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Journal Articles BMC Bioinformatics Year : 2018

DiNAMO: highly sensitive DNA motif discovery in high-throughput sequencing data

Abstract

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.

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Dates and versions

hal-01881466 , version 1 (24-01-2024)

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Chadi Saad, Laurent Noé, Hugues Richard, Julie Leclerc, Marie-Pierre Buisine, et al.. DiNAMO: highly sensitive DNA motif discovery in high-throughput sequencing data. BMC Bioinformatics, 2018, 19 (1), ⟨10.1186/s12859-018-2215-1⟩. ⟨hal-01881466⟩
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