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IntSplice: prediction of the splicing consequences of intronic single-nucleotide variations in the human genome
http://hdl.handle.net/2237/24971
http://hdl.handle.net/2237/24971e9da22e8-f8a0-479c-bda2-ffaae18bde04
名前 / ファイル | ライセンス | アクション |
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Manuscript_for_repository.pdf (959.8 kB)
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Item type | 学術雑誌論文 / Journal Article(1) | |||||
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公開日 | 2016-10-20 | |||||
タイトル | ||||||
タイトル | IntSplice: prediction of the splicing consequences of intronic single-nucleotide variations in the human genome | |||||
言語 | en | |||||
著者 |
Shibata, Akihide
× Shibata, Akihide× Okuno, Tatsuya× Mohammad, Alinoor Rahman× Azuma, Yoshiteru× Takeda, Jun-ichi× Masuda, Akio× Selcen, Duygu× Engel, Andrew G× Ohno, Kinji |
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アクセス権 | ||||||
アクセス権 | open access | |||||
アクセス権URI | http://purl.org/coar/access_right/c_abf2 | |||||
抄録 | ||||||
内容記述 | Precise spatiotemporal regulation of splicing is mediated by splicing cis-elements on pre-mRNA. Single-nucleotide variations (SNVs) affecting intronic cis-elements possibly compromise splicing, but no efficient tool has been available to identify them. Following an effect-size analysis of each intronic nucleotide on annotated alternative splicing, we extracted 105 parameters that could affect the strength of the splicing signals. However, we could not generate reliable support vector regression models to predict the percent-splice-in (PSI) scores for normal human tissues. Next, we generated support vector machine (SVM) models using 110 parameters to directly differentiate pathogenic SNVs in the Human Gene Mutation Database and normal SNVs in the dbSNP database, and we obtained models with a sensitivity of 0.800±0.041 (mean and s.d.) and a specificity of 0.849±0.021. Our IntSplice models were more discriminating than SVM models that we generated with Shapiro–Senapathy score and MaxEntScan::score3ss. We applied IntSplice to a naturally occurring and nine artificial intronic mutations in RAPSN causing congenital myasthenic syndrome. IntSplice correctly predicted the splicing consequences for nine of the ten mutants. We created a web service program, IntSplice (http://www.med.nagoya-u.ac.jp/neurogenetics/IntSplice) to predict splicing-affecting SNVs at intronic positions from −50 to −3. | |||||
言語 | en | |||||
内容記述タイプ | Abstract | |||||
内容記述 | ||||||
内容記述 | published online 24 March 2016 | |||||
言語 | en | |||||
内容記述タイプ | Other | |||||
出版者 | ||||||
言語 | en | |||||
出版者 | nature | |||||
言語 | ||||||
言語 | eng | |||||
資源タイプ | ||||||
資源タイプresource | http://purl.org/coar/resource_type/c_6501 | |||||
タイプ | journal article | |||||
出版タイプ | ||||||
出版タイプ | AM | |||||
出版タイプResource | http://purl.org/coar/version/c_ab4af688f83e57aa | |||||
DOI | ||||||
関連タイプ | isVersionOf | |||||
識別子タイプ | DOI | |||||
関連識別子 | https://doi.org/10.1038/jhg.2016.23 | |||||
ISSN | ||||||
収録物識別子タイプ | PISSN | |||||
収録物識別子 | 1434-5161 | |||||
書誌情報 |
en : Journal of Human Genetics 巻 61, p. 633-640, 発行日 2016 |
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著者版フラグ | ||||||
値 | author | |||||
URI | ||||||
識別子 | http://doi.org/10.1038/jhg.2016.23 | |||||
識別子タイプ | DOI | |||||
URI | ||||||
識別子 | http://hdl.handle.net/2237/24971 | |||||
識別子タイプ | HDL |