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DiNAMO:高通量测序数据中高度敏感的 DNA 基序发现。

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

机构信息

Univ. Lille, CNRS, Inria, UMR 9189 - CRIStAL - Centre de Recherche en Informatique Signal et Automatique de Lille, Lille, France.

Univ. Lille, Inserm, Lille University Hospital, UMR-S 1172 - JPARC - Centre de Recherche Jean-Pierre AUBERT, Lille, F-59000, France.

出版信息

BMC Bioinformatics. 2018 Jun 11;19(1):223. doi: 10.1186/s12859-018-2215-1.

Abstract

BACKGROUND

Discovering over-represented approximate motifs in DNA sequences is an essential part of bioinformatics. 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 throughput sequencing technologies. To overcome this problem, existing tools use greedy algorithms and probabilistic approaches to find motifs in reasonable time. Nevertheless these approaches lack sensitivity and have difficulties coping with rare and subtle motifs.

RESULTS

We developed DiNAMO (for DNA MOtif), a new software based on an exhaustive and efficient algorithm for IUPAC motif discovery. We evaluated DiNAMO on synthetic and real datasets with two different applications, namely ChIP-seq peaks and Systematic Sequencing Error analysis. DiNAMO proves to compare favorably with other existing methods and is robust to noise.

CONCLUSIONS

We shown that DiNAMO software can serve as a tool to search for degenerate motifs in an exact manner 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.

AVAILABILITY

https://github.com/bonsai-team/DiNAMO .

摘要

背景

在 DNA 序列中发现过度表示的近似基序是生物信息学的重要组成部分。由于潜在应用的数量不断增加,这个主题已经得到了广泛的研究。然而,这仍然是一个具有挑战性的问题,特别是对于高通量测序技术产生的大量数据。为了解决这个问题,现有的工具使用贪婪算法和概率方法在合理的时间内找到基序。然而,这些方法缺乏敏感性,并且难以应对罕见和微妙的基序。

结果

我们开发了 DiNAMO(用于 DNA 基序),这是一种基于 IUPAC 基序发现的穷举和高效算法的新软件。我们使用两种不同的应用程序(即 ChIP-seq 峰和系统测序错误分析)在合成和真实数据集上评估了 DiNAMO。DiNAMO 被证明与其他现有方法相比具有优势,并且对噪声具有鲁棒性。

结论

我们表明,DiNAMO 软件可以用作使用 IUPAC 模型以精确方式搜索简并基序的工具。DiNAMO 可以在滑动窗口的扫描模式或固定位置模式下使用,这使其适用于许多潜在的应用。

可用性

https://github.com/bonsai-team/DiNAMO。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6565/5996464/c3aa52262b92/12859_2018_2215_Fig1_HTML.jpg

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