Researchers at the Josep Carreras Leukaemia Research Institute have demonstrated that combining data from different origins enables a more precise characterization of cell type’s diversity into tissues and organs. The team also introduced scOMM, a new machine learning tool for classifying and comparing cell types across the distinct data modalities. The tool is openly available to researchers worldwide and has been successfully tested in kidney tissue, one of the most cellularly diverse organs in the human body and validated in blood and heart tissue. As the results demonstrate, when it comes to understanding complex tissues, the whole is greater than the sum of its parts.
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