A biologist-oriented research assistant for context-aware pathway analysis, prioritization, and interpretation.
Analyze and interpret bulk or single-cell RNA-seq data through simple conversations. From data preprocessing and differential expression analysis to pathway analysis, integrative analysis, and post-analysis tasks, PAG-Agent streamlines the end-to-end transcriptomic analysis workflow.
Access gene and pathway annotations, retrieve relevant scientific references, generate biological hypotheses, refine academic writing, and more through lightweight retrieval and in-context learning strategies that enhance the reliability of AI-generated responses.
PAG-Agent introduces context-aware Over-Representation Analysis (cORA) that prioritizes biologically meaningful pathways using study-specific context rather than statistical significance alone.
PAG-Agent is a component of PAGER, developed through a collaboration among researchers from Auburn University (AU), the University of Alabama at Birmingham (UAB), Hanoi University of Science and Technology (HUST), and other partner institutions.