GRSN improves downstream pathway analysis using Gene Set Enrichment Analysis (GSEA)
In addition to examining the effects of GRSN on variance and statistical gene selection we have used the GSEA tool [25] to further analyze the effects of GRSN on downstream microarray data analysis. GSEA looks for the enrichment of known pathways (sets of genes) in the "gene signature" of a particular experiment. Part of the power of GSEA is that it considers the rank and significance of all genes in the gene signature. Therefore, GSEA will benefit both from an increase in True Positives and in a decrease in False Positive gene selection results with the use of GRSN. We have applied GSEA to both the RS and the SS datasets (using the 'R' implementation, version GSEA.1.0.R). The ability of GSEA to detect pathways shown to be relevant in each of these datasets is evaluated both with and without the use of GRSN. As shown in Table 2, both the Normalized Enrichment Score (NES) and the False Discovery Rate (FDR) for these relevant pathways are consistently improved and in some cases, pathways are only detected when GRSN is used. In particular, VEGF is identified as an important player in the SS study [24] but the associated "vegfPathway" is only identified by GSEA when the data is normalized with GRSN. Also, the RS study involves expression of the c-Myc oncoprotein, which is known to induce cell cycle, cell proliferation, cell growth, DNA damage, cell death, and HTERT (see references in Table 2). GSEA identifies all of these pathways to be enriched with c-Myc expression compared to control and as shown in Table 2 all of these pathways are detected at a higher NES and much more significant FDR value when GRSN is used.
Table 2  GRSN aids Gene Set Enrichment Analysis (GSEA).  GSEA is applied to the SS and RS datasets. Pathways known to be active in these datasets are shown and referenced. For each selected pathway, the Normalized Enrichment Score (NES) and the False Discovery Rate (FDR), as reported by GSEA, are shown. NES and FDR values are shown both for data processed with RMA alone (Without GRSN) and for data processed with RMA followed by GRSN (With GRSN) as indicated.