Genetic differences have been shown to contribute to gene expression variability. A complete evaluation of the associations between a whole genome scan with 550k Single Nucleotide Polymorphisms (SNPs) and 54k detectable expression levels (probesets) was performed on 176 human peripheral blood samples. The results are presented along with visualizations that reveal cis and trans gene expression regulatory effects. The algorithmic approach followed utilized a distributed computational system. The analysis was performed using a linear regression adjusting for all relevant covariates. Permutation testing on a random subset of the top results provided an indication of the significance levels adjusted for multiple testing and the non independence of SNPs due to linkage disequilibrium. The database of the produced results can be used as a resource to assess the functional impact of genetic polymorphisms to gene expression regulation. This resource is applicable across all disease areas.
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| http://dx.doi.org/10.1109/IEMBS.2009.5334061 | DOI Listing |
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