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Nexus Expression allows researchers to quickly analyze and explore data with confidence and to easily identify differentially expressed genes, affected pathways, and common phenotypes between gene expression profiles, whether the source data is microarray or RNA-Seq data. Ease of statistical comparisons between subgroups, clustering, gene enrichment analysis and integration with copy number changes will be some of the features covered in this presentation. Cancer-specific tools in Nexus Expression include Cox-regression analysis to identify genes predictive of survival and generation of K-M plots. This presentation will take you through the process from data loading and processing to identification of affected pathways using a solid tumor data set.