Evidence map›Paper›PMID 34816521›Full record

ArticleHuman mutation2022

Annotating and prioritizing genomic variants using the Ensembl Variant Effect Predictor-A tutorial.

Sarah E Hunt, Benjamin Moore, Ridwan M Amode, Irina M Armean, Diana Lemos, Aleena Mushtaq, Andrew Parton, Helen Schuilenburg, Michał Szpak, Anja Thormann and 5 more

Abstract read
In one paragraph

Article in Human mutation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
63citing papers in PubMed, 4 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

63 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
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  9. Diagnostics (Basel, Switzerland) · 2026
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3 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

15 authors.

Sarah E HuntEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK.ORCID 0000-0002-8350-1235
Benjamin MooreEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK.ORCID 0000-0002-0918-4753
Ridwan M AmodeEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK.
Irina M ArmeanEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK.
Diana LemosEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK.
Aleena MushtaqEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK.
Andrew PartonEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK.
Helen SchuilenburgEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK.
Michał SzpakEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK.
Anja ThormannEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK.
Emily PerryEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK.
Stephen J TrevanionEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK.
Paul FlicekEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK.
Andrew D YatesEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK.
Fiona CunninghamEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK.ORCID 0000-0002-7445-2419

Funding

Biotechnology and Biological Sciences Research Council BB/S020152/1Wellcome WT108749/Z/15/ZWellcome WT200990/Z/16/ZWellcome WT212925/Z/18/ZWellcome Trust 108749Wellcome Trust 200990Wellcome Trust 201535Wellcome Trust 212925
6 · The paper itself

Abstract

The Ensembl Variant Effect Predictor (VEP) is a freely available, open-source tool for the annotation and filtering of genomic variants. It predicts variant molecular consequences using the Ensembl/GENCODE or RefSeq gene sets. It also reports phenotype associations from databases such as ClinVar, allele frequencies from studies including gnomAD, and predictions of deleteriousness from tools such as Sorting Intolerant From Tolerant and Combined Annotation Dependent Depletion. Ensembl VEP includes filtering options to customize variant prioritization. It is well supported and updated roughly quarterly to incorporate the latest gene, variant, and phenotype association information. Ensembl VEP analysis can be performed using a highly configurable, extensible command-line tool, a Representational State Transfer application programming interface, and a user-friendly web interface. These access methods are designed to suit different levels of bioinformatics experience and meet different needs in terms of data size, visualization, and flexibility. In this tutorial, we will describe performing variant annotation using the Ensembl VEP web tool, which enables sophisticated analysis through a simple interface.

Indexed as

GenomicsSoftwareComputational BiologyDatabases, GeneticGene FrequencyHumansMolecular Sequence AnnotationPhenotypefiltering“molecular consequence”variant annotationvariant prioritisationVEP

Identifiers

PMID34816521
PMCPMC7613081

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.