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Integrating genetic and gene expression evidence, review presentation

The following is a review presentation used for discussing the article Integrating genetic and gene expression evidence into genome-wide association analysis of gene sets by Xiong et all.

The article describes how SNP data and gene expression data (Microarray) can be integrated aiming for a better prediction of what sets of genes are responsible for a specific phenotypic class. Complexity and noise reduction is performed by grouping the genes into sets of which the members have a comparable function (pathway).

First the genes are scored separately. As there is no trivial way of weighting the SNP values for one gene, only the most significant SNP within a 250bp window is used. Then the score for both the SNP and the gene expression is merged by a scoring scheme described in the slides. After scoring the genes are sorted and enrichment for a gene set is verified.

The presentation has been constructed in Inkscape, exported to png to preserve the custom font editing, reimported and compiled using Sozi.

Link to this article