title: GenoExp: a web tool for predicting gene expression levels from single nucleotide polymorphisms.
abstract: Understanding the effect of single nucleotide polymorphisms (SNPs) on the expression level of genes is an important goal. We recently published a study in which we devised a multi-SNP predictive model for gene expression in Lymphoblastoid cell lines (LCL), and showed that it can robustly predict the expression of a small number of genes in test individuals. Here, we validate the generality of our models by predicting expression profiles for genes in LCL in an independent study, and extend the pool of predictable genes for which we are able to explain more than 25% of their expression variability to 232 genes across 14 different cell types. As the number of people who obtained their SNP profiles through companies such as 23andMe is rising rapidly, we developed GenoExp, a web-based tool in which users can upload their individual SNP data and obtain predicted expression levels for the set of predictable genes across the 14 different cell types. Our tool thus allows users with biological knowledge to study the possible effects that their set of SNPs might have on these genes and predict their cell-specific expression levels relative to the population average.
  
  
  METHODS
  GenoExp is freely available at http://genie.weizmann.ac.il/pubs/GenoExp/.
authors: Department of Computer Science and Applied Mathematics and Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 76100, Israel.
authors: Ohad
authors: O
authors: Manor
authors: Department of Computer Science and Applied Mathematics and Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 76100, Israel Department of Computer Science and Applied Mathematics and Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 76100, Israel.
authors: Eran
authors: E
authors: Segal
mesh_terms: D002460:Cell Line; D020869:Gene Expression Profiling; D006801:Humans; D020407:Internet; D008957:Models, Genetic; D020641:Polymorphism, Single Nucleotide; D012984:Software
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