak summits. With this model, we introduced a new measure to discover functional k-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 k-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.</div>
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<ReferenceList><Reference><Citation>Science. 2010 Dec 24;330(6012):1787-97</Citation>
<ArticleIdList><ArticleId IdType="pubmed">21177974</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Genome Res. 2010 Nov;20(11):1512-25</Citation>
<ArticleIdList><ArticleId IdType="pubmed">20693478</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>PLoS Comput Biol. 2011;7(2):e1001070</Citation>
<ArticleIdList><ArticleId IdType="pubmed">21347314</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>J Biol Chem. 2011 Apr 8;286(14):11985-96</Citation>
<ArticleIdList><ArticleId IdType="pubmed">21310950</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Bioinformatics. 2011 Jun 15;27(12):1653-9</Citation>
<ArticleIdList><ArticleId IdType="pubmed">21543442</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nucleic Acids Res. 2011 Aug;39(15):e98</Citation>
<ArticleIdList><ArticleId IdType="pubmed">21602262</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>J Comput Biol. 2000;7(3-4):345-62</Citation>
<ArticleIdList><ArticleId IdType="pubmed">11108467</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>J Comput Biol. 2002;9(2):225-42</Citation>
<ArticleIdList><ArticleId IdType="pubmed">12015879</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nat Biotechnol. 2002 Aug;20(8):835-9</Citation>
<ArticleIdList><ArticleId IdType="pubmed">12101404</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Bioinformatics. 2002;18 Suppl 1:S354-63</Citation>
<ArticleIdList><ArticleId IdType="pubmed">12169566</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nucleic Acids Res. 2003 Jul 1;31(13):3586-8</Citation>
<ArticleIdList><ArticleId IdType="pubmed">12824371</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nucleic Acids Res. 2004 Jul 1;32(Web Server issue):W199-203</Citation>
<ArticleIdList><ArticleId IdType="pubmed">15215380</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Science. 1993 Oct 8;262(5131):208-14</Citation>
<ArticleIdList><ArticleId IdType="pubmed">8211139</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Proc Int Conf Intell Syst Mol Biol. 1994;2:28-36</Citation>
<ArticleIdList><ArticleId IdType="pubmed">7584402</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nat Biotechnol. 1998 Oct;16(10):939-45</Citation>
<ArticleIdList><ArticleId IdType="pubmed">9788350</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Bioinformatics. 2005 Jan 1;21(1):31-8</Citation>
<ArticleIdList><ArticleId IdType="pubmed">15333453</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nat Biotechnol. 2005 Jan;23(1):137-44</Citation>
<ArticleIdList><ArticleId IdType="pubmed">15637633</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Bioinformatics. 2005 Feb 1;21(3):307-13</Citation>
<ArticleIdList><ArticleId IdType="pubmed">15319260</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Proc Natl Acad Sci U S A. 2005 Feb 1;102(5):1560-5</Citation>
<ArticleIdList><ArticleId IdType="pubmed">15668401</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>BMC Bioinformatics. 2005;6:173</Citation>
<ArticleIdList><ArticleId IdType="pubmed">16011807</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Bioinformatics. 2006 Jul 15;22(14):e150-7</Citation>
<ArticleIdList><ArticleId IdType="pubmed">16873465</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nat Biotechnol. 2006 Nov;24(11):1429-35</Citation>
<ArticleIdList><ArticleId IdType="pubmed">16998473</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Cell. 2007 Mar 23;128(6):1231-45</Citation>
<ArticleIdList><ArticleId IdType="pubmed">17382889</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Cell. 2007 May 18;129(4):823-37</Citation>
<ArticleIdList><ArticleId IdType="pubmed">17512414</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>PLoS Comput Biol. 2007 Mar 30;3(3):e61</Citation>
<ArticleIdList><ArticleId IdType="pubmed">17397256</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Science. 2007 Jun 8;316(5830):1497-502</Citation>
<ArticleIdList><ArticleId IdType="pubmed">17540862</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nucleic Acids Res. 2007;35(10):3203-13</Citation>
<ArticleIdList><ArticleId IdType="pubmed">17452354</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nat Methods. 2007 Jul;4(7):563-5</Citation>
<ArticleIdList><ArticleId IdType="pubmed">17589518</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nat Methods. 2007 Aug;4(8):651-7</Citation>
<ArticleIdList><ArticleId IdType="pubmed">17558387</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Cell. 2008 Jun 13;133(6):1106-17</Citation>
<ArticleIdList><ArticleId IdType="pubmed">18555785</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>BMC Bioinformatics. 2008;9:262</Citation>
<ArticleIdList><ArticleId IdType="pubmed">18533028</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Genome Res. 2008 Jul;18(7):1180-9</Citation>
<ArticleIdList><ArticleId IdType="pubmed">18411406</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nucleic Acids Res. 2008 Aug;36(14):4549-64</Citation>
<ArticleIdList><ArticleId IdType="pubmed">18611952</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nucleic Acids Res. 2008 Sep;36(16):5221-31</Citation>
<ArticleIdList><ArticleId IdType="pubmed">18684996</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nat Biotechnol. 2008 Nov;26(11):1293-300</Citation>
<ArticleIdList><ArticleId IdType="pubmed">18978777</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nature. 2008 Nov 20;456(7220):400-3</Citation>
<ArticleIdList><ArticleId IdType="pubmed">18931655</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Genome Biol. 2008;9(9):R137</Citation>
<ArticleIdList><ArticleId IdType="pubmed">18798982</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nat Methods. 2008 Sep;5(9):829-34</Citation>
<ArticleIdList><ArticleId IdType="pubmed">19160518</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nat Rev Genet. 2009 Apr;10(4):252-63</Citation>
<ArticleIdList><ArticleId IdType="pubmed">19274049</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nucleic Acids Res. 2009 Sep;37(17):e113</Citation>
<ArticleIdList><ArticleId IdType="pubmed">19553195</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nucleic Acids Res. 2010 Jan;38(Database issue):D105-10</Citation>
<ArticleIdList><ArticleId IdType="pubmed">19906716</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>PLoS Biol. 2010 Mar;8(3):e1000343</Citation>
<ArticleIdList><ArticleId IdType="pubmed">20351773</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nucleic Acids Res. 2010 Apr;38(7):2154-67</Citation>
<ArticleIdList><ArticleId IdType="pubmed">20056654</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Bioinformatics. 2010 May 1;26(9):1152-9</Citation>
<ArticleIdList><ArticleId IdType="pubmed">20223835</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>EMBO J. 2010 Jul 7;29(13):2147-60</Citation>
<ArticleIdList><ArticleId IdType="pubmed">20517297</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>PLoS One. 2010;5(7):e11425</Citation>
<ArticleIdList><ArticleId IdType="pubmed">20625510</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>PLoS One. 2010;5(7):e11471</Citation>
<ArticleIdList><ArticleId IdType="pubmed">20628599</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Bioinformatics. 2010 Oct 15;26(20):2622-3</Citation>
<ArticleIdList><ArticleId IdType="pubmed">20736340</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nat Rev Genet. 2010 Nov;11(11):751-60</Citation>
<ArticleIdList><ArticleId IdType="pubmed">20877328</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Science. 2010 Dec 24;330(6012):1775-87</Citation>
<ArticleIdList><ArticleId IdType="pubmed">21177976</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
</PubmedData>
</pubmed>
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