Rheumatoid arthritis (RA) is a chronic autoimmune disease that affects approximately 1% of the global population, leading to joint inflammation, pain, and progressive disability. In this study, we applied a computational pipeline to analyze a publicly available scRNA-seq dataset of peripheral blood mononuclear cells (PBMCs) from RA patients and healthy controls (Binvignat et al., 2024). Our goal was to identify transcriptional signatures associated with disease activity and explore the potential of gene expression features to distinguish between disease states
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