The Ensembl COVID-19 resource: Ongoing integration of public SARS-CoV-2 data

ABSTRACTThe Ensembl COVID-19 browser (covid-19.ensembl.org) was launched in May 2020 in response to the ongoing pandemic. It is Ensembl’s contribution to the global efforts to develop treatments, diagnostics and vaccines for COVID-19, and it supports research into the genomic epidemiology and evolution of the SARS-CoV-2 virus. This freely available resource incorporates a new Ensembl gene set, multiple sets of variants, and alignments of annotation from several resources against the reference assembly for SARS-CoV-2. It represents the first virus to be encompassed within the Ensembl platform. Additional data are being continually integrated via our new rapid release protocols alongside tools such as the Ensembl Variant Effect Predictor. Here we describe the data and infrastructure behind the resource and discuss future work.

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Finding a Needle in a Haystack: Variant Effect Predictor (VEP) Prioritizes Disease Causative Variants from Millions of Neutral Ones

Essentials of Bioinformatics, Volume II ◽

10.1007/978-3-030-18375-2_6 ◽

2019 ◽

pp. 85-104

Author(s):

Yashvant Khimsuriya ◽

Salil Vaniyawala ◽

Babajan Banaganapalli ◽

Muhammadh Khan ◽

Ramu Elango ◽

...

Keyword(s):

Variant Effect Predictor ◽

Variant Effect

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

Bioinformatics ◽

10.1093/bioinformatics/bty960 ◽

2018 ◽

Vol 35 (13) ◽

pp. 2315-2317 ◽

Cited By ~ 5

Author(s):

Jannah Shamsani ◽

Stephen H Kazakoff ◽

Irina M Armean ◽

Will McLaren ◽

Michael T Parsons ◽

...

Keyword(s):

Splice Site ◽

Disease Risk ◽

Cancer Susceptibility ◽

Mrna Splicing ◽

Supplementary Information ◽

Mendelian Disease ◽

Functional Protein ◽

Variant Effect Predictor ◽

Cancer Susceptibility Genes ◽

Variant Effect

Abstract Summary Assessing 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.

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Syntactic and cognitive issues in investigating gendered coreference

10.31234/osf.io/6cf57 ◽

2019 ◽

Author(s):

Lauren Marie Ackerman

Keyword(s):

Additional Data ◽

Personal Names ◽

Conceptual Representations ◽

Linguistic Patterns ◽

Biological Aspects ◽

Future Work ◽

Insight Into

This paper presents a framework for how the multifaceted nature of "gender" (human and linguistic) interacts with grammatical operations such as coreference dependency formation. It frames the question through the lens of English, in which it focuses on how personal names and referents who identify as nonbinary can provide insight into the conceptual representations of gender. Additional data from a variety of modern languages supports a model of how gender might be cognitively represented such that the observed linguistic patterns are available. A three-tiered model of gender is proposed that unites grammatical, cognitive, social, and biological aspects and describes how implications of this model might be tested in future work.

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Rich annotation of DNA sequencing variants by leveraging the Ensembl Variant Effect Predictor with plugins

Briefings in Bioinformatics ◽

10.1093/bib/bbu008 ◽

2014 ◽

Vol 16 (2) ◽

pp. 255-264 ◽

Cited By ~ 26

Author(s):

Michael Yourshaw ◽

S. Paige Taylor ◽

Aliz R. Rao ◽

Martín G. Martín ◽

Stanley F. Nelson

Keyword(s):

Dna Sequencing ◽

Variant Effect Predictor ◽

Variant Effect

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Annotating and prioritising genomic variants using the Ensembl Variant Effect Predictor ‐ a tutorial

Human Mutation ◽

10.1002/humu.24298 ◽

2021 ◽

Author(s):

Sarah E. Hunt ◽

Benjamin Moore ◽

Ridwan M. Amode ◽

Irina M. Armean ◽

Diana Lemos ◽

...

Keyword(s):

Variant Effect Predictor ◽

Genomic Variants ◽

Variant Effect

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The Ensembl Variant Effect Predictor

Genome Biology ◽

10.1186/s13059-016-0974-4 ◽

2016 ◽

Vol 17 (1) ◽

Cited By ~ 1789

Author(s):

William McLaren ◽

Laurent Gil ◽

Sarah E. Hunt ◽

Harpreet Singh Riat ◽

Graham R. S. Ritchie ◽

...

Keyword(s):

Variant Effect Predictor ◽

Variant Effect

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What went wrong with variant effect predictor performance for the PCM1 challenge

Human Mutation ◽

10.1002/humu.23832 ◽

2019 ◽

Vol 40 (9) ◽

pp. 1486-1494 ◽

Cited By ~ 3

Author(s):

Maximilian Miller ◽

Yanran Wang ◽

Yana Bromberg

Keyword(s):

Variant Effect Predictor ◽

Variant Effect

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Ensembl 2021

Nucleic Acids Research ◽

10.1093/nar/gkaa942 ◽

2020 ◽

Vol 49 (D1) ◽

pp. D884-D891 ◽

Cited By ~ 1

Author(s):

Kevin L Howe ◽

Premanand Achuthan ◽

James Allen ◽

Jamie Allen ◽

Jorge Alvarez-Jarreta ◽

...

Keyword(s):

Comparative Genomics ◽

Evolutionary History ◽

Genomic Data ◽

Regulatory Elements ◽

Vertebrate Species ◽

Variant Effect Predictor ◽

Rapid Release ◽

History Of ◽

Genome Browsers ◽

Gene Structures

Abstract The Ensembl project (https://www.ensembl.org) annotates genomes and disseminates genomic data for vertebrate species. We create detailed and comprehensive annotation of gene structures, regulatory elements and variants, and enable comparative genomics by inferring the evolutionary history of genes and genomes. Our integrated genomic data are made available in a variety of ways, including genome browsers, search interfaces, specialist tools such as the Ensembl Variant Effect Predictor, download files and programmatic interfaces. Here, we present recent Ensembl developments including two new website portals. Ensembl Rapid Release (http://rapid.ensembl.org) is designed to provide core tools and services for genomes as soon as possible and has been deployed to support large biodiversity sequencing projects. Our SARS-CoV-2 genome browser (https://covid-19.ensembl.org) integrates our own annotation with publicly available genomic data from numerous sources to facilitate the use of genomics in the international scientific response to the COVID-19 pandemic. We also report on other updates to our annotation resources, tools and services. All Ensembl data and software are freely available without restriction.

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Annotating and prioritising genomic variants using the Ensembl Variant Effect Predictor - a tutorial

10.22541/au.162460842.27880071/v1 ◽

2021 ◽

Author(s):

Sarah Hunt ◽

Benjamin Moore ◽

M. Amode ◽

Irina Armean ◽

Diana Lemos ◽

...

Keyword(s):

Application Programming Interface ◽

Access Methods ◽

Variant Effect Predictor ◽

Genomic Variants ◽

Representational State Transfer ◽

Gene Sets ◽

Command Line Tool ◽

Application Programming ◽

Variant Effect ◽

User Friendly

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 consequence 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 SIFT and CADD. Ensembl VEP includes filtering options to customise variant prioritisation. 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 (REST) application programming interface (API) 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, visualisation 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.

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The Ensembl Variant Effect Predictor

10.1101/042374 ◽

2016 ◽

Cited By ~ 10

Author(s):

William McLaren ◽

Laurent Gil ◽

Sarah E Hunt ◽

Harpreet Singh Riat ◽

Graham R. S. Ritchie ◽

...

Keyword(s):

Web Interface ◽

Large Collection ◽

High Quality ◽

Binding Motifs ◽

Variant Effect Predictor ◽

Genomic Variants ◽

Coding Regions ◽

Variation Data ◽

Variant Effect ◽

Program Interface

The Ensembl Variant Effect Predictor (VEP) is a powerful toolset for the analysis, annotation and prioritization of genomic variants, including in non-coding regions. The VEP accurately predicts the effects of sequence variants on transcripts, protein products, regulatory regions and binding motifs by leveraging the high quality, broad scope, and integrated nature of the Ensembl databases. In addition, it enables comparison with a large collection of existing publicly available variation data within Ensembl to provide insights into population and ancestral genetics, phenotypes and disease. The VEP is open source and free to use. It is available via a simple web interface (http://www.ensembl.org/vep), a powerful downloadable package, and both Ensembl’s Perl and REST application program interface (API) services.

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