Identification of Common Biological Pathways and Drug Targets Across Multiple Respiratory Viruses Based on Human Host Gene Expression Analysis

Smith, Steven B.; Dampier, William; Tozeren, Aydin; Brown, James R.; Magid-Slav, Michal

To our knowledge the QC analysis performed with each GEO dataset is unique to this study. Although no dataset was completely disregarded after QC analysis, some samples were clear outliers, thus potentially skewing the data. Kauffmann and Huber have demonstrated improvements in signal-to-noise ratios after performing post normalization QC analysis to remove array outliers within an experiment [35] . Those authors used MA-plot and boxplots of the log-ratios to determine outliers instead of MAD scores, PCA and pair-wise correlations employed in this study. Fundamentally, the concept of data improvement after outlier removal applies regardless of the QC analysis approach. signaling 26 JUN, MYC, NFKBIA, STAT1, FOS, JAK2, HBEGF, DUSP1, DUSP4, PTK2, GSK3B, MMP9, NFKB2, PIK3R1, PRKCA, SOS2, TGFA CD40 signaling 31 IL8, JUN, NFKBIA, TNFAIP3, CCL2, FAS, IL6, IRF1, JAK2, PTGS2, TRAF1, CCND2, CD86, ICAM1, LYN, MAP2K3, MAP3K14, MAPK14, NFKB2, PIK3R1, TP53, TRAF5 IFNG signaling 24 MYC, STAT1, CDKN1A, EIF2AK2, IRF1, JAK2, SOCS1, STAT2, CAMK2G, CEBPB, ICAM1, MAPK14, PIK3R1, PRKCA, PTPN11 HRH1 signaling 25 IL8, JUN, NFKBIA, FOS, IL6, TNF, CSF2, F3, GNAQ, GNB4, GNG12, ICAM1