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

Tune H. Pers*, Pascal Timshel* and Joel N. Hirschhorn

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.

Bioinformatics, first published online October 13, 2014 doi:10.1093/bioinformatics/btu655

SNPsnap main usage

Match input SNPs
SNPsnap is designed to generate matched sets of SNPs that can be used to calibrate background expectations in SNP-based enrichment analysis.

Annotate input SNPs using 1000 Genomes data
SNPsnap allows users to quickly retrieve 1000 Genomes population specific annotation about SNP locus bounderies, nearest genes, genes in loci, minor allele frequencies and much more.

Tips & Tricks

Tip #1: fast SNP input annotation
SNPsnap's main purpose is to match input SNPs. However, many users are often only interested in annotating their input SNPs using 1000 Genomes population specific genotypes. If this is also your main goal, you can set Number of matched SNPs to a low value (e.g. 1), which will highly speed up the runtime for your job. Of course you should also make sure to enable Annotate input SNPs.

Tip #2: independence of SNPs (clumping)
SNPsnap has a nifty extra feature to check the independence of your input SNPs. This feature was originally designed to facilitate proper use of the SNP-matching results. However, many of our users find it useful on its own - just as a quick way to clump your SNPs using PLINK 1.9's algorithm.