Journal
BIOINFORMATICS
Volume 31, Issue 3, Pages 418-420Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btu655
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Funding
- Danish Council for Independent Research Medical Sciences (FSS)
- Alfred Benzon Foundation
- Novo Scholarship Programme
- National Institute of Diabetes and Digestive and Kidney Diseases [2R01DK075787]
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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 genedense 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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