High-content imaging (HCI) provides researchers with a powerful tool for understanding cellular processes. Although phenotypic analysis generated through HCI is a potent technique to determine the overall cellular effects of a given treatment, it frequently produces complex data sets requiring extensive interpretation. The authors developed statistical analyses to decrease the time spent to determine the outcome of each HCI assay and to better understand complex phenotypic changes. To test these tools, the authors performed a comparison experiment between 2 types of oligonucleotide-mediated gene silencing (OMGS), antisense oligonucleotides (ASOs), and short, double-stranded RNAs (siRNAs). Although similar in chemical structure, these 2 methods differ in cellular mechanism of action and off-target effects. Using a library of 50 validated ASOs and siRNAs to the same targets, the authors characterized the differential effects of these 2 technologies using a HeLa cell G2-M cell cycle assay. Although knockdown of a variety of targets by ASOs or siRNAs affected the cell cycle profile, few of those targets were affected by both ASOs and siRNAs. Distribution analysis of population changes induced through target knockdown led to the identification of targets that, when inhibited, could affect the G2-M transition in the cell cycle in a statistically significant manner. The distinctly different mechanisms of action of these 2 forms of gene silencing may help define the use of these treatments in both clinical and research environments.