SCAN is a large-scale database of genetics and genomics data associated to a web-interface and a set of methods and algorithms that can be used for mining the data in it. The database contains two categories of single nucleotide polymorphism (SNP) annotations:

  1. Physical-based annotation where SNPs are categorized according to their position relative to genes (intronic, inter-genic, etc.) and according to linkage disequilibrium (LD) patterns (an inter-genic SNP can be annotated to a gene if it is in LD with variation in the gene).
  2. Functional annotation where SNPs are classified according to their effects on expression levels, i.e. whether they are expression quantitative trait loci (eQTLs) for that gene.

One of the possible applications of SCAN is in conducting follow-up analyses of the results from genome-wide association studies (GWAS). GWAS generate genotype information on hundreds of thousands of SNPs that can be ranked according to their evidence for association with a given trait. Making sense of these data requires a number of steps related to the prioritization of variants (SNPs or CNVs) showing association to disease. Having as much information as possible about the variants is critical to sensible prioritization.

SCAN can be utilized in several ways including: (i) queries of the SNP and gene databases; (ii) analysis using the attached tools and algorithms; (iii) downloading files with SNP annotation for various GWA platforms.

This project has been developed at The University of Chicago (see the Contacts page for more details on the people involved) with support from the Genotype-Tissue Expression (GTEx) initiative (R01 MH090937), the ENDGAMe (ENhancing Development of Genome-wide Association Methods) initiative (U01 HL084715) and PAAR (Pharmacogenetics of Anti-cancer Agents Research; U01 GM61393), and a contribution from the Center for Neuropsychiatric Genetics and Molecular Neuroscience at the University of Chicago. Support for maintenance of the site includes the ENDGAMe (U01 HL084715), PAAR (U01 HL084715), The University Of Chicago DRTC (Diabetes Research and Training Center; P60 DK20595), and The University of Chicago Breast Cancer SPORE (P50 CA125183).