A Meta-Analysis Strategy for Gene Prioritization Using Gene Expression, SNP Genotype, and eQTL Data

<table class="figure-group"><tr class="fig-image" id="a"><td><object data="https://static.hindawi.com/articles/bmri/volume-2015/576349/figures/576349.fig.004a.svgz" name="576349.fig.004a" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(a) </b>Comparison of integration methods (prostate cancer)</td></tr><tr class="fig-image" id="b"><td><object data="https://static.hindawi.com/articles/bmri/volume-2015/576349/figures/576349.fig.004b.svgz" name="576349.fig.004b" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(b) </b>Comparison of integration methods (lung cancer)</td></tr></table>

<div>Comparison of the improved TOPSIS with other integration methods in terms of the ability to discover actual disease-related genes: (a) prostate cancer results, (b) lung cancer results.</div>

BioMed Research International

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Figure 4: A Meta-Analysis Strategy for Gene Prioritization Using Gene Expression, SNP Genotype, and eQTL Data 