Abstract
Summary: 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.
Availability and implementation: SNPsnap server is available at http://www.broadinstitute.org/mpg/snpsnap/. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.
Availability and implementation: SNPsnap server is available at http://www.broadinstitute.org/mpg/snpsnap/. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.
Original language | English |
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Journal | Bioinformatics |
Volume | 31 |
Issue number | 3 |
Pages (from-to) | 418-420 |
Number of pages | 3 |
ISSN | 1367-4803 |
DOIs | |
Publication status | Published - 2015 |