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

Xueqiu Jian, Eric Boerwinkle, Xiaoming Liu

Research output: Contribution to journalReview articlepeer-review

54 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)497-503
Number of pages7
JournalGenetics in Medicine
Volume16
Issue number7
DOIs
StatePublished - Jul 2014
Externally publishedYes

Keywords

  • Bioinformatics
  • End user
  • In silico prediction tool
  • Medical genetics
  • Splicing consensus region
  • Splicing mutation

ASJC Scopus subject areas

  • Genetics(clinical)

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