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GenoExp: a web tool for predicting gene expression levels from single nucleotide polymorphisms
Author(s) -
Ohad Manor,
Eran Segal
Publication year - 2015
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btv050
Subject(s) - single nucleotide polymorphism , snp , gene , computational biology , upload , biology , genetics , population , set (abstract data type) , expression (computer science) , gene expression , web application , generality , computer science , world wide web , genotype , programming language , psychology , demography , sociology , psychotherapist
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.

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