SNPsnap: a Web-based tool for identification and annotation of matched SNPs

Tune H. Pers; Pascal Timshel; Joel N Hirschhorn

doi:10.1093/bioinformatics/btu655

SNPsnap: a Web-based tool for identification and annotation of matched SNPs

Tune H. Pers, Pascal Timshel, Joel N Hirschhorn

66 Citationer (Scopus)

Abstract

An important computational step following genome-wide association studies (GWAS) is to assess whether disease or trait-associated single-nucleotide polymorphisms (SNPs) enrich for particular biological annotations. SNP-based enrichment analysis needs to account for biases such as co-localization of GWAS signals to gene-dense and high linkage disequilibrium (LD) regions, and correlations of gene size, location and function. The SNPsnap Web server enables SNP-based enrichment analysis by providing matched sets of SNPs that can be used to calibrate background expectations. Specifically, SNPsnap efficiently identifies sets of randomly drawn SNPs that are matched to a set of query SNPs based on allele frequency, number of SNPs in LD, distance to nearest gene and gene density.

Originalsprog	Engelsk
Tidsskrift	Bioinformatics
Vol/bind	31
Udgave nummer	3
Sider (fra-til)	418-420
Antal sider	3
ISSN	1367-4803
DOI	https://doi.org/10.1093/bioinformatics/btu655
Status	Udgivet - 15 jul. 2015
Udgivet eksternt	Ja

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10.1093/bioinformatics/btu655

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N2 - An important computational step following genome-wide association studies (GWAS) is to assess whether disease or trait-associated single-nucleotide polymorphisms (SNPs) enrich for particular biological annotations. SNP-based enrichment analysis needs to account for biases such as co-localization of GWAS signals to gene-dense and high linkage disequilibrium (LD) regions, and correlations of gene size, location and function. The SNPsnap Web server enables SNP-based enrichment analysis by providing matched sets of SNPs that can be used to calibrate background expectations. Specifically, SNPsnap efficiently identifies sets of randomly drawn SNPs that are matched to a set of query SNPs based on allele frequency, number of SNPs in LD, distance to nearest gene and gene density.

AB - An important computational step following genome-wide association studies (GWAS) is to assess whether disease or trait-associated single-nucleotide polymorphisms (SNPs) enrich for particular biological annotations. SNP-based enrichment analysis needs to account for biases such as co-localization of GWAS signals to gene-dense and high linkage disequilibrium (LD) regions, and correlations of gene size, location and function. The SNPsnap Web server enables SNP-based enrichment analysis by providing matched sets of SNPs that can be used to calibrate background expectations. Specifically, SNPsnap efficiently identifies sets of randomly drawn SNPs that are matched to a set of query SNPs based on allele frequency, number of SNPs in LD, distance to nearest gene and gene density.

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SNPsnap: a Web-based tool for identification and annotation of matched SNPs

Abstract

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