3.6 years ago by
Correct me if I am wrong, this package takes into account all the genes expressed between your conditions and outlines the most enriched-significant pathway due to the most variable genes between your conditions. It is based on a regression model and by and large it takes in to account Differential Rank Conservation (DIRAC) and tries to build the pathway on those genes. If you find pathway hit for those genes, ideally these genes are enriched in your dataset and significantly changing when compared to all the genes in that pathway. So it is significantly showing the pathway. This should be also indicating that the genes that are involved in that pathway from your samples are differentially expressed. I would prefer to see the direction of this genes in order to understand which condition has it up-regulated. Just extract the genes of the pathway, map them with your expression matrix to see which are these in your samples. Make a heatmap of them and you will get the idea in which conditions they are up or down regulated. Pretty sure ERBB2 will also come out of it.
Alternatively do a differentially expression analysis , if its a microarray, I would here go for limma or even for that matter RankProd since the GSREG is based upon differential ranking. Overlap your DE genes with the genes of the pathway and plot the fold-changes for the ones that are matching. A simple barplot of them will show how these genes are behaving across both conditions. ERBB2 signalling pathway should be the one you target (so overlap all genes from that pathway with your DEGs) and plot that are common with fold changes between your conditions. I hope I made myself clear.