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Improving the Power of eQTL Studies by accounting for non-genetic Factors

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Discovering patterns of genetic variation that influence gene regulation has the potential to impact a broad range of biological endeavours, such as improving our understanding of genetic diseases. In this talk I will review state of art techniques to identify such relations between SNPs and gene expression levels and introduce a new model that significantly improves the statistical power of eQTL studies by explicitly accounting for non-genetic factors.

This talk is part of the Inference Group series.

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