Friday, May 7, 2010

fitSNPs Server - Functionally interpolating Single Nucleotide Polymorphism

fitSNP analyzed all human microarray studies from the NCBI Gene Expression Omnibus (GEO), and found that differentially expressed genes were more likely to have disease-associated variants. The more experiments in which a gene was differentially expressed, the more likely it contained disease-associated variants. Based on this property, we derived a list of functionally interpolating SNPs (fitSNPs) to prioritize genes for disease association, and successfully prioritized type 1 diabetes genes from the top 7 loci of Wellcome Trust Case Control Consortium GWAS.  
  In gene page, all human genes are sorted by their likelihoods to have disease-associated variants along with experimently confirmed disease association if any. The likelihood is estimated by their differential expression ratios (DER). The higher DER a gene has, the more likely it will contain disease-associated variants. By clicking DER values, you can retrieve all microarray studies where this gene was differentially expressed. By clicking GAD, you can retrieve the experimental evidence for its disease association.  

  GWAS page describes a simple step-by-step tutorial to load fitSNPs into UCSC genome graph and visualize it along with your genomic data, such as GWAS data.  

  Some highly differentially expressed genes have not yet been associated with any disease, and are interesting investigative leads. We used fitSNPs to prioritize genes for diseases with previously identified loci and unknown molecular basis from OMIM, and suggested 2586 genes to be sequenced for 597 syndromes in the prediction page.

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