PASI: A novel pathway method to identify delicate group effects (original) (raw)

PASI is a novel computational method designed to identify subtle group effects in gene expression data. It involves a detailed preprocessing workflow to convert raw measurements into meaningful gene-level values, applying statistical techniques to filter noise and outliers. The final pathway scores are derived from node values in a ranked manner, highlighting delicate differences between samples. PASI aims to enhance the understanding of gene interactions and pathways by providing a clearer perspective on group effects, making it a valuable tool for genomic research.