snpXplorer: a web application to explore human SNP-associations and annotate SNP-sets.


Journal

Nucleic acids research
ISSN: 1362-4962
Titre abrégé: Nucleic Acids Res
Pays: England
ID NLM: 0411011

Informations de publication

Date de publication:
02 07 2021
Historique:
accepted: 01 05 2021
revised: 19 04 2021
received: 03 03 2021
pubmed: 29 5 2021
medline: 20 7 2021
entrez: 28 5 2021
Statut: ppublish

Résumé

Genetic association studies are frequently used to study the genetic basis of numerous human phenotypes. However, the rapid interrogation of how well a certain genomic region associates across traits as well as the interpretation of genetic associations is often complex and requires the integration of multiple sources of annotation, which involves advanced bioinformatic skills. We developed snpXplorer, an easy-to-use web-server application for exploring Single Nucleotide Polymorphisms (SNP) association statistics and to functionally annotate sets of SNPs. snpXplorer can superimpose association statistics from multiple studies, and displays regional information including SNP associations, structural variations, recombination rates, eQTL, linkage disequilibrium patterns, genes and gene-expressions per tissue. By overlaying multiple GWAS studies, snpXplorer can be used to compare levels of association across different traits, which may help the interpretation of variant consequences. Given a list of SNPs, snpXplorer can also be used to perform variant-to-gene mapping and gene-set enrichment analysis to identify molecular pathways that are overrepresented in the list of input SNPs. snpXplorer is freely available at https://snpxplorer.net. Source code, documentation, example files and tutorial videos are available within the Help section of snpXplorer and at https://github.com/TesiNicco/snpXplorer.

Identifiants

pubmed: 34048563
pii: 6287842
doi: 10.1093/nar/gkab410
pmc: PMC8262737
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

W603-W612

Informations de copyright

© The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.

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Auteurs

Niccolo Tesi (N)

Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.
Section Genomics of Neurodegenerative Diseases and Aging, Department of Clinical Genetics, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.
Delft Bioinformatics Lab, Delft University of Technology, Delft, The Netherlands.

Sven van der Lee (S)

Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.
Section Genomics of Neurodegenerative Diseases and Aging, Department of Clinical Genetics, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.

Marc Hulsman (M)

Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.
Section Genomics of Neurodegenerative Diseases and Aging, Department of Clinical Genetics, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.
Delft Bioinformatics Lab, Delft University of Technology, Delft, The Netherlands.

Henne Holstege (H)

Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.
Section Genomics of Neurodegenerative Diseases and Aging, Department of Clinical Genetics, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.
Delft Bioinformatics Lab, Delft University of Technology, Delft, The Netherlands.

Marcel J T Reinders (MJT)

Delft Bioinformatics Lab, Delft University of Technology, Delft, The Netherlands.

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Classifications MeSH