Featured publication: IPA used for integrative analysis to understand the EGF dependent transcriptome of HeLa cells.

RNA-Seq and microarray data analysis in IPA helped established validated gene sets with altered transcript levels after EGF treatment, and illuminated on the role of the EFG signaling pathway in cancer.

PathwayIn this study, Dr. Franc Lorens et al. analyzed RNA-Seq and microarray data in IPA to study the EGF dependent transcriptome of HeLa cells. The authors used IPA to establish a well validated gene set with transcript levels altered after EGF treatment. They used this robust gene list to build higher order networks of gene interaction by interconnecting associated networks, and supported and extended the important role of the EGF signaling pathway in cancer. In addition, they found an entirely new set of genes previously unrelated to the currently accepted EGF associated cellular functions.

Read the study:

Multiple platform assessment of the EGF dependent transcriptome by microarray and deep tag sequencing analysis.  Llorens et al.: Multiple platform assessment of the EGF dependent transcriptome by microarray and deep tag sequencing analysis. BMC Genomics 2011 12:326.