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

Our study used a systematic process to minimize potential technical noise that could have arisen from our comparative analysis of fifteen unique datasets from nine different cell types, and seven different array platforms. These measures included candidate dataset filtering followed by QC, differential gene expression and pathway enrichment analyses. A total of 14 out of 42, about one third of the total comparisons, were removed as a result of this filtering process, which is indicative of our conservative analysis approach. We had previously used largescale and merged-SAM analyses in integrating large-scale microarray datasets involving cancer tissues from multiple laboratories [33, 34] . However, the small sample size datasets used in the present study required a more rigorous methodology to identify data outliers.