In silico tools for splicing defect prediction: a survey from the viewpoint of end users

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 th...

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Vydáno v:Genetics in medicine Ročník 16; číslo 7; s. 497 - 503
Hlavní autoři: Jian, Xueqiu, Boerwinkle, Eric, Liu, Xiaoming
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Nature Publishing Group US 01.07.2014
Elsevier Limited
Témata:
631/114
631/208/1516
631/208/1792
Biomedical and Life Sciences
Biomedicine
Computational Biology - methods
Computer Simulation
Genetic Variation - genetics
Human Genetics
Humans
Laboratory Medicine
Mutation
review
RNA Precursors - genetics
RNA Splicing - genetics
Software
splicing mutation
splicing consensus region
end user
medical genetics
in silico prediction tool
bioinformatics
ISSN:1098-3600, 1530-0366, 1530-0366
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Shrnutí: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 data sets 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. Genet Med 16 7, 497–503.
Bibliografie:ObjectType-Article-1
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ISSN:1098-3600
1530-0366
1530-0366
DOI:10.1038/gim.2013.176