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Approved research

A phenome-wide association study of copy number variation

Principal Investigator: Professor Nathan Pankratz
Approved Research ID: 17731
Approval date: January 24th 2017

Lay summary

To identify changes in the DNA, particularly large deletions and duplications of the genome, that are related to complex diseases and intermediate biomarkers The identification of genetic risk factors that are related to disease will help reveal the underlying biology and thereby expose targets for environmental modification and/or novel drug development. We will use the raw Affymetrix Axiom data (.CEL files) and apply a principal components analysis on these intensities to correct for DNA quality and batch effects. We will then perform a joint calling across all samples to determine potential deletions and duplications using our soon to be open-source Genvisis software package, which will also assess the quality of these calls and filter them down to a set of high quality calls (~1 year to complete). We will then associate the high quality calls with the phenotypes available, and replicate any findings using external data sources (~1 additional year). Full cohort; all samples with high quality intensity data will be analyzed