Link to bioRxiv paper:
http://biorxiv.org/cgi/content/short/2023.03.27.534310v1?rss=1
Authors: Davis, D., Wizel, A., Drier, Y.
Abstract:
Inferring which and how biological pathways and gene sets are changing is a key question in many studies that utilize single-cell RNA sequencing. While typically these questions are addressed by quantifying the enrichment of known gene sets in lists of genes derived from global analysis, there are many benefits to first inferring pathway status of each pathway in each cell. Here we report on a new tool that allows such inference, apply it on several datasets, and demonstrate the improvement over current state of the art methods. We also demonstrate how it can be used to better classify cells based on gene set scores instead of single genes and the benefits of this approach.
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