In silico tools for splicing defect prediction: a survey from the viewpoint of end users.
In silico tools for splicing defect prediction: a survey from the viewpoint of end users.
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DOI：
10.1038/gim.2013.176
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发表时间：
2014-07
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影响因子：
--
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--
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RNA剪接是切割内含子和剪接外显子的过程。剪接信号的准确识别是这一过程的关键，影响剪接的突变在遗传病病因中占有相当大的比例。分析患者的RNA样本是检测剪接缺陷的最直接和最可靠的方法。然而，目前的技术限制限制了它在常规临床实践中的使用。在电子计算机中，预测剪接突变的潜在后果的工具在日常诊断活动中可能是有用的。在这篇综述中，我们从最终用户的角度为医学遗传学家提供了一些基本的见解，以了解一些在剪接缺陷预测中最流行的电子工具。正在研究大型数据集的相关领域的生物信息学家也可能从这项审查中受益。具体而言，我们关注的是那些主要目的是预测5‘和3’剪接共识区域内突变的影响的工具：简要介绍了不同工具使用的算法及其主要优缺点；总结了它们的输入和输出格式；并讨论了解释、评估和展望。
RNA splicing is the process during which introns are excised and exons are spliced. The precise recognition of splicing signals is critical to this process and mutations affecting splicing comprise a considerable proportion of genetic disease etiology. Analysis of RNA samples from the patient is the most straightforward and reliable method to detect splicing defects. However, currently the technical limitation prohibits its use in routine clinical practice. In silico tools that predict potential consequences of splicing mutations may be useful in daily diagnostic activities. In this review, we provide medical geneticists with some basic insights into some of the most popular in silico tools for splicing defect prediction, from the viewpoint of end-users. Bioinformaticians in relevant areas who are working on huge datasets may also benefit from this review. Specifically, we focus on those tools whose primary goal is to predict the impact of mutations within the 5′ and 3′ splicing consensus regions: the algorithms used by different tools as well as their major advantages and disadvantages are briefly introduced; the formats of their input and output are summarized; and the interpretation, evaluation, and prospection are also discussed.
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影响因子：
64.5
作者：
Cooper TA;Wan L;Dreyfuss G
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LEFEBVRE, S;BURGLEN, L;MELKI, J
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Vorechovsky, Igor