Abstract
Cellular pathways represent complex networks of molecular interactions that regulate biological processes, from signal transduction to metabolic functions. The ability to accurately quantify pathway activity in individual cells within their spatial context represents a crucial step toward understanding cellular behavior, tissue organization, and disease mechanisms. Here, we propose a new method for calculating pathway activity, PaaSc, based on multiple correspondence analysis (MCA) and linear regression. PaaSc can more accurately quantify the activity of a pathway in scRNA-seq and spatial transcriptomics.
Figure 1: PaaSc workflow