Evidence map›Paper›PMID 36765386›Full record

ReviewHuman genomics2023

SpliceAI-visual: a free online tool to improve SpliceAI splicing variant interpretation.

Jean-Madeleine de Sainte Agathe, Mathilde Filser, Bertrand Isidor, Thomas Besnard, Paul Gueguen, Aurélien Perrin, Charles Van Goethem, Camille Verebi, Marion Masingue, John Rendu and 12 more

Abstract readReview
In one paragraph

Review in Human genomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 133 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
133citing papers in PubMed, 2 pooled it
–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

133 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Genotype-phenotype correlations inOncology reviews · 2025
    Pooled it
  3. Article
  4. TECTB Variants Reveal Tectorial Membrane Vulnerability in Dominant Non-Syndromic Hearing Loss.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  5. Molecular genetics and metabolism reports · 2026
    Article
  6. Review
  7. Elevated Hemoglobin AJournal of clinical laboratory analysis · 2026
    Article
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  9. Article
  10. Review
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
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  20. Article

73 more citing papers are in PubMed but not listed here.

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

22 authors.

Jean-Madeleine de Sainte AgatheDépartement de Génétique Médicale, Groupe Hospitalier Universitaire de la Pitié Salpêtrière, AP-HP.Sorbonne Université, Laboratoire de Médecine Génomique Sorbonne Université, Paris, France. jean-madeleine.desainteagathe@aphp.fr.
Mathilde FilserDépartement de Génétique Médicale, Groupe Hospitalier Universitaire de la Pitié Salpêtrière, AP-HP.Sorbonne Université, Laboratoire de Médecine Génomique Sorbonne Université, Paris, France.
Bertrand IsidorNantes Université, CHU Nantes, Service de Génétique Médicale, 44000, Nantes, France.
Thomas BesnardNantes Université, CHU Nantes, Service de Génétique Médicale, 44000, Nantes, France.
Paul GueguenLaboratoire de Biologie Médicale Multi-Sites SeqOIA (laboratoire-seqoia.fr/), Paris, France.
Aurélien PerrinLaboratoire de Génétique Moléculaire, CHU de Montpellier, Université de Montpellier, Montpellier, France.
Charles Van GoethemLaboratoire de Génétique Moléculaire, CHU de Montpellier, Université de Montpellier, Montpellier, France.
Camille VerebiService de Médecine Génomique, Maladies de Système et d'Organe, Fédération de Génétique et de Médecine Génomique, DMU BioPhyGen, APHP Centre-Université Paris Cité, Hôpital Cochin, Paris, France.
Marion MasingueCentre de référence des maladies neuromusculaires Nord/Est/Ile de France, Hôpital Pitié-Salpêtrière, APHP, Paris, France.
John RenduInserm, U1216, CHU Grenoble Alpes, Grenoble Institut Neurosciences, Université Grenoble Alpes, Grenoble, France.
Mireille CosséeLaboratoire de Génétique Moléculaire, CHU de Montpellier, Université de Montpellier, Montpellier, France.
Anne BergougnouxLaboratoire de Génétique Moléculaire, CHU de Montpellier, Université de Montpellier, Montpellier, France.
Laurent FrobertLaboratoire de Biologie Médicale Multi-Sites SeqOIA (laboratoire-seqoia.fr/), Paris, France.
Julien BurattiDépartement de Génétique Médicale, Groupe Hospitalier Universitaire de la Pitié Salpêtrière, AP-HP.Sorbonne Université, Laboratoire de Médecine Génomique Sorbonne Université, Paris, France.
Élodie LejeuneDépartement de Génétique Médicale, Groupe Hospitalier Universitaire de la Pitié Salpêtrière, AP-HP.Sorbonne Université, Laboratoire de Médecine Génomique Sorbonne Université, Paris, France.
Éric Le GuernDépartement de Génétique Médicale, Groupe Hospitalier Universitaire de la Pitié Salpêtrière, AP-HP.Sorbonne Université, Laboratoire de Médecine Génomique Sorbonne Université, Paris, France.
Florence PasquierCentre mémoire, Inserm U1172 DistALZ, Licend, Univ Lille, CHU Lille, 59000, Lille, France.
Fabienne ClotDépartement de Génétique Médicale, Groupe Hospitalier Universitaire de la Pitié Salpêtrière, AP-HP.Sorbonne Université, Laboratoire de Médecine Génomique Sorbonne Université, Paris, France.
Vasiliki KalatzisINM, Univ Montpellier, INSERM, Montpellier, France.
Anne-Françoise RouxLaboratoire de Génétique Moléculaire, CHU de Montpellier, Université de Montpellier, Montpellier, France.
Benjamin CognéLaboratoire de Biologie Médicale Multi-Sites SeqOIA (laboratoire-seqoia.fr/), Paris, France.
David BauxLaboratoire de Génétique Moléculaire, CHU de Montpellier, Université de Montpellier, Montpellier, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

SpliceAI is an open-source deep learning splicing prediction algorithm that has demonstrated in the past few years its high ability to predict splicing defects caused by DNA variations. However, its outputs present several drawbacks: (1) although the numerical values are very convenient for batch filtering, their precise interpretation can be difficult, (2) the outputs are delta scores which can sometimes mask a severe consequence, and (3) complex delins are most often not handled. We present here SpliceAI-visual, a free online tool based on the SpliceAI algorithm, and show how it complements the traditional SpliceAI analysis. First, SpliceAI-visual manipulates raw scores and not delta scores, as the latter can be misleading in certain circumstances. Second, the outcome of SpliceAI-visual is user-friendly thanks to the graphical presentation. Third, SpliceAI-visual is currently one of the only SpliceAI-derived implementations able to annotate complex variants (e.g., complex delins). We report here the benefits of using SpliceAI-visual and demonstrate its relevance in the assessment/modulation of the PVS1 classification criteria. We also show how SpliceAI-visual can elucidate several complex splicing defects taken from the literature but also from unpublished cases. SpliceAI-visual is available as a Google Colab notebook and has also been fully integrated in a free online variant interpretation tool, MobiDetails ( https://mobidetails.iurc.montp.inserm.fr/MD ).

Indexed as

AlgorithmsRNA SplicingHumans

Identifiers

PMID36765386
PMCPMC9912651

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.