This study introduces SCimilarity, a novel metric learning framework designed to enhance the understanding of cellular profiles across various human tissues and diseases.
By querying a vast atlas of 23.4 million cells, we uncovered significant similarities in macrophage and fibroblast profiles linked to interstitial lung disease and other fibrotic conditions.
Our SCimilarity framework enables efficient searches among extensive scRNA-seq data, allowing researchers to discover unexpected cell states and their disease associations.
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