DiNAMO: highly sensitive DNA motif discovery ...
Document type :
Article dans une revue scientifique: Article original
Title :
DiNAMO: highly sensitive DNA motif discovery in high-throughput sequencing data
Author(s) :
Saad, Chadi [Auteur]
Bioinformatics and Sequence Analysis [BONSAI]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Centre de Recherche Jean-Pierre AUBERT Neurosciences et Cancer - U837 [JPArc]
Noé, Laurent [Auteur]
Bioinformatics and Sequence Analysis [BONSAI]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Richard, Hugues [Auteur]
Biologie Computationnelle et Quantitative = Laboratory of Computational and Quantitative Biology [LCQB]
Leclerc, Julie [Auteur]
Pôle de Biologie Pathologie Génétique [CHU Lille]
Hétérogénéité, Plasticité et Résistance aux Thérapies des Cancers = Cancer Heterogeneity, Plasticity and Resistance to Therapies - UMR 9020 - U 1277 [CANTHER]
Centre de Recherche Jean-Pierre AUBERT Neurosciences et Cancer - U837 [JPArc]
Buisine, Marie-Pierre [Auteur]
Centre de Recherche Jean-Pierre AUBERT Neurosciences et Cancer - U837 [JPArc]
Touzet, Helene [Auteur]
Bioinformatics and Sequence Analysis [BONSAI]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Figeac, Martin [Auteur]
Plateforme de génomique fonctionnelle et structurelle [Lille]
Bioinformatics and Sequence Analysis [BONSAI]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Centre de Recherche Jean-Pierre AUBERT Neurosciences et Cancer - U837 [JPArc]
Noé, Laurent [Auteur]

Bioinformatics and Sequence Analysis [BONSAI]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Richard, Hugues [Auteur]
Biologie Computationnelle et Quantitative = Laboratory of Computational and Quantitative Biology [LCQB]
Leclerc, Julie [Auteur]

Pôle de Biologie Pathologie Génétique [CHU Lille]
Hétérogénéité, Plasticité et Résistance aux Thérapies des Cancers = Cancer Heterogeneity, Plasticity and Resistance to Therapies - UMR 9020 - U 1277 [CANTHER]
Centre de Recherche Jean-Pierre AUBERT Neurosciences et Cancer - U837 [JPArc]
Buisine, Marie-Pierre [Auteur]
Centre de Recherche Jean-Pierre AUBERT Neurosciences et Cancer - U837 [JPArc]
Touzet, Helene [Auteur]

Bioinformatics and Sequence Analysis [BONSAI]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Figeac, Martin [Auteur]

Plateforme de génomique fonctionnelle et structurelle [Lille]
Journal title :
BMC Bioinformatics
Publisher :
BioMed Central
Publication date :
2018-12
ISSN :
1471-2105
English keyword(s) :
DNA
Chip-Seq
Motif
Chip-Seq
Motif
HAL domain(s) :
Informatique [cs]/Bio-informatique [q-bio.QM]
English abstract : [en]
Background:Discovering over-represented approximate motifs in DNA sequences is an essential part ofbioinformatics. This topic has been studied extensively because of the increasing number of potential applications.However, ...
Show more >Background:Discovering over-represented approximate motifs in DNA sequences is an essential part ofbioinformatics. This topic has been studied extensively because of the increasing number of potential applications.However, it remains a difficult challenge, especially with the huge quantity of data generated by high throughputsequencing technologies. To overcome this problem, existing tools use greedy algorithms and probabilisticapproaches to find motifs in reasonable time. Nevertheless these approaches lack sensitivity and have difficultiescoping with rare and subtle motifs.Results:We developed DiNAMO (for DNA MOtif), a new software based on an exhaustive and efficient algorithm forIUPAC motif discovery. We evaluated DiNAMO on synthetic and real datasets with two different applications, namelyChIP-seq peaks and Systematic Sequencing Error analysis. DiNAMO proves to compare favorably with other existingmethods and is robust to noise.Conclusions:We shown that DiNAMO software can serve as a tool to search for degenerate motifs in an exactmanner using IUPAC models. DiNAMO can be used in scanning mode with sliding windows or in fixed position mode,which makes it suitable for numerous potential applications.Show less >
Show more >Background:Discovering over-represented approximate motifs in DNA sequences is an essential part ofbioinformatics. This topic has been studied extensively because of the increasing number of potential applications.However, it remains a difficult challenge, especially with the huge quantity of data generated by high throughputsequencing technologies. To overcome this problem, existing tools use greedy algorithms and probabilisticapproaches to find motifs in reasonable time. Nevertheless these approaches lack sensitivity and have difficultiescoping with rare and subtle motifs.Results:We developed DiNAMO (for DNA MOtif), a new software based on an exhaustive and efficient algorithm forIUPAC motif discovery. We evaluated DiNAMO on synthetic and real datasets with two different applications, namelyChIP-seq peaks and Systematic Sequencing Error analysis. DiNAMO proves to compare favorably with other existingmethods and is robust to noise.Conclusions:We shown that DiNAMO software can serve as a tool to search for degenerate motifs in an exactmanner using IUPAC models. DiNAMO can be used in scanning mode with sliding windows or in fixed position mode,which makes it suitable for numerous potential applications.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
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