PathNet

PathNet is an algorithm to improve the interpretation of gene lists generated from high-throughput experimental studies, specifically by leveraging the connectivity information within canonical pathways. Traditional pathway enrichment analyses often treat pathways merely as sets of genes without considering the intricate network of inter- and intra-pathway connections. PathNet addresses this limitation by incorporating gene differential expression and the relationships of these genes within and across pathways to provide a more nuanced understanding of the biological processes involved in a given experimental condition.

Unlike conventional methods that primarily focus on identifying enriched pathways, PathNet goes a step further by using the connectivity of differentially expressed genes to score contextual associations among pathways. This approach allows for statistically identifying non-obvious dependencies and interactions among pathways, offering insights into complex biological relationships and mechanisms underlying the experimental conditions.