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For those interested in understanding both copy number variation and gene/miRNA expression across the same sample set.

Integration of genomic data from different modalities (e.g. copy number variation, gene expression, miRNA expression, etc.) is a major area of interest with the growing ability to extract such information using high throughput methods such as microarrays. In this presentation we will highlight how BioDiscovery‚Äôs Nexus Copy Number and Nexus Expression software solutions can be used by research scientists to integrate knowledge gain from one modality with another to create a complete picture of the underlying biology. We will use data generated by The Cancer Genome Atlas (TCGA) project on a set of ovarian cancer samples. The data will include copy number and LOH analysis from SNP arrays as well as mRNA and miRNA data generated using microarray technology. We will show how to identify regions of significant copy number change that are predictive of survival and how the expression of the genes in these regions can also be predictive of survival. Time permitting, we will also look at the effect of miRNA expression changes on target gene expression.