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ASSA: Fast identification of statistically significant interactions between long RNAs

机译：ASSA：快速识别长RNA之间的统计上显着的相互作用

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摘要

The discovery of thousands of long noncoding RNAs (lncRNAs) in mammals raises a question about their functionality. It has been shown that some of them are involved in post-transcriptional regulation of other RNAs and form inter-molecular duplexes with their targets. Sequence alignment tools have been used for transcriptome-wide prediction of RNA RNA interactions. However, such approaches have poor prediction accuracy since they ignore RNA's secondary structure. Application of the thermodynamics-based algorithms to long transcripts is not computationally feasible on a large scale. Here, we describe a new computational pipeline ASSA that combines sequence alignment and thermodynamics-based tools for efficient prediction of RNA RNA interactions between long transcripts. To measure the hybridization strength, the sum energy of all the putative duplexes is computed. The main novelty implemented in ASSA is the ability to quickly estimate the statistical significance of the observed interaction energies. Most of the functional hybridizations between long RNAs were classified as statistically significant. ASSA outperformed 11 other tools in terms of the Area Under the Curve on two out of four test sets. Additionally, our results emphasized a unique property of the Alu repeats with respect to the RNA RNA interactions in the human transcriptome. ASSA is available at https://sourceforge.net/projects/assa/
机译：在哺乳动物中发现数千名长的NONCODING RNA（LNCRNA）提出了关于他们的功能的问题。已经表明，其中一些参与其他RNA的转录后调节，并与其靶标形成分子间双链体。序列对准工具已被用于RNA RNA相互作用的转录组宽预测。然而，这种方法具有差的预测准确性，因为它们忽略了RNA的二级结构。将基于热力学的算法应用于长转录物的应用在大规模上没有计算地可行。在这里，我们描述了一种新的计算流水线ASA，它结合了序列对准和基于热力学的工具，以便在长转录物之间有效预测RNA RNA相互作用。为了测量杂交强度，计算所有推定双工的总能。在ASA中实施的主要新奇是能够快速估计观察到的互动能量的统计学意义。长RNA之间的大多数功能杂交被归类为统计学意义。 ASSA在四个测试集中的两个中的曲线下的区域方面表现出11种其他工具。此外，我们的结果强调了Alu对人体转录组中RNA RNA相互作用的独特性质。 ASSA在HTTPS://sourceForge.net/projects/assa//

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