Evidence map›Paper›PMID 30475984›Full record

ArticleBioinformatics (Oxford, England)2019

A plugin for the Ensembl Variant Effect Predictor that uses MaxEntScan to predict variant spliceogenicity.

Jannah Shamsani, Stephen H Kazakoff, Irina M Armean, Will McLaren, Michael T Parsons, Bryony A Thompson, Tracy A O'Mara, Sarah E Hunt, Nicola Waddell, Amanda B Spurdle

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers.

0numbers the graph read from it
0cells of the map it votes in
60citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

60 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Genetic analysis of neurodegenerative diseases.The Journal of clinical investigation · 2026
    Review
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  7. Article
  8. Article
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  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Case Report: Evaluation ofFrontiers in medicine · 2025
    Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Jannah ShamsaniDepartment of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane QLD, Australia.
Stephen H KazakoffDepartment of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane QLD, Australia.
Irina M ArmeanEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK.
Will McLarenEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK.
Michael T ParsonsDepartment of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane QLD, Australia.
Bryony A ThompsonCentre for Epidemiology and Biostatistics, School of Population and Global Health, University of Melbourne, Melbourne VIC, Australia.
Tracy A O'MaraDepartment of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane QLD, Australia.
Sarah E HuntEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK.
Nicola WaddellDepartment of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane QLD, Australia.
Amanda B SpurdleDepartment of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane QLD, Australia.

Funding

GENCODE Resource ProjectU41HG007234 · NHGRI · SANGER INSTITUTE · PI FLICEK, PAUL · 2013 to 2020
$20.3M
GWAS CatalogU41HG007823 · NHGRI · EUROPEAN MOLECULAR BIOLOGY LABORATORY · PI PARKINSON, HELEN ELIZABETH · 2014 to 2021
$6.7M
Biotechnology and Biological Sciences Research Council BB/M011615/1Biotechnology and Biological Sciences Research Council BB/N019563/1NHGRI NIH HHS U41 HG007234NHGRI NIH HHS U41 HG007823Wellcome Trust WT104947/Z/14/ZWellcome Trust WT108749/Z/15/AWellcome Trust WT108749/Z/15/ZWellcome Trust WT200990/Z/16/ZWellcome Trust WT201535/Z/16/ZWellcome Trust WT212925/Z/18/Z
6 · The paper itself

Abstract

summaryAssessing the pathogenicity of genetic variants can be a complex and challenging task. Spliceogenic variants, which alter mRNA splicing, may yield mature transcripts that encode non-functional protein products, an important predictor of Mendelian disease risk. However, most variant annotation tools do not adequately assess spliceogenicity outside the native splice site and thus the disease-causing potential of variants in other intronic and exonic regions is often overlooked. Here, we present a plugin for the Ensembl Variant Effect Predictor that packages MaxEntScan and extends its functionality to provide splice site predictions using a maximum entropy model. The plugin incorporates a sliding window algorithm to predict splice site loss or gain for any variant that overlaps a transcript feature. We also demonstrate the utility of the plugin by comparing our predictions to two mRNA splicing datasets containing several cancer-susceptibility genes. AVAILABILITY AND IMPLEMENTATION: Source code is freely available under the Apache License, Version 2.0: https://github.com/Ensembl/VEP_plugins. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

RNA SplicingSoftwareAlgorithmsExonsIntrons

Identifiers

PMID30475984
PMCPMC6596880

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.