Identify enriched pathways and biological processes with ORA. By comparing your data against known gene sets, discover the underlying mechanisms relevant to your research.

Pluto's Over-representation Analysis (ORA) tool enables researchers to conduct comprehensive pathway enrichment analyses, shedding light on the biological processes and molecular pathways significantly associated with their datasets. Utilizing well-curated gene set databases, such as KEGG, GO, and Reactome, ORA in Pluto helps to contextualize high-throughput data within the larger framework of biological systems. This analysis is indispensable for interpreting gene expression patterns, identifying biomarkers, or understanding disease mechanisms by revealing how groups of related genes are over-represented in your sample compared to what would be expected by chance. With Pluto, this complex analysis is simplified, allowing biologists to quickly move from raw data to meaningful biological insights, fostering deeper understandings of the data's implications for disease, development, and health. Ultimately, ORA serves as a powerful bridge between quantitative data and qualitative biological significance, empowering researchers to make informed hypotheses and pursue targeted follow-up studies.