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The widespread of Next Generation Sequencing technologies accounted in recent years for the possibility to evaluate gene expression with great accuracy. Moreover, it allowed assessing differential gene expression among biological conditions with high sensitivity. However, state-of-the-art bioinformatics methodologies for differential gene expression evaluation from RNA Sequencing data still suffer from several drawbacks such as reduced specificity. In this paper we propose geneEx, a novel methodology and tool for differential gene expression evaluation from RNA Sequencing reads. By combining gene and exon expression evaluation and BioMart information, geneEX provides users with annotated lists of highly reliable differentially expressed genes. The results obtained in Sequencing Quality Control dataset proven the importance of a novel approach to lower False Positive predictions from current methodologies and the strength of the proposed methodological approach to increase the sensitivity of differentially expressed gene identification.

geneEx - A Novel Tool to Assess Differential Expression from Gene and Exon Sequencing Data